阅读说明：本技术 雷达泄漏测量更新 (Radar leak measurement update ) 是由 黄文隆 邱文勋 乌萨·瓦 于 2020-02-25 设计创作，主要内容包括：本公开涉及将被提供用于支持超过诸如长期演进(LTE)的第四代(4G)通信系统的更高数据速率的准第五代(5G)或5G通信系统。一种用于更新用于泄漏消除的泄漏响应的方法和电子装置。所述电子装置包括雷达收发器、存储器及处理器。所述处理器被配置为：确定是否有对象在所述雷达收发器的附近区域内并且在所述雷达收发器的视场内,响应于确定没有对象接近所述雷达收发器并且在所述雷达收发器的视场内,获得所述雷达收发器的泄漏测量,以及基于所述泄漏测量来更新用于泄漏消除的泄漏响应。(The present disclosure relates to a quasi-fifth generation (5G) or 5G communication system to be provided for supporting higher data rates over fourth generation (4G) communication systems such as Long Term Evolution (LTE). A method and electronic device for updating a leak response for leak elimination. The electronic device includes a radar transceiver, a memory, and a processor. The processor is configured to: the method further includes determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver, obtaining a leakage measurement of the radar transceiver in response to determining that no object is proximate to and within the field of view of the radar transceiver, and updating a leakage response for leakage cancellation based on the leakage measurement.)

1. An electronic device, comprising:

a radar transceiver;

a memory configured to store data; and

a processor operatively connected to the radar transceiver,

the processor is configured to:

determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver;

in response to determining that no object is proximate to and within a field of view of the radar transceiver, obtaining a leakage measurement of the radar transceiver; and

updating a leak response for leak cancellation based on the leak measurement.

2. The electronic device of claim 1, wherein the processor is further configured to:

detecting a change in at least one state variable of the electronic device; and

determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver by determining whether the object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver in response to detecting the change in the at least one state variable.

3. The electronic device of claim 1, wherein the processor is configured to:

determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver by performing a successful radar-based measurement of a target located outside the vicinity of the radar transceiver, and

the leakage measurement is obtained by extracting a signal corresponding to a set of leakage taps from the successful radar-based measurement.

4. The electronic device of claim 1, wherein the processor is configured to:

determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver by confirming that reflected energy from an area proximate the radar transceiver is proportional to a background level.

5. The electronic device of claim 1, wherein the processor is configured to:

determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver by also performing successful non-radar sensor-based measurements of targets located outside the vicinity of the radar transceiver, an

The leakage measurement is obtained by measuring a leakage signal between a transmitter and a receiver of the radar transceiver.

6. A method for updating a leak response, the method comprising:

determining, by an electronic device having a radar transceiver, whether an object is within a vicinity of and within a field of view of the radar transceiver;

in response to determining that no object is proximate to the radar transceiver and within a field of view of the radar transceiver, obtaining a leakage measurement of the radar transceiver; and

updating the leak response for leak cancellation based on the leak measurement.

7. The method of claim 6, further comprising: detecting a change in at least one state variable of the electronic device; and

wherein determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver comprises: in response to detecting the change in the at least one state variable, determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver.

8. The method of claim 6, wherein determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver further comprises: performing successful radar-based measurements on targets located outside the vicinity of the radar transceiver, and

wherein the step of obtaining the leak measurement further comprises: signals corresponding to a set of leakage taps are extracted from the successful radar-based measurements.

9. The method of claim 6, wherein determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver further comprises confirming that reflected energy from within the vicinity of the radar transceiver is proportional to a background level.

10. The method of claim 6, wherein determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver further comprises: performing successful non-radar sensor based measurements on targets located outside the vicinity of the radar transceiver, and

wherein obtaining the leakage measurement further comprises measuring a leakage signal between a transmitter and a receiver of the radar transceiver.

11. A non-transitory computer-readable medium storing instructions that, when executed by a processor of an electronic device, cause the electronic device to:

determining, by the electronic device, whether an object is within a vicinity of and within a field of view of a radar transceiver of the electronic device;

obtaining a leakage measurement of the radar transceiver in response to determining that no object is proximate to and within a field of view of the radar transceiver; and

updating a leak response for leak cancellation based on the leak measurement.

12. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to:

detecting a change in at least one state variable of the electronic device; and

determining whether an object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver by determining whether the object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver in response to detecting the change in the at least one state variable.

13. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to:

determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver by performing a successful radar-based measurement of a target located outside the vicinity of the radar transceiver, and

the leakage measurement is obtained by extracting a signal corresponding to a set of leakage taps from the successful radar-based measurement.

14. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to:

further determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver by performing successful non-radar sensor based measurements of targets located outside the vicinity of the radar transceiver, an

The leakage measurement is obtained by measuring a leakage signal between a transmitter and a receiver of the radar transceiver.

15. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to:

determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver by determining with a non-radar proximity sensor that no target is detected within the vicinity of the radar transceiver, and

the leakage measurement is obtained by measuring a leakage signal between a transmitter and a receiver of the radar transceiver.

Technical Field

The present disclosure relates generally to addressing signal leakage in radar applications. More particularly, the present disclosure relates to timely updating of radar leakage measurements for radar transceivers.

Background

In order to meet the increasing demand for wireless data services since the deployment of 4G communication systems, efforts have been made to develop improved 5G or quasi-5G communication systems. Accordingly, the 5G or quasi-5G communication system is also referred to as a "super 4G network" or a "post-LTE system".

The 5G communication system is considered to be implemented in a higher frequency (millimeter wave) band (for example, 60GHz band) in order to achieve a higher data rate. In order to reduce propagation loss of radio waves and increase transmission distance, beamforming, massive Multiple Input Multiple Output (MIMO), full-dimensional MIMO (FD-MIMO), array antenna, analog beamforming, massive antenna techniques are discussed in the 5G communication system.

Further, in the 5G communication system, development for system network improvement is being performed based on advanced small cells, a cloud Radio Access Network (RAN) ultra-dense network, device-to-device (D2D) communication, wireless backhaul, a mobile network, cooperative communication, coordinated multipoint (CoMP), receiving side interference cancellation, and the like.

In 5G systems, hybrid FSK and QAM modulation (FQAM) and Sliding Window Superposition Coding (SWSC) have been developed as Advanced Coding Modulation (ACM), and filter bank multi-carrier (FBMC), non-orthogonal multiple access (NOMA), and Sparse Code Multiple Access (SCMA) as advanced access techniques.

The radar may operate in various frequency bands including, but not limited to, 6-8GHz, 28GHz, 39GHz, 60GHz and 77 GHz. The radar operates to locate targets in the radar field of view in azimuth (distance) and/or elevation (angle) and/or velocity. For single station radar, the transmitter and receiver are mounted close together, which results in a leakage signal being transmitted directly from the transmitter to the receiver. The leakage signal interferes with radar detection and ranging. Strong leakage signals may interfere with the signal returned from the target, which may mask the target, hinder detection and/or render the range estimation inaccurate.

Disclosure of Invention

Technical problem

The leakage signal interferes with radar detection and ranging. Strong leakage signals may interfere with the signal returned from the target, which may mask the target, hinder detection and/or render the range estimation inaccurate.

Technical scheme

Embodiments of the present disclosure include a method, electronic device, and non-transitory computer-readable medium for leakage cancellation. In one embodiment, the electronic device includes a radar transceiver, a memory, and a processor. The processor is configured to determine whether an object is in a vicinity of and within a field of view of the radar transceiver, obtain a leakage measurement of the radar transceiver in response to determining that no object is proximate to and within the field of view of the radar transceiver, and update a leakage response for leakage cancellation based on the leakage measurement.

