阅读说明：本技术 灯具及相应的方法 (Lamp and corresponding method ) 是由 S·H·可汗 F·皮尔曼 于 2020-02-10 设计创作，主要内容包括：一些实施例涉及一种运动检测器(100),其被配置为对运动信号进行信号处理以获得多个运动分量,运动分量与环境中的运动的方向和速度相关,在运动分量中消除对应于具有相反方向的运动的两个运动分量,并从未消除的运动分量中检测环境中的运动。(Some embodiments relate to a motion detector (100) configured to signal process a motion signal to obtain a plurality of motion components, the motion components being related to a direction and a speed of motion in an environment, to cancel two motion components corresponding to motion having opposite directions in the motion components, and to detect motion in the environment from the motion components that are not cancelled.)

1. A luminaire (170) comprising a motion detector (100), the motion detector (100) comprising:

a motion sensor interface (120) configured to receive a motion signal from a motion sensor, the motion signal relating to motion in a motion sensor environment,

-a processor system configured to:

-signal processing the motion signal to obtain a plurality of motion components, the motion components being related to the direction and speed of motion in the environment,

-eliminating in the motion component two motion components corresponding to motions having opposite directions,

-detecting motion in the environment from the motion components that are not eliminated,

-wherein the luminaire is connectable to a light emitting element (172) and configured to control the light emitting element at least in dependence of the motion detector.

2. The light fixture (170) of any of the preceding claims, wherein the motion signal comprises a first channel (I) and a second, different channel (Q), the first and second channels being related to motion in the motion sensor environment.

3. The luminaire (170) of claim 2, wherein a complex signal (I + jQ) is obtained from the first and second channels, and the transformation is a complex transformation.

4. A luminaire (170) according to claim 2 or 3, wherein the sensor is a two-channel doppler microwave sensor.

5. The luminaire (170) of any of the preceding claims, wherein the signal processing comprises transforming the motion signal from a time domain to a frequency domain to obtain the plurality of motion components.

6. The light fixture (170) according to any of the preceding claims, wherein movements having opposite directions contribute to different motion components of the plurality of motion components.

7. The light fixture (170) according to any of the preceding claims, wherein the plurality of motion components correspond to a frequency, motions with opposite directions contributing motion components with the same frequency but opposite signs.

8. The luminaire (170) of any of the preceding claims, wherein the motion component corresponding to a frequency is subtracted from the motion component having the same frequency but opposite sign to eliminate the motion component corresponding to a motion having an opposite direction.

9. The luminaire (170) of any of the preceding claims, wherein eliminating two motion components comprises subtracting one of the two motion components from a correction factor (f) before subtracting the two motion componentsβ) Multiplication.

10. The luminaire (170) of any of the preceding claims, wherein eliminating the two motion components comprises calculating

Therein withoutA(ω) I represents the magnitude of the motion component of frequency omega,βrepresenting a correction factor.

11. A luminaire (170) according to claim 9 or 10, wherein the processor system is configured to estimate the correction factor during use of the motion sensor.

12. The luminaire (170) of claim 11, wherein the processor system is configured to:

-determining whether the motion signal corresponds to a non-vibratory motion,

-estimating a correction factor from the motion signal.

13. The light fixture (170) according to any of the preceding claims, further comprising at least one light emitting element.

14. A motion detection method (700), comprising:

-receiving (710) a motion signal from a luminaire (170) comprising a motion sensor, the motion signal relating to motion in a motion sensor environment, wherein the luminaire is connectable to a light emitting element (172),

-signal processing (720) the motion signal to obtain a plurality of motion components, the motion components being related to a direction and a velocity of motion in the environment,

-eliminating (730) two motion components corresponding to motions having opposite directions among the motion components,

-detecting (740) motion in the environment from the motion components that are not eliminated,

-controlling the light-emitting element at least in dependence of the motion sensor.

15. A transitory or non-transitory computer-readable medium (1000) comprising data (1020) representing instructions to cause a processor system to perform the method according to claim 14.

Technical Field

The invention relates to a luminaire, a motion detection method and a computer readable medium.

Background

Reliable motion detection is important in many areas. For example, motion detection is used in lighting systems to control lighting. The use of a motion detector may avoid turning on the light when nobody is present. Other applications are for example for burglar alarms and office occupancy detection, for example for office management.