In another embodiment, a method of eliminating leakage includes: determining, by an electronic device having a radar transceiver, whether an object is in a vicinity of the radar transceiver and within a field of view of the radar transceiver; in response to determining that no object is proximate to the radar transceiver and within a field of view of the radar transceiver, obtaining a leakage measurement of the radar transceiver; and updating a leak response for leak cancellation based on the leak measurement.

In another embodiment, an electronic device includes a non-transitory computer-readable medium. The non-transitory computer-readable medium stores instructions that, when executed by the processor, cause the processor to: determining, by an electronic device having a radar transceiver, whether an object is in a vicinity of the radar transceiver and within a field of view of the radar transceiver; in response to determining that no object is proximate to the radar transceiver and within a field of view of the radar transceiver, obtaining a leakage measurement of the radar transceiver; and updating a leak response for leak cancellation based on the leak measurement.

Other technical features may be readily apparent to one skilled in the art from the figures, descriptions, and claims.

Before proceeding with the following detailed description, it may be advantageous to set forth definitions of certain words and phrases used throughout this disclosure. The term "couple" and its derivatives refer to any direct or indirect communication between two or more elements, whether or not those elements are in physical contact with one another. The terms "transmit," "receive," and "communicate," as well as derivatives thereof, encompass both direct and indirect communication. The terms "include" and "comprise," as well as derivatives thereof, mean inclusion without limitation. The term "or" is inclusive, meaning "and/or". The phrase "associated with … …" and derivatives thereof means including, included within … …, interconnected with … …, contained within … …, connected to or with … …, coupled to or with … …, communicable with … …, cooperative with … …, interleaved, juxtaposed, proximate, bound or with … …, having the nature of … …, having a relationship with … …, having a relationship with … …, and the like. When used with respect to a column of items, the phrase "at least one of … … means that different combinations of one or more of the listed items can be used and only one item in the column may be required. For example, "at least one of A, B and C" includes any one of the following combinations: A. b, C, A and B, A and C, B and C and a and B and C. Likewise, the term "group" means one or more. Thus, a group of items may be a single item or a collection of two or more items.

Further, various functions described below may be implemented or supported by one or more computer programs, each of which is formed from computer-readable program code and embodied in a computer-readable medium. The terms "application" and "program" refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in suitable computer readable program code. The phrase "computer readable program code" includes any type of computer code, including source code, object code, and executable code. The phrase "computer readable medium" includes any type of medium capable of being accessed by a computer, such as Read Only Memory (ROM), Random Access Memory (RAM), a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), or any other type of memory. A "non-transitory" computer-readable medium does not include a wired, wireless, optical, or other communication link that transmits transitory electrical or other signals. Non-transitory computer readable media include media that can permanently store data and media that can store data and later rewrite data, such as rewritable optical disks or erasable memory devices.

Definitions for certain other words and phrases are provided throughout this disclosure. Those of ordinary skill in the art should understand that in many, if not most instances, such definitions apply to prior, as well as future uses of such defined words and phrases.

Advantageous effects

The present disclosure relates generally to addressing signal leakage in radar applications.

Drawings

For a more complete understanding of the present disclosure and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, wherein like reference numbers represent like parts:

FIG. 1 shows an electronic device according to various embodiments of the present disclosure;

FIG. 2 illustrates a single station radar according to various embodiments of the present disclosure;

fig. 3 shows an example of a Channel Impulse Response (CIR) in accordance with various embodiments of the present disclosure;

fig. 4 shows a timing diagram for radar transmission according to various embodiments of the present disclosure;

FIG. 5 illustrates a flow diagram for leakage cancellation according to various embodiments of the present disclosure;

FIG. 6 shows a flowchart of steps for updating leakage measurements in a timely manner, in accordance with various embodiments of the present disclosure;

FIG. 7 shows a flowchart of steps for determining the validity of a leak measurement, in accordance with various embodiments of the present disclosure;

FIG. 8 illustrates a flow chart for determining the validity of a leak measurement with reference to time as a state variable according to various embodiments of the present disclosure;

FIG. 9 illustrates a flow chart for determining the effectiveness of a leak measurement with reference to temperature and humidity as state variables according to various embodiments of the present disclosure;

FIG. 10 illustrates a flow diagram for updating decisions for leakage measurements for radar-based applications, in accordance with various embodiments of the present disclosure;

FIG. 11 illustrates a flow diagram for updating decisions for leak measurements for radar-based presence detection, in accordance with various embodiments of the present disclosure;

FIG. 12 illustrates a flow diagram for radar-based range estimation using updated leakage responses in accordance with various embodiments of the present disclosure;

FIG. 13 illustrates a flow diagram for leak measurement update decisions for radar-based face authentication, in accordance with various embodiments of the present disclosure;

fig. 14 illustrates user interaction with an electronic device for radar-based facial authentication, in accordance with various embodiments of the present disclosure.

Fig. 15 shows a flow diagram for leak measurement update decision for radar-based emotion or heartbeat monitoring, in accordance with various embodiments of the present disclosure;

FIG. 16 shows a flow diagram for leak measurement update decision for applications using non-radar sensors and radar transceivers, in accordance with various embodiments of the present disclosure;

fig. 17 illustrates a general flow diagram for leak measurement update decisions for non-radar applications, in accordance with various embodiments of the present disclosure;

FIG. 18 illustrates a flow diagram for updating a decision for leak measurement for non-radar applications using sensors, in accordance with various embodiments of the present disclosure;

FIG. 19 shows a flow diagram of a process for leak measurement update decision for vision-based face authentication in non-radar applications, in accordance with various embodiments of the present disclosure;

FIG. 20 shows a flow diagram of a process for updating a decision for leakage measurement of a proximity sensor in a non-radar application, in accordance with various embodiments of the present disclosure;

FIG. 21 illustrates a flow diagram for integrating confidence levels into leak measurement update decisions in accordance with various embodiments of the present disclosure;

FIG. 22 illustrates a flow diagram for integrating confidence level decisions into leakage measurement update decisions, in accordance with various embodiments of the present disclosure;

figure 23 shows a flow diagram of a process for updating decisions for leakage measurements for voice or video call applications, in accordance with various embodiments of the present disclosure;

fig. 24 shows a flow diagram of a process for updating a decision for a surrogate leakage measurement for a voice or video call application in accordance with various embodiments of the present disclosure; and

FIG. 25 shows a flow diagram of a process for timely updating a leak response, according to various embodiments of the present disclosure.

Detailed Description

The drawings included herein and the various embodiments used to describe the principles of the present disclosure are illustrative only and should not be construed in any way to limit the scope of the present disclosure. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged communication system, either wired or wireless.

Fig. 1 illustrates an electronic device according to various embodiments of the present disclosure. The embodiment of the electronic device 100 shown in FIG. 1 is for illustration only. Other embodiments may be used without departing from the scope of this disclosure.

As shown in fig. 1, electronic device 100 includes a Radio Frequency (RF) transceiver 110, Transmit (TX) processing circuitry 115, a microphone 120, Receive (RX) processing circuitry 125, a speaker 130, a processor 140, an input/output (I/O) Interface (IF)145, a memory 160, a display 165, an input 170, and sensors 175. Non-limiting examples of sensors 175 include inertial sensors, proximity sensors, infrared sensors, ultrasonic sensors, laser sensors, and capacitive sensors that can provide contextual operational data that can be used to update the leak response on-the-fly. Memory 160 includes an Operating System (OS)162 and one or more applications 164. The one or more applications 164 may be type 1 applications or type 2 applications that may be used to provide additional contextual operational data that may also be used to update the leak response in a timely manner.

The transceiver 110 sends signals to other components in the system and receives incoming signals sent by other components in the system. For example, the transceiver 110 transmits RF signals such as bluetooth or WI-FI signals to access points (such as base stations, WI-FI routers, bluetooth devices) of a network (such as WI-FI, bluetooth, cellular, 5G, LTE-A, WiMAX, or any other type of wireless network) and receives RF signals such as bluetooth or WI-FI signals from access points (such as base stations, WI-FI routers, bluetooth devices) of a network (such as WI-FI, bluetooth, cellular, 5G, LTE-A, WiMAX, or any other type of wireless network). The received signal is processed by RX processing circuitry 125. RX processing circuitry 125 may send the processed signals to speaker 130 (such as for voice data) or to processor 140 for further processing (such as for web browsing data). TX processing circuitry 115 receives voice data from microphone 120 or other outgoing data from processor 140. Outgoing data may include web data, email, or interactive video game data. TX processing circuitry 115 processes the outgoing data to generate processed signals. Transceiver 110 receives outgoing processed signals from TX processing circuitry 115 and converts the received signals to RF signals that are transmitted via an antenna. In other embodiments, transceiver 110 may send and receive radar signals to detect objects potentially present in the surrounding environment of electronic device 100.

In this embodiment, one of the one or more of the transceivers 110 includes being a radar transceiver 150 configured to transmit and receive signals for detection and ranging purposes. For example, radar transceiver 150 may be any type of transceiver, including but not limited to a WiFi transceiver, such as an 802.11ay transceiver. The radar transceiver 150 includes an antenna array 155 including an antenna array of transmitters 157 and receivers 159. In some embodiments, the signals transmitted by the radar transceiver 150 may include, but are not limited to, millimeter wave (mmWave) signals. After a signal bounces or reflects from a target object in the surrounding environment of the electronic device 100, the radar transceiver 150 may receive the signal originally transmitted from the radar transceiver 150. The processor 140 may analyze a time difference between the transmission of the signal by the radar transceiver 150 and the reception of the signal by the radar transceiver 150 to measure the distance of the target object from the electronic device 100.

The transmitter 157 and the receiver 159 may be closely fixed to each other such that a spaced distance therebetween is small. For example, the transmitter 157 and receiver 159 may be located within a few centimeters of each other. In some embodiments, the transmitter 157 and receiver 159 may be co-located with an indistinguishable separation distance. Based on contextual information available from other applications executing on the electronic device 100, the processor 140 executes instructions to cause the electronic device to update the leakage measurements for the transmitter 157 and the receiver 159 at a timely basis that can be used to eliminate leakage signals transmitted from the transmitter 157 to the receiver 159. The leakage measurement may be represented by a CIR as described in more detail in fig. 3.

TX processing circuitry 115 receives analog or digital voice data from microphone 120 or other outgoing baseband data (such as web data, email, or interactive video game data) from processor 140. TX processing circuitry 115 encodes, multiplexes, and/or digitizes the outgoing baseband data to generate a processed baseband or IF signal. Transceiver 110 receives the outgoing processed baseband or IF signal from TX processing circuitry 115 and upconverts the baseband or IF signal to an RF signal, which is transmitted via antenna 105.

The processor 140 is also capable of executing an operating system 162 in the memory 160 to control the overall operation of the electronic device 100. For example, processor 140 may move data into or out of memory 160 as needed to execute a process. In some embodiments, the processor 140 is configured to execute the application 164 based on the OS program 162 or in response to a signal received from an external device or operator. In some embodiments, the memory 160 is also configured to store data, such as leak responses for leak elimination, which the processor 140 may utilize to cause various components of the electronic device to perform leak elimination, either individually or in cooperation. In some embodiments, processor 140 may control the reception of forward channel signals and the transmission of reverse channel signals by transceiver 110, RX processing circuitry 125, and TX processing circuitry 115 in accordance with well-known principles. In some embodiments, processor 140 includes at least one microprocessor or microcontroller.

Processor 140 is also coupled to I/O interface 145, display 165, input 170, and sensor 175. The I/O interface 145 provides the electronic device 100 with the ability to connect to other devices, such as laptop computers and handheld computers. I/O interface 145 is the communication path between these accessories and processor 140. The display 165 may be a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, an organic LED (oled), an active matrix oled (amoled), or other display capable of presenting text and/or graphics, such as from a web site, video, games, images, or the like.

The processor 140 may be coupled to an input 170. An operator of electronic device 100 may use input 150 to enter data or input into electronic device 100. The input 150 may be a keyboard, touch screen, mouse, trackball, voice input, or any other device capable of acting as a user interface that allows a user to interact with the electronic device 100. For example, the input 150 may include a voice recognition process, thereby allowing a user to input voice commands via the microphone 120. For another example, input 150 may include a touch panel, a (digital) pen sensor, a key, or an ultrasonic input device. The touch panel may recognize a touch input of at least one scheme, for example, a capacitive scheme, a pressure-sensitive scheme, an infrared scheme, or an ultrasonic scheme.

The electronic device 100 may also include one or more sensors 175 that meter physical quantities or detect activation states of the electronic device 100 and convert the metered or detected information into electrical signals. For example, the sensors 175 may include one or more buttons for touch input, one or more cameras, gesture sensors, eye tracking sensors, gyroscopes or gyroscopic sensors, barometric pressure sensors, magnetic sensors or magnetometers, acceleration sensors or accelerometers, grip sensors, proximity sensors, color sensors, biophysical sensors, temperature/humidity sensors, illuminance sensors, Ultraviolet (UV) sensors, Electromyography (EMG) sensors, electroencephalogram (EEG) sensors, Electrocardiogram (ECG) sensors, Infrared (IR) sensors, ultrasound sensors, fingerprint sensors, and the like. The sensor 175 may also include control circuitry for controlling at least one of the sensors included therein.

In various embodiments, the electronic device 100 may be a telephone or a tablet computer. In other embodiments, the electronic device 100 may be a robot or any other electronic device that uses a radar transceiver. Fig. 1 does not limit the present disclosure to any particular type of electronic device.

Fig. 2 illustrates a single station radar according to various embodiments of the present disclosure. The embodiment of the single station radar 200 shown in fig. 2 is for illustration only, and other embodiments may be used without departing from the scope of the present disclosure. The single station radar 200 shown in fig. 2 includes a processor 210, a transmitter 220, and a receiver 230. In some embodiments, processor 210 may be processor 140.

In some embodiments, the transmitter 220 and receiver 230 may be a radar transceiver 150 and are connected to a transmitter 157 and receiver 159 antenna array, respectively, included in the antenna array 155. In various embodiments, the transmitter 220 and receiver 230 are co-located using a common antenna, or nearly co-located while using separate but adjacent antennas. It is assumed that the single station radar 200 is coherent such that the transmitter 220 and the receiver 230 are synchronized via a common time reference.

Processor 210 controls transmitter 220 to transmit a radar signal or radar pulse. The radar pulses are generated to achieve a desired "radar waveform" that is modulated onto a radio carrier frequency and transmitted either omnidirectionally or focused into a particular direction by a power amplifier and antenna (shown as a parabolic antenna), such as transmitter 220. After transmitting the radar pulse, a target 240 at a distance R from the radar 200 and within the field of view of the transmitted pulse will be at the RF power density p for the duration of the transmission_t(in W/m)²In units) is illuminated. For the first order, p_tDescribed by equation 1:

wherein, P_TIs the transmission power [ W]，G_TIs the transmit antenna gain [ dBi]，A_TIs the effective aperture area m2]And λ is the wavelength [ m ] of the radar signal RF carrier signal]And R is the target distance [ m]。

The transmitted power density impinging on the target surface causes reflections depending on the material composition, surface shape and dielectric behavior at the frequency of the radar signal. Off-direction scatter signals are generally not sufficiently recovered at the receiver 230, and therefore only direct reflections contribute to a detectable received signal. Thus, one or more illuminated areas of the target with a normal vector directed back to the receiver 230 act as a transmit antenna aperture with directivity or gain according to their effective aperture area. Reflected power P_reflDescribed by equation 2:

wherein, P_reflIs the effective (isotropic) target reflected power [ W]，A_tIs the effective target area [ m ] perpendicular to the radar direction²]，r_tIs the reflectivity and shape of the material [ 0.. 1. ], 1]，G_tIs the corresponding aperture gain [ dBi]And RCS is radarSection [ m ]²]。

As shown in equation 2, the Radar Cross Section (RCS) is an equivalent area scaled in proportion to the square of the actual reflection area, inversely proportional to the square of the wavelength, and decreased according to various shape factors and the reflectivity of the material itself. For example, for and²relatively large flat total mirror area A_t，Due to material and shape dependencies, it is difficult to infer the actual physical area of the target 240 based on the reflected power, even if the distance R from the target to the radar 200 is known.