Unfortunately, motion sensing presents a number of problems. One problem with motion sensors is that they may be sensitive to certain types of narrowband noise (sometimes referred to as buzzes or buzzing types of noise). In particular, sensors based on the doppler effect are susceptible to false positives caused by buzzing noise.

A known motion sensor is described in korean patent application KR20160141503 "apparatus and method for driving a lamp". In korean patent application, an illumination driving apparatus for driving an illumination apparatus equipped with a motion sensing member is disclosed. The device automatically controls the lighting depending on whether motion is detected.

The motion detection unit is a microwave (RF) doppler sensor and detects motion by detecting waves generated from a wave source using the doppler effect. The motion sensing unit may detect not only the motion of an object but also vibrations occurring in the surrounding environment. There is a problem in that the lamp may be turned on when only vibration occurs without movement.

Fig. 1 of the cited patent illustrates a known lighting driving device. In addition to the motion sensing unit 12, the known device comprises a vibration sensing unit 11 for sensing vibrations.

The motion sensing unit 12 is an RF doppler sensor which senses motion using doppler effect using microwave (RF) and outputs a motion sensing signal of a corresponding magnitude. The vibration sensing unit 11 is a Micro Electro Mechanical System (MEMS) that measures acceleration and senses vibration, and outputs an electric signal of a corresponding magnitude as a vibration sensing signal.

The controller lights the illumination device 4 when the motion detection unit 12 detects motion, but lights only when no vibration is detected. This prevents the lighting device 4 from being switched on when a vibration is detected.

US2018/263502a1 discloses the use of radar signals to estimate heart rate, heart rate variation, respiration rate and/or respiration rate variation of a human or other animal. Respiratory motion in the radar baseband output signal can be estimated. The estimated respiration signal can then be subtracted from the radar signal in the time domain and can be further enhanced using digital signal processing techniques to produce an estimate of the heartbeat pulses.

Disclosure of Invention

The known system has a number of disadvantages. First, known systems require a separate vibration sensor in addition to the motion sensor. This increases the parts inventory, increases system complexity and cost. Second, as long as vibration is detected, motion cannot be detected. The hum may be intermittent and may only last for a few seconds, but the inventors have observed that hum-type noise may also last for hours. This continuous hum may disable the known system because no movement is detected and no lights are turned on while the hum continues. Alternatively, the threshold for vibration may be set at a high level so that the risk of false positives due to one or more sources of buzzing noise still exists. Third, known systems only detect mechanical vibrations. However, the inventors have observed that hum noise may also originate from the air supply.

To address these and other problems, a light fixture including a motion detector is presented. The motion detector includes:

a motion sensor interface configured to receive motion signals from a motion sensor, the motion signals relating to motion in a motion sensor environment,

-a processor system configured to

-signal processing the motion signal to obtain a plurality of motion components, the motion components being related to the direction and speed of motion in the environment,

-eliminating in the motion component two motion components corresponding to motions having opposite directions,

-detecting motion in the environment from the non-eliminated motion components. The luminaire is connectable to the light-emitting element and configured to control the light-emitting element at least in dependence of the motion detector.

The advantage of motion detection is that no separate vibration sensor is required. Instead, hum noise may be removed from the output of the motion sensor. For example, in an embodiment, the determining may include determining the energy in the remaining frequency bins. For example, if the determined energy exceeds a threshold, the environment may be classified as motion. The frequency bins may be implemented as coefficients produced by a frequency domain transform (e.g., FFT, DFT, etc.). The frequency bin is referred to as a bin because it actually corresponds to a narrow range of frequencies, which for a doppler sensor correspondingly corresponds to a narrow range of velocities of the area surrounding the sensor.

The inventors have the insight that vibrations in the environment comprise two movements having opposite directions. By removing the motion component having such a contour, vibration noise is reduced.

In an embodiment, the motion signal comprises a first channel (I) and a different second channel (Q), the first channel and the second channel being related to motion in the environment of the motion sensor. Accessing both channels is one way in which the direction of motion can be determined from the motion sensor.