The target reflected power at the location of the receiver 230 is based on the reflected power density at the reverse distance R collected over the receiver antenna aperture area. Received target reflected power P_RDescribed by equation 3:

wherein, P_RIs the received target reflected power [ W ]]And A is_RIs the effective aperture area m2 of the receiver antenna]. In some embodiments, A_RCan be reacted with A_TThe same is true.

Such radar systems are available as long as the receiver signal exhibits a sufficient signal-to-noise ratio (SNR). The specific value of SNR depends on the waveform and detection method used. The SNR is described by equation 4:

where kT is the boltzmann constant x temperature [ W/Hz ], B is the radar signal bandwidth [ Hz ], and F is the receiver noise factor, referring to the degradation of the received signal SNR due to the noise contribution to the receiver circuit itself.

In some embodiments, the radar signal may be of the type having a signal defined by T_PDuration or width of the representationShort pulses of (a). In these embodiments, the delay t between transmission and reception of the corresponding echo will be equal to τ 2R/c, where c is the speed of light propagation in the medium (such as air). In some embodiments, there may be multiple targets 240 at slightly different distances R. In these embodiments, the individual echoes of each individual target 240 are so distinguished only when the delays differ by at least one pulse width, and the range resolution of the radar is described as Δ R ═ c Δ τ/2 ═ c t_P)/2. Duration T_PExhibits a power spectral densityWherein the first zero point is 1/T at its bandwidth B_PTo (3). Thus, the relationship of the range resolution of the radar to the bandwidth of the radar waveform is described by equation 5:

ΔR＝c/2B

based on the reflected signal received by the receiver 230, the processor 210 generates a metric that measures the response of the reflected signal as a function of the distance of the target 240 from the radar. In some embodiments, the metric may be a CIR.

Fig. 3 shows an example depicting a measured CIR of a leakage response in accordance with various embodiments of the present disclosure. The CIR is a response metric based on the signal received by the receiver 230. For example, the CIR is a measure of the amplitude and/or phase of the reflected signal as a function of distance. As shown in fig. 3, the CIR is depicted as a delay tap index with the measured distance represented on the x-axis, and the amplitude of the radar measurement [ dB ] represented on the y-axis. In a single station radar (e.g., radar 200) having separate transmit and receive antenna modules, a strong signal may radiate directly from transmitter 220 to receiver 230, causing a strong response at a delay corresponding to the separation between transmitter 220 and receiver 230. The strong signal radiated from the transmitter 220 to the receiver 230 is referred to as a leakage signal. Even though it may be assumed that the direct leakage signal from transmitter 220 corresponds to a single delay, the effect of the direct leakage signal may still affect multiple delay taps adjacent to the direct leakage signal.

In the measured leakage response shown in fig. 3, the main leakage peak is represented at tap 11. In addition, taps 10 and 12 also have a strong response, which is noted to be greater than 20dB above the noise floor. Due to additional responses such as those shown at taps 10 and 12, it is difficult to reliably detect and estimate the target distances within those first few taps from the leaky taps.

Fig. 4 shows a timing diagram for radar transmission, in accordance with various embodiments of the present disclosure. In particular, fig. 4 shows a frame structure that divides time into frames, each frame comprising a plurality of bursts. Each burst comprises a plurality of pulses. The timing diagram shown in fig. 4 assumes the underlying pulse compression radar system.

As shown in fig. 4, each frame comprises N bursts, as shown by burst 1, burst 2, burst 3 through burst N. Each burst is formed of a plurality of pulses. For example, fig. 4 shows that pulse train 1 includes a plurality of pulses labeled pulse 1, pulse 2, and so on through pulse M.

For example, in burst 1, a radar transceiver, such as transmitter 157, may transmit pulse 1, pulse 2, and pulse M. In burst 2, transmitter 157 may transmit similar pulses pulse 1, pulse 2, and pulse M. Each different pulse (pulse 1, pulse 2, and pulse M) and burst (burst 1, burst 2, burst 3, etc.) may identify a particular pulse and burst with a different transmit/receive antenna configuration, i.e., an active set of antenna elements and corresponding analog/digital beamforming weights. For example, each pulse or burst may identify a particular pulse or burst with a different active set of antenna elements and corresponding analog/digital beamforming weights.

After each frame, a processor connected to transmitter 157 (e.g., processor 140) obtains radar measurements at the end of each frame. For example, the radar measurements may be depicted as a three-dimensional complex CIR matrix. The first dimension may correspond to a burst index, the second dimension may correspond to a burst index, and the third dimension may correspond to a delay tap index. The delay tap index may be converted to a measure of the distance or time of flight of the received signal.

Leakage signals from the radar transmitter to the radar receiver may hinder the target detection and range estimation capabilities of the radar, particularly for objects within the vicinity of the radar transceiver and within the field of view of the radar transceiver. In some exemplary embodiments, the object is within a vicinity of and within a field of view of the radar transceiver when the object is less than about 20cm from the radar transceiver. In a more specific embodiment, the object is within a vicinity of the radar transceiver and within a field of view of the radar transceiver when the object is less than about 10cm from the radar transceiver.

The elimination of the leakage signal can overcome this problem. The pre-measured leak signal stored on the electronic device (such as in memory 160 of electronic device 100) may be used to eliminate the leak signal from the radar measurement. This approach is feasible because the leakage signal propagates through a well-defined path determined by the device hardware, which may be assumed to be constant over a relatively long duration under similar environmental conditions. Occasional updates of stored leakage measurements may ensure accuracy of radar-based sensing. To discontinuously use resources to update leakage measurements when inconvenient or unnecessary, novel aspects of various embodiments disclosed herein relate to updating stored leakage measurements when necessary and/or when possible in due course. For example, a recently obtained stored leak measurement may not need to be updated and thus may be considered valid. If the stored leak measurement is no longer valid, the stored leak measurement may be updated only when possible. For example, if an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver, the stored leakage measurements may not be updated.

Various embodiments of the present disclosure are directed to using context information from various applications executing on an electronic device to determine whether a stored leakage measurement is still valid and, if not, when the stored leakage measurement may be updated. Whether or not the applications being executed directly utilize radar measurements, successful operation of these applications typically depends on the absence of objects in the vicinity of the radar transceiver and within the field of view of the radar transceiver. An exemplary application, which will be explained in more detail in the following figures, relates to radar-based face authentication. In this case, for successful operation, there must be no obstacle between the radar antenna module and the user's face, which are typically separated by a distance of between 20cm and 50 cm. The latest leak measurement may be extracted from the radar measurements that have produced the desired result (e.g., successful authentication). The extracted leakage measurement may be used to update a leakage response of a radar transceiver in the electronic device by cancelling a leakage signal of the radar measurement. The updated leak response may then be used for reliable detection and accurate ranging of the target, particularly in the vicinity of and within the field of view of the radar transceiver.

Fig. 5 illustrates a flow diagram of general operations for leakage cancellation, according to various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo operations described in flowchart 500 for canceling the effects of a leakage signal transmitted directly from a transmitter to a receiver. For example, the radar measurements made in operation 502 include a leakage signal that may be cancelled in operation 506 by the stored leakage measurements obtained from operation 504. The stored leakage measurements are data describing the signal strength of the set of leakage signals relative to the delay tap index, which may be attributed to the leakage signals transmitted directly from the transmitter to the receiver of the radar transceiver. The stored leakage measurements may be represented in the CIR as shown in fig. 3. The radar measurements after leakage cancellation may be used in operation 508 to achieve target detection and range estimation.

The stored leakage measurements of fig. 5 may be associated with one or more state variables, such as a timestamp describing the conditions under which the stored leakage measurements were obtained, temperature, or humidity. Each of the state variables may be further divided into one or more categories or ranges. For example, the leak measurements may be stored for each temperature category (such as high, medium, low, or the temperature may be divided into multiple intervals of N degrees each). Leak measurement updates may then be made separately for each temperature class. Further, when stored measurements are used to remove leakage for radar detection and estimation, the temperature at which the radar measurements are taken may be used to select an appropriate stored leakage measurement for leakage removal. Other types of information may also be used in a similar manner. For example, humidity is another factor that may affect the behavior of the circuitry of the device and thus may also affect the leakage behavior, and it may be used as part of the description of the operating environment.

FIG. 6 illustrates a flowchart of operations for timely updating a leak measurement, according to a non-limiting embodiment of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo the operations described in flowchart 600 to determine the validity of the stored leakage measurements and update the stored leakage signals as necessary and possible.

A state of an electronic device is identified in operation 602. The state of the device is based on one or more state variables, examples of which may include time, temperature, and humidity. Based on the state of the device, the validity of the stored leak measurement may be determined in operation 604. 7-9 and related embodiments illustrate some non-limiting examples for determining the validity of stored leakage measurements based on state variables.

If the stored leakage measure is still valid, the stored leakage measure is not updated in operation 606. Otherwise, if the stored leakage measurement is no longer valid, as determined in operation 604, a determination is made in operation 608 as to whether the stored leakage measurement can be updated. If the stored leakage measure cannot be updated, flow diagram 600 proceeds to operation 610, or if the stored leakage measure can be updated, flow diagram 600 proceeds to operation 612.

There are different methods for updating the stored leakage measurements in operation 612. For example, a simple approach is to replace a stored leak measurement with a newly obtained leak measurement. Another approach involves averaging, a simple average or a weighted average of all past valid leakage measurements. In one embodiment, the weighted average may include all of the historical leakage measurements, and in another embodiment, the weighted average spans only a particular time window to include only a subset of the historical leakage measurements. Another weighted averaging method may use the timestamp of the leak measurement to determine the age of the measurement and perform an averaging weighted by the freshness of the measurement (e.g., giving more weight to more recent leak measurements). Note that if the leakage measurements are stored for different types of classes of operating environment of the radar (e.g. defined by state variables such as temperature and/or humidity), the averaging method described so far may be used for measurements belonging to each operating environment class separately.

FIG. 7 shows a flowchart of steps for determining validity of stored leak measurements, in accordance with various embodiments of the present disclosure. The classifier may be based on the stored state variables of the stored leakage measurements from operation 702 in operation 706 (S)_lk) And the current state variable (S) of the electronic device from operation 704_cu) To determine if a leak update is needed (i.e., to make a validity determination). The stored state variables may be maintained in memory 160 and compared to corresponding state variables determined by one or more sensors 175 and/or applications 164. Based on the results of the determination made in operation 706, flowchart 700 proceeds to operation 708 if the stored leakage measure is not valid, or flowchart 700 proceeds to operation 710 if the stored leakage measure is still valid.

FIG. 8 illustrates a flow chart for determining the validity of a leak measurement with reference to time as a state variable according to various embodiments of the present disclosure. The processor may use the stored timestamp (t) of the stored leakage measurement from operation 802 in operation 806_lk) And the current timestamp (t) from operation 804_cu) A validity determination is made. The stored state variables may be maintained in memory 160 and compared to corresponding state variables determined by one or more applications 164 capable of providing the current timestamp. For example, in operation 806, the processor may determine whether a difference between the stored timestamp and the current timestamp exceeds a predefined threshold. If the difference exceeds a predefined threshold, the stored leakage measure is in operation808, or 810, as valid.

FIG. 9 illustrates a flow chart for determining the effectiveness of a leak measurement with reference to temperature and humidity as state variables according to various embodiments of the present disclosure. The processor may measure a temperature (T) based on the stored leakage from operation 902 in operation 910_lk) With the current temperature (T) of the electronic device from operation 908_cu) And/or the stored humidity (H) of the leak measurement from operation 904_lk) With the current humidity (H) of the electronic device from operation 906_cu) The comparison of (a) makes a validity determination. The stored state variables may be maintained in memory 160 and compared to corresponding state variables determined by one or more sensors 175 capable of providing the current temperature and/or humidity.

In the non-limiting embodiment shown in FIG. 9, if the current temperature (T)_cu) And a stored temperature (T) associated with the stored leak measurement_lk) The difference between exceeds a temperature threshold, and/or if the current humidity (H) is present _cu ) And a stored humidity (H) associated with the stored leak measurement _lk ) The difference therebetween exceeds the humidity threshold, a validity determination may be made in operation 910. If the temperature threshold is exceeded, the humidity threshold is exceeded, or both the temperature threshold and the humidity threshold are exceeded, then flowchart 900 proceeds to operation 912. If neither the temperature threshold nor the humidity threshold is exceeded, the flow diagram 900 proceeds to operation 914.

For ease of discussion, timely updating of leak measurements may be separated into two different types of applications. A first type of application (which may be referred to herein as a type 1 application) is an application that uses radar measurements. These radar-based applications do not necessarily require target detection as in typical radar use cases. Some examples include facial authentication and gesture recognition, which do not require explicit radar detection (although explicit radar detection may still be used). The second type of application (which may be referred to herein as a type 2 application) does not use radar measurements. Type 2 applications may use other non-radar sensors (e.g., cameras) or no sensors at all. Operational context data from non-radar sensors or the application itself may be used to infer whether an update of the leak measurement is possible (i.e., the radar field of view has no objects so that a new leak measurement may be obtained). In both type 1 and type 2 applications, leak measurement update decisions are made based on inferences used to determine whether an object is within a vicinity of and within a field of view of an associated radar transceiver (which would prevent accurate leak measurements from being captured).

Fig. 10 illustrates a flow diagram for updating decisions for leakage measurements for radar-based applications, in accordance with various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo the operations described in flowchart 1000 to arrive at a leak measurement update decision. In general, type 1 applications obtain and process radar measurements to generate some operational context data that describes the operational state of the application, which is application specific. The operational context data may then be used to determine whether the leakage measurements may be updated as described in fig. 10 and subsequent figures.

In flow diagram 1000, radar measurements are obtained for a type 1 application in operation 1002. The radar measurements may be obtained from the radar transceiver 150 in fig. 1. The radar measurements include leakage signals transmitted directly from the radar transmitter 157 to the radar receiver 159, and signals returned to the receiver 159 from targets within the field of view of the radar transceiver 150.

Based on those radar measurements obtained in operation 1002, a determination is made in operation 1004 as to whether the leakage measurements can be updated. If the leakage measurement can be updated, a measurement corresponding to the leakage signal is extracted from the radar measurements in operation 1006. In a particular embodiment, the extraction is accomplished by selecting a signal response corresponding to a small delay tap (e.g., in a range between 0-20cm, or in a range between about 0-15 cm). In the alternative, these small delay taps may be referred to as "leakage taps". Since the leakage is a direct transmission between the transmitter and the receiver, the path length is short, and therefore its main effect is at short distances. For this reason, radar measurements at close range or equivalently small delay indices are of particular interest in order to eliminate major leakage.

In operation 1008, the stored leakage measure may be updated with the extracted measure corresponding to the leakage signal. If it is determined at operation 1004 that the leak measurement cannot be updated, the leak signal is not updated at operation 1010.