For example, by performing frequency transformation, a motion component corresponding to a frequency, e.g., both a positive frequency and a negative frequency, can be obtained. In general, motion toward and away from the sensor may be represented as positive and negative frequencies, respectively, or vice versa. Thus, noise cancellation may include subtracting a motion component corresponding to a positive frequency from a motion component having a corresponding negative frequency. The frequency transform is typically done using a fourier transform (e.g., FFT), but another option is to apply a wavelet decomposition to obtain the motion components.

Due to imperfections in the motion sensor, real motion, such as non-humming noise, e.g., a walking person, may contribute to one or more of the positive frequency motion components, but may inadvertently contribute to the corresponding negative frequency. By subtracting the motion component, this may reduce the energy in the positive signal, which may increase the chance of false positives (e.g., the detector does not detect motion even if motion is present). This can be avoided by applying a correction factor that corrects for sensor defects. For example, in an embodiment, a correction factor may be applied to the motion component before the two motion components are subtracted. Interestingly, symmetrizing the application of the correction factor may result in the resulting factor still removing the hum noise.

One aspect of the invention relates to a motion detection method.

Embodiments of the method may be implemented on a computer as a computer-implemented method, or in dedicated hardware, or in a combination of both. Executable code for embodiments of the method may be stored on a computer program product. Examples of computer program products include memory devices, optical storage devices, integrated circuits, servers, online software, and so forth. Preferably, the computer program product comprises non-transitory program code stored on a computer readable medium for performing the embodiments of the method when said program product is run on a computer.

In an embodiment the computer program comprises computer program code adapted to perform all or part of the steps of an embodiment of the method when the computer program runs on a computer. Preferably, the computer program is embodied on a computer readable medium.

Drawings

Further details, aspects and embodiments of the invention will be described, by way of example only, with reference to the accompanying drawings. Elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. In the figures, elements corresponding to elements already described may have the same reference numerals. In the drawings, there is shown in the drawings,

figure 1a schematically shows an example of embodiment of a motion detector,

figure 1b schematically shows an example of embodiment of a luminaire,

figure 1c schematically shows an example of embodiment of the illumination system,

figure 2a shows a graph of the magnitude of the FFT transformation of a single channel motion sensor signal,

figure 2b shows a graph of the magnitude of the FFT transformation of the two-channel motion sensor signal,

figure 2c shows a graph of the magnitude of the FFT transformation of a single channel motion sensor signal,

figure 2d shows a graph of the magnitude of the FFT transformation of the two-channel motion sensor signal,

figure 3 schematically shows an example of embodiment of a dual channel motion sensor,

figure 4a shows a graph of the magnitude of the FFT transformation of a two-channel motion sensor signal,

figure 4b shows a graph of the size of the FFT transform with noise cancellation,

figure 4c shows a graph of the magnitude of the FFT transformation of the two-channel motion sensor signal,

figure 4d shows a graph of the size of the FFT transform with noise cancellation,

figure 5a schematically shows an example of an embodiment of the motion detector,

figure 5b schematically shows an example of an embodiment of the motion detector,

figure 6 schematically shows an example of an embodiment of the motion detector method,

figure 7a schematically shows a computer-readable medium having a writeable part comprising a computer program according to an embodiment,

fig. 7b schematically shows a representation of a processor system according to an embodiment.

List of reference numerals in fig. 1a-5b, 7a-7 b:

100, 101, 102 motion detector

110 motion sensor

112 sensor

114 signal processing unit

120 signal input terminal

130 frequency domain converter

140. 141 noise eliminating unit

150 motion detection unit

162 correction term estimator

164 correction term memory

170 lamp

171 illumination system

172 luminous element

173 computer network

175 lighting controller

210, 220 frequency spectrum

230, 240 spectrum

211, 213 Peak

212 positive frequency

214 negative frequency

221 Peak

223 without peak

411, 413 hum noise correlation peak

412 motion correlation peak

414 no peak

500 motion sensor

510 transmission signal generator

511 emitter

512 receiver

520 phase shifter

530 Mixer

540 Mixer

550 low-pass filter

560 low pass filter

551Q signal

561I signal

1000 computer readable medium

1010 writable portion

1020 computer program

1100 device

1110 system bus

1120 processor

1130 memory

1140 user interface

1150 communication interface

1160 memory device

1161 operating system

1162,1163, and 1164 instructions.