Fig. 11 illustrates a flow diagram for updating decisions for leak measurements for radar-based presence detection, in accordance with various embodiments of the present disclosure. Leak measurement update decisions may be made based at least in part on information from a type 1 application that employs an algorithm for processing raw radar measurements to detect the presence of objects in its vicinity. The raw radar measurements include contributions from the leakage signal. The application may also have a distance estimation function that may be inaccurate due to the effects of leakage signals, particularly in close range distances such as distances less than about 20cm or distances less than about 10 cm. Presence detection is achieved by observing the behavior of the CIR near the leaky tap. The leakage contribution from the static source has a certain behavior. By detecting deviations of the measured radar signal, the presence of an object can be detected. Various methods may be used as the detection algorithm. Some examples include classical signal processing algorithms and machine learning methods. Some example signal processing methods may be methods that detect a change in the shape of the leaked CIR. This method may calculate some conceptual distances to some stored templates of pure leaky CIRs and detect an object if the resulting distances deviate from a certain threshold; otherwise, no target is detected. Some example machine learning methods may be any classifier, such as k-nearest neighbor or support vector machine based or even neural network based classifiers. The classifier may be trained to identify behavior of the pure-leakage CIR such that it can distinguish between the pure-leakage CIR and the non-pure-leakage CIR (i.e., when one or more targets are present).

A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo a series of operations described in flowchart 1100. In operation 1102, radar measurements for presence detection are obtained. The measurements may be obtained from the radar transceiver 150 of fig. 1. A determination is made in operation 1104 as to whether the presence of the target is detected. If the presence of the target is not detected, then no object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver. A measurement corresponding to a leakage signal between the transmitter and the receiver is extracted in operation 1106 and used to update the stored leakage measurement in operation 1108.

If a target is detected in operation 1104, there is a possibility that the object may be within the vicinity of the radar transceiver and within the field of view of the radar transceiver. Accordingly, the flow diagram 1100 proceeds to operation 1110 and the stored leak is not updated.

Fig. 12 illustrates a flow diagram for radar-based range estimation using updated leakage responses, in accordance with various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo a series of operations for distance estimation described in flowchart 1200. In operation 1202, radar measurements for presence detection are obtained. A determination is made in operation 1204 as to whether a target is detected. If no targets are detected, the stored leak measurements are updated in operation 1206, if necessary. In a non-limiting embodiment, the stored leakage measurements are updated by extracting a leakage signal from the radar measurements obtained in operation 1202. Returning to operation 1204, if a target is detected, the distance to the target is estimated in operation 1208 using the updated leak response obtained previously.

Fig. 13 illustrates a flow diagram for leak measurement update decisions for radar-based face authentication, in accordance with various embodiments of the present disclosure. Flow diagram 1300 describes using operational context data from a radar-based face authentication application for a divulging update decision. The radar measurements for face authentication are input into a face authentication algorithm, and the output of the face authentication application contains the desired operational context data. For example, if the face authentication application successfully performs radar measurements, whether or not the user is authenticated, it may be assumed that the face was correctly captured in the radar measurements without any obstructing objects located in the environment between the radar transceiver and the user's face. An illustration depicting a typical use case of an electronic device for face authentication is depicted in fig. 14. The radar measurements of the user's face contain leakage signals in the small delay taps that can be used to update the leakage measurements.

Using the radar measurements for face authentication obtained in operation 1302, a determination is made in operation 1304 as to whether face authentication completed successfully. In one embodiment, the successful completion of the face authentication is the authentication of a user executing a radar-based face authentication application on the electronic device. In another embodiment, successful completion of facial authentication may be based on a rejection of the user's authentication attempt based on an unobstructed radar measurement.

If the face authentication is successfully completed, a measurement corresponding to the leakage signal is extracted from the radar measurements in operation 1306. In operation 1308, the stored leakage measure is updated with the extracted measure. If the face authentication is not successfully completed in operation 1304, the leak measurement is not updated in operation 1310.

Fig. 14 illustrates user interaction with an electronic device for radar-based facial authentication, in accordance with various embodiments of the present disclosure. An electronic device 1400, which is an electronic device such as device 100 in fig. 1, executes a radar-based authentication application (not shown) for authenticating a user 1402. The electronic device 1400 maintains a facial distance D from the user 1402. Typically, the distance is between 20cm-50cm, which ensures that there are no objects in the vicinity of the electronic device 1400 and within the field of view of the electronic device 1400 (i.e., between 0-20cm from the electronic device).

Fig. 15 shows a flow diagram for leak measurement update decision for radar-based emotion or heartbeat monitoring, according to various embodiments of the present disclosure. Flow diagram 1500 depicts the use of operational context data from a radar-based emotion or heartbeat monitoring application for leak update decisions. Type 1 applications may use radar measurements to monitor the mood or heartbeat of a user, an example of which is mobile applications for monitoring driver drowsiness or incapacitations. Radar can be used to infer the physical state of the driver based on physiological patterns such as heartbeat, respiration, etc. In this embodiment, the mobile device executing the type 1 application may be placed on the dashboard toward the driver. In a typical use case, there will be no obstacle object between the radar transceiver and the driver.

Flowchart 1500 begins with radar measurements for mood or heartbeat monitoring obtained in operation 1502. Using those radar measurements, operation 1504 determines whether the leakage measurements can be updated based on signal strength and/or doppler effect. With regard to the pure possibility of leakage measurements, additional precautions may be incorporated to ensure a better quality of the captured measurements. For example, signal strength and doppler information may be used to provide additional operational context data that may be used to determine whether the vehicle is moving. Movement in the vehicle will appear as vibration in the electronic device, which is a micromovement relative to other objects in the vehicle. By confirming that there is not a large amount of energy in the leaky tap signal in the non-zero doppler channel, it can be inferred that there are no obstructing objects in the vicinity of the radar transceiver, and the leakage can be updated. In other words, objects in the vicinity of the radar transceiver and within the field of view of the radar transceiver will have a reflected energy level in the leakage tap that exceeds the background level. Conversely, the absence of objects in the vicinity of the radar transceiver and within the field of view will have reflected energy in the leakage tap proportional to the background level. The amount of energy in the non-zero doppler channel at the small delay tap is taken as the inverse of the confidence level. That is, the stronger the energy, the less likely the leak can be refreshed. Confidence levels are discussed in more detail in fig. 21 and 22 below.

If the leakage measure can be updated, a measure corresponding to the leakage signal is extracted from the radar measurements used in the mood or heartbeat application in operation 1506. However, if the leakage measurement cannot be updated based on the result of operation 1504, the leakage measurement is not updated in operation 1510.

Fig. 16 shows a flow diagram for leak measurement update decision for applications using non-radar sensors and radar transceivers, in accordance with various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo the operations described in flowchart 1600 for making update decisions using non-radar sensors and radar-based sensors. In certain embodiments, the non-radar sensor is an inertial sensor that may be used to determine movement of the electronic device, and subsequent analysis of the radar measurements from the radar transceiver may be used to determine whether new leakage measurements may be obtained.

If the electronic device moves relative to its surroundings, the doppler information and signal strength can be used to detect whether there are any obstacles in its vicinity. Device motion can also be inferred from type 1 application usage as described in more detail in fig. 15 without the use of inertial sensors. Due to the motion of the device relative to its surroundings, if there is an obstructing object in the vicinity of the radar antenna module, the reflection from this object will have a non-zero doppler effect. Leakage as a direct signal from a radar transmitting antenna rigidly mounted on the device to a receiving antenna rigidly mounted on the device will be static with respect to each other. The leakage signal will fall into the zero doppler path. Thus, by confirming that there is not a large amount of energy in the leaky tap signal in the non-zero doppler channel, it can be inferred that there are no obstructing objects in the vicinity of the radar transceiver, and the leakage can be updated. Note that in this case, the amount of energy in the non-zero doppler channel at the small delay tap can be used as the inverse of the confidence level. That is, the stronger the energy, the less likely the leak can be updated, a fact that can be used during the calculation of the confidence level.