Detailed Description

While this invention is susceptible of embodiment in many different forms, there is shown in the drawings and will herein be described in detail one or more specific embodiments, with the understanding that the present disclosure is to be considered as an exemplification of the principles of the invention and is not intended to limit the invention to the specific embodiments illustrated and described.

In the following, for the sake of understanding, elements of the embodiments are described in operation. It will be apparent, however, that the various elements are arranged to perform the functions described as being performed by them.

Furthermore, the invention is not limited to these embodiments, and lies in each and every novel feature or combination of features described herein or recited in mutually different dependent claims.

Fig. 1a schematically shows an example of an embodiment of a motion detector 100.

Motion detectors can be used in a variety of applications, with illumination being particularly advantageous. For example, fig. 1b schematically shows an example of an embodiment of a luminaire 170. Light fixture 170 may include motion detector 100 and lighting element 172. For example, the illumination element may be configured to radiate light when motion is detected by the motion detector 100. The lighting element may be one or more LEDs. For example, fig. 1c schematically shows an example of an embodiment of an illumination system 171. The lighting system 171 includes a light fixture 170 (typically a plurality of light fixtures), a motion detector 100 (typically a plurality of motion detectors), and a lighting controller 175. The lighting controller 175 is configured to receive motion signals, such as a quiet/motion classification, from the motion detector(s) and determine lighting control signals based thereon. The lighting control signal is sent to one or more luminaires, which then illuminate according to the control signal. One or more motion detectors may be incorporated into the light fixture, but this is not required. Communication between the motion detector, the lighting controller and the light fixture may be over a digital communication network, such as a computer network.

For example, the various devices of the system 171 may communicate with one another over a computer network 173. The computer network may be the internet, an intranet, a LAN, a WLAN, etc. The computer network 173 may be the internet. The computer network may be wired in whole or in part and/or wireless in whole or in part. For example, the computer network may include an ethernet connection. For example, the computer network may include a wireless connection, such as Wi-Fi, ZigBee, and the like. The devices include connection interfaces that are arranged to communicate with other devices of the system 171 as needed. For example, the connection interface may include a connector, such as a wired connector, e.g., an ethernet connector, an optical connector, etc., or a wireless connector, e.g., an antenna, such as a Wi-Fi, 4G, or 5G antenna. For example, devices 100, 175, and 170 may each include a communication interface. The computer network 173 may include additional elements such as routers, hubs, etc.

The operation of the motion detector 100 may be implemented in processor circuitry, examples of which are illustrated herein. For example, fig. 1a shows functional units which may be a motion detector and a functional unit such as a processor circuit. For example, FIG. 1a may be used as a blueprint for a possible functional organization of processor circuitry. The processor circuit is not shown separately from the units in fig. 1 a. For example, the functional units shown in fig. 1a may be implemented in whole or in part as computer instructions that are stored at the device 100, e.g., in an electronic memory of the device 100, and that are executable by a microprocessor of the device 100. In a hybrid embodiment, the functional units are implemented partly in hardware, e.g. as coprocessors, e.g. signal coprocessors, and partly in software stored and executed on the device 100.

In addition to lighting control, motion detectors have other applications. For example, motion detectors may be used in burglar alarms. For example, motion sensors may be used to detect occupancy of an office, which in turn may be used to manage the office, e.g., suggest an empty office for use, or report office occupancy over time.

As shown in fig. 1a, the motion detector 100 includes a motion sensor 110; but this is not essential. The motion detector 100 may use an external motion sensor. Part of the signal processing may be done in an external motion sensor or in the motion detector itself. In an embodiment, the motion sensor 110 may be an integral part of the motion detector 100. The motion sensor 110 is configured to generate a sensor signal for a motion detector.

There are many options for motion sensors. For example, the motion sensor 110 may be a doppler motion sensor, a microwave sensor, or an ambient light sensor, among others. As an excitation example, embodiments will be described below for a doppler sensor. It should be noted, however, that the motion detector may be combined with any motion sensor that has problems with noise, particularly of the hum type.

In an embodiment, the motion sensor 110 may include a sensor 112 and a processing unit 114. The processing unit 114 may perform pre-processing before the signal is further processed by the rest of the motion detector 100. The processing unit 114 is optional.

For example, in an embodiment, the motion sensor 110 may be of the doppler type. For example, a doppler sensor may be configured to detect motion or velocity of a moving object by the doppler principle. The sensor 112 may be configured to transmit a signal, such as a microwave signal. For example, the transmitted signal may have a frequency from 5 to 30GHz and/or from 30 to 100GHz, etc., lower or higher being possible. Examples of signal frequencies include: 5.8GHz, 24 GHz and 60 GHz. For example, the transmitted signal may have frequencies in the ultra high frequency band (SHF) or the extremely high frequency band (EHF).

The sensor 112 may be configured to receive a back signal. The shift in the frequency signal is related to the velocity of the moving object reflecting the transmitted signal relative to the sensor. For example, one way of processing in a doppler sensor is to calculate the product of the transmitted signal and the received signal and apply a low pass filter to the multiplied signal. The resulting signal may be indicated by a geometric function to include a frequency shift. For example, the processing unit 114 may be configured to multiply the transmit signal and the receive signal and apply a low pass filter.

The resulting signal is provided to the signal input 120 of the motion detector 100. For example, the signal input 120 may be an internal input. The signal input 120 may also be an input port, such as an electronic input port, or a digital input port, such as an API or the like. For example, in an embodiment, the sensor signal of the motion sensor 110 received at the signal input 120 may be a signal in which the frequency component corresponds to a doppler shift and thus to the velocity of an object in the area surrounding the sensor 110. In an embodiment, the signal is a received signal reflected by a surrounding area object. In the latter case, further doppler processing may be performed after the signal is received at the signal input.

In an embodiment, the motion sensor interface 120 is configured to receive motion signals from the motion sensor 110. The motion signal is related to motion in the motion sensor environment. In particular, the motion signal is arranged such that the direction of motion in the environment is related to the motion signal. The correlation need not be perfect. For example, it is sufficient if the correlation is only related to the projection of the direction of motion. For example, the direction of motion may be directed to a line from a moving object toward the sensor 110. For example, some noise cancellation may be achieved if two equal motions with opposite directions (e.g., relative to each other) can be distinguished from each other in the motion signal. In an embodiment, the motion signals are Q and I time domain signals.

In an embodiment, the motion sensor 110 is a so-called dual channel sensor, e.g. the motion signal contains two channels, each channel being associated with motion in the environment. Since two channels are available, more information about the direction of motion in the environment can be obtained. For example, in an embodiment, the motion signal includes a first channel (I) and a second, different channel (Q), the first and second channels being related to motion in the motion sensor environment.

In an embodiment, the first and second channels are obtained by mixing the received reflected signal with a first and second mixed signal, respectively, the first and second mixed signals having a phase difference of at least 30 degrees, preferably at least 70 degrees, more preferably 90 degrees.

For example, the motion sensor may be a two-channel doppler microwave sensor. The output of the sensor may have been processed into I and Q channels by the signal processing unit 114, but this is not required; for example, the motion sensor may derive raw received signals and perform signal processing in the motion sensor 110.

Fig. 3 schematically shows an example of an embodiment of a dual channel motion sensor 500. For example, a dual channel motion sensor 500 may be used for the motion sensor 110. Fig. 3 shows only one architecture of the motion sensor 110 and other options are possible.

Fig. 3 shows a transmission signal generator configured to generate a signal, e.g. a sinusoidal signal, for transmission by the transmitter 110. The transmitted signal is reflected by objects in the environment of the sensor 500. The reflection is received in a receiver 512. The receive signal is mixed with the transmit signal in mixer 540 and directed through a low pass filter 560 to obtain an in-phase signal 561, e.g., an I-channel 561. The transmitted signal 510 also experiences a phase shift, typically shifted by more than 90 degrees. The received signal is mixed with the phase-shifted transmit signal in mixer 530 and directed through a low-pass filter 550 to obtain a quadrature signal 551, e.g., a Q-channel 551. Typically, phase shifter 520 is shifted 90 degrees, but this may be different. In particular, the offset may be slightly more or less due to inaccuracies. For example, the phase shift of phase shifter 520 may be between 85 degrees and 95 degrees. An offset of 270 degrees is considered equivalent to an offset of 90 degrees. Non-ideal components, such as amplifiers and phase shifters 520, etc., may also introduce slight variations in signal amplitude. Due to these factors, the two channels