The flowchart 1600 begins with obtaining input from one or more sensors in operation 1602. Using the sensor input, operation 1604 determines whether the device is in motion. If the device is not in motion, the leak update measurement is not updated in operation 1606. However, if the device is in motion, then radar measurements are obtained in operation 1608, and the flow chart proceeds to operation 1610, where a determination is made as to whether signal strength and doppler effects can be used to infer whether the leakage measurements can be updated in operation 1610. If it can be inferred using signal strength and Doppler effects that the leakage measurement can be updated, the flow chart proceeds to operation 1612 where a measurement corresponding to the leakage signal is extracted from the radar measurements in operation 1612. The leak measurement is updated in operation 1614. However, if it is determined at operation 1610 that it can be inferred using the signal strength and doppler effect that the leakage measurement cannot be updated, the updated leakage measurement is not updated in operation 1616.

Fig. 17 illustrates a general flow diagram for leak measurement update decisions for non-radar applications, in accordance with various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo a series of steps described in flowchart 1700 for making leak measurement update decisions.

The operational context data obtained in operation 1702 may be used to make a leakage measurement update decision in operation 1704. In some embodiments, the type 2 application uses non-radar sensors (such as proximity sensors and inertial sensors) to obtain the operational context data, and in other embodiments, the operational context data is derived directly from the execution of the application. In either case, if the leakage measurement can be updated, then the radar leakage measurement is performed in operation 1706. In operation 1708, a radar leakage measurement is performed by activating a radar transceiver to perform a set of radar measurements that may be processed to obtain a leakage measurement to update a stored leakage measurement. If the leak measurement cannot be updated in operation 1704, the leak measurement is not updated in operation 1710.

Fig. 18 illustrates a flow diagram for updating a decision for leakage measurement for non-radar applications using sensors, in accordance with various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo a series of steps described in flowchart 1800 for making leak measurement update decisions. Sensor measurements for the type 2 application are obtained in operation 1802. The sensor measurements may be captured directly from one or more sensors or derived from data captured by one or more sensors.

In operation 1804, a determination is made as to whether the leak measurement can be updated based on the sensor measurement. If the leak measurement can be updated, then a radar leak measurement is performed in operation 1806. In operation 1808, a radar leak measurement is performed by activating the radar transceiver to perform a set of radar measurements that may be processed to obtain a leak measurement to update the stored leak measurement. If the leak measurement cannot be updated in operation 1804, the leak measurement is not updated in operation 1810.

Fig. 19 shows a flow diagram of a process for leak measurement update decision for vision-based face authentication in non-radar applications, according to various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo a series of steps described in flowchart 1900 to make a leak measurement update decision based on successful image capture. In particular, if the user's face is successfully captured, it may be inferred that no object exists between the electronic device and the user's face, regardless of whether the user is actually authenticated. This also means that the environment near the radar transceiver is clear for leakage measurements. In some embodiments, the results of the vision-based authentication application may be a factor considered in the confidence level determination. For example, successful authentication may be weighted higher than unsuccessful authentication because unsuccessful authentication may be due to additional factors, such as unexpected and undetected obstructions of the user's hand or finger.

To reduce or eliminate obstruction of the user's hand or fingers, additional sensor data may be captured and used to determine the position of the user's hand or fingers. For example, a capacitive touch sensor may be used to detect a grip, or an infrared-based proximity sensor near a radar transceiver may be used. As will be described in fig. 21 and 22, the sensor data may be incorporated into the calculation of the confidence level.

Returning to flowchart 1900, the process begins in step 1902 by capturing a camera image for a vision-based facial authentication application. In step 1904, it is determined whether the image capture was successful. If the image capture is successful, a radar leak measurement is performed in step 1906 and the stored leak measurement update is updated in step 1908. However, if at step 1904 it is determined that the image capture was not successful, then the process continues to step 1910 and the stored leak measurement update is not updated.

Although the exemplary embodiment described in fig. 19 relates to facial authentication, the steps of flowchart 1900 may be generally applied to other forms of biometric authentication, such as iris sensor authentication and fingerprint authentication, where the operational context data obtained in step 1902 may be used to infer that there is no object in the vicinity of the radar transceiver for purposes of leak measurement.

Fig. 20 shows a flow diagram of a process for updating a decision for leakage measurement of a proximity sensor in a non-radar application, in accordance with various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo a series of steps described in flowchart 2000. Additionally, the sensors 175 may include one or more proximity sensors capable of capturing sensor data that may be used to make update decisions. Examples of proximity sensors include infrared, ultrasound, laser or capacitance based sensors or any other type of proximity sensor based on touch or hand grip, including even advanced methods such as using image processing on camera images to identify objects and measure their distance.

Proximity sensor data is obtained in step 2002 and used to determine whether an object is in the vicinity of the radar transceiver in step 2004. If the object is not in the vicinity of the radar transceiver, then a radar leakage measurement may be performed in step 2006 as described in previous embodiments. The stored leak measurements may be updated in step 2008 using the results of the radar leak measurements before the process terminates. If it is determined in step 2004 that the object is within the vicinity of the radar transceiver, then the leak measurement is not updated in step 2010 and the process terminates.

Fig. 21 illustrates a flow diagram for incorporating confidence levels into leak measurement update decisions, in accordance with various embodiments of the present disclosure. The confidence level is a set of calculated values that can be used to weight the inputs to the leak measurement update procedure. The confidence level may be calculated by a processor in the electronic device (such as processor 140 of electronic device 100 in fig. 1) from data captured by one or more sensors 175 or data originating from one or more of applications 164 as previously described. Different methods may be used to perform leak measurement updates based on the confidence level. One example is to perform an average weighted by the confidence level. Another possibility is to perform the averaging using weights that are calculated using both the confidence level and the measured freshness (e.g. determined from the timestamp of the recording).

In operation 2102, radar measurements are obtained for the type 1 application. The confidence level may be calculated in operation 2104 based on the radar measurements and input into the leakage measurement update process of operation 2108, which also takes into account the radar measurements corresponding to the leakage signal extracted in operation 2106.

Although the flow diagram in fig. 21 is described with respect to a type 1 application, contextual operational data may be captured from a type 2 application for use in calculating a confidence level that may be used to make leak measurement update decisions. For example, a confidence level may be calculated for the vision-based face authentication application described in fig. 19, which takes into account not only that a successful image was captured for face authentication, but also whether the results of face authentication were successful. Successful authentication may be given a higher confidence level than unsuccessful authentication.

Fig. 22 illustrates a flow diagram for incorporating confidence level decisions into leakage measurement update decisions, in accordance with various embodiments of the present disclosure. The leakage measure update decision combines a soft decision and a hard decision based on the confidence level. The confidence level may be calculated by a processor in the electronic device (such as processor 140 of electronic device 100 in fig. 1) from data captured by one or more sensors 175 or data originating from one or more of applications 164 as previously described.

In operation 2202, radar measurements are obtained for a type 1 application. A confidence level is calculated in operation 2204 based on those radar measurements. In operation 2206, it is determined whether the confidence level exceeds a threshold. If the confidence level exceeds the threshold, then in operation 2208, a measurement corresponding to the leakage signal is extracted from the radar measurements. In operation 2210, the stored leakage measurements are updated. However, if it is determined at operation 2206 that the confidence level does not exceed the threshold, then at operation 2212, the stored leakage measure is not updated.

Although the flow diagram in fig. 22 is described with respect to a type 1 application, contextual operational data may be captured from a type 2 application for use in calculating a confidence level that may be used to make leak measurement update decisions. For example, the confidence level may be calculated for the vision-based face authentication application described in fig. 19. Further, the confidence level may be incorporated into the type 2 application discussed in fig. 23 and 24 that uses contextual operational data derived from a voice or video call application.

Fig. 23 shows a flow chart of a process for obtaining a leakage measurement update decision for a voice or video application, according to an example embodiment. The process may be implemented in a communication-enabled electronic device, such as a phone, tablet, or smart watch. In addition, it is assumed that a call accepted when the electronic device is not in hands-free mode will be carried by the user's hand towards the user's face or suspended in mid-air to enable the call to be made on a speakerphone. The condition of not using the hands-free mode reduces the likelihood that a call may be accepted while the electronic device remains in the pocket.

The process begins when a call is received for a voice or video application in step 2302. A determination is made in step 2304 as to whether the call was accepted without the hands-free mode. If the call is accepted without the hands-free mode, then a radar leak measurement is performed in step 2306. In step 2308, the stored radar leakage measurement is updated with a new radar leakage measurement, and the process ends. Returning to step 2304, if it is determined that the call is accepted without the hands-free mode, the stored leak measurement is not updated in step 2310, and the process ends.

In another embodiment, rejecting calls without activating the hands-free mode may also be used to trigger radar leak measurements, assuming that the user will hold the electronic device in a manner that will not introduce objects in the vicinity and field of view of the radar transceiver.

In a variation of these embodiments, a time delay may be imposed after the call is accepted before radar leak measurements are allowed to be performed to ensure that the device is in mid-air without any obstructions in the vicinity of the radar transceiver when the leak measurements are captured. In another variation, a time window may be applied for performing the radar leak measurement in step 2306 to ensure that no leak measurement is obtained when the electronic device is near or against the user's face.

In another variation of the embodiment depicted in fig. 23, other non-radar applications may be substituted for the voice/video application as long as they require the user to hold the electronic device in a particular position that can be used to infer that no object is in the vicinity and field of view of the radar transceiver. For example, some gaming applications may require a user to place a finger in a position that does not interfere with the radar antenna module.

Fig. 24 shows a flow chart of a process for updating a decision for replacement leakage measurements for a voice or video call application, according to another example embodiment. The process may be implemented in a communication-enabled electronic device, such as a phone, tablet, or smart watch, that activates a hands-free mode. The hands-free mode is active when the electronic device is connected to the user through a wired or wireless headset, which allows the user to indirectly accept or decline the call regardless of the location or location of the electronic device. For example, a user may accept a call with the phone in a pocket or with the phone facing down, with the radar antenna module blocked. Additional context data may be needed to determine whether a radar leak measurement should be performed. Examples of contextual data may include data from proximity sensors, light detection sensors, positioning sensors, which may be used to reduce the likelihood that radar leak measurements will be performed when one or more objects are in the vicinity and field of view of the radar transceiver.

The process described in flowchart 2400 begins when a call is received for a voice or video application in step 2402. In step 2404, a determination is made as to whether the call was accepted with hands-free mode active. If the call is accepted with hands-free mode active, then if the context data allows, then in step 2406 a radar leak measurement is performed. Thereafter, the stored leak measurement is updated in step 2408, and the process terminates. If it is determined in step 2404 that the call was not accepted with hands-free mode active, the process does not update the leak measurement in step 2410 and the process terminates.

Confidence levels may also be calculated for the embodiments described in fig. 23 and 24. For example, a position sensor, light sensor, or proximity sensor providing operational context data consistent with the presence of the electronic device in a pocket or face down may be used to calculate a confidence level that is not conducive to updating the stored leak measurement updates.

FIG. 25 is a flow diagram of a process for updating leak responses in a timely manner, according to various embodiments of the present disclosure. A processor, such as processor 140 of electronic device 100 in fig. 1, may execute instructions to cause the electronic device to undergo the steps described in flowchart 2500 to update the leak response as appropriate.

The process begins in step 2502 by making a determination as to whether a change in at least one state variable is detected. The change in state variable may be used to identify whether the stored leakage measure associated with the at least one state variable is still valid. Non-limiting examples of state variables may include time, temperature, humidity, or any other device-related state that may affect radar transmission in an electronic device. In some embodiments, the change in the at least one state variable is determined by identifying any change in the state variable. In other embodiments, the change in the state variable may be a change that exceeds a certain threshold. For example, the change in the state variable may be the passage of a discrete amount of time, or a change in temperature over a certain number of degrees or a certain percentage.

If no change is detected in step 2502, then the stored leak response need not be updated, and the process returns to the beginning. If a change in at least one state variable has been detected, then in step 2504, a determination is made as to whether an object is in the vicinity of the radar transceiver and within the field of view. If there is an object in the vicinity and field of view of the radar transceiver, the radar signal in the leaky tap cannot be accurately attributed to the leaky signal or the object in the vicinity of the field of view of the radar transceiver. Thus, the process returns to the beginning.

If no object is in the vicinity of the radar transceiver and no object is in the field of view of the radar transceiver, a leak measurement is obtained in step 2506. The leak measurements may be obtained in any number of ways as described in the previous embodiments. For example, the leakage measurements may be obtained by extracting a set of signals from radar measurements captured during execution of the type 1 application, or by activating a radar transceiver after or during execution of the type 2 application to perform a set of radar measurements that may be processed to obtain the leakage measurements.

In step 2508, the leak response is updated based on the leak measurement. The update may be a simple substitution or may incorporate averaging as previously described. Additionally, the updates may incorporate confidence levels as previously described. After the leak response is updated, the process terminates.

As previously discussed in the previous embodiments, when the process of flowchart 2500 is applied to some type 1 applications, the step of determining whether an object is within the vicinity and within the field of view of the radar transceiver involves performing a successful radar-based measurement on a target that is outside the vicinity of the radar transceiver, and the step of obtaining a leakage measurement includes extracting a signal corresponding to a set of leakage taps from the successful radar-based measurement.

As previously discussed in the previous embodiment, when the process of flowchart 2500 is applied to some type 1 applications that have access to operational context data including doppler data, the step of determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver includes confirming that reflected energy from within the vicinity of the radar transceiver is proportional to the background level.

As previously discussed in the previous embodiments, when the process of flowchart 2500 is applied to some type 2 applications, the step of determining whether an object is within a vicinity of and within a field of view of the radar transceiver includes performing a successful non-radar sensor-based measurement of a target that is outside of the vicinity of the radar transceiver, and the step of obtaining a leakage measurement includes measuring a leakage signal between a transmitter and a receiver of the radar transceiver.

As previously discussed in the previous embodiment, when the process of flowchart 2500 is applied to some type 2 applications that access operational context data from one or more proximity sensors, the step of determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver includes determining with a non-radar proximity sensor that a target is not detected within the vicinity of the radar transceiver, and the step of obtaining a leak measurement includes measuring a leak signal between a transmitter and a receiver of the radar transceiver.

As previously discussed in the previous embodiments, when the process of flowchart 2500 is applied to some type 2 applications that do not access operational context data from sensors, the step of determining whether an object is within the vicinity of the radar transceiver and within the field of view of the radar transceiver includes receiving, by the electronic device, a user input relating to the absence of any object within the vicinity of the radar transceiver. Examples of user inputs are described in more detail in fig. 23 and 24, and may include accepting or rejecting a voice or video call when the electronic device is not operating in the hands-free mode. Another example of a user input may be movement of a phone in three-dimensional space, such as when the user brings the phone to the user's ear. Additionally, the step of obtaining a leakage measurement further comprises measuring a leakage signal between a transmitter and a receiver of the radar transceiver.

None of the description in this application should be read as implying that any particular element, step, or function is an essential element which must be included in the claim scope. Furthermore, no claim is intended to refer to 35 u.s.c. § 112(f), unless the exact word "means for" followed by a word line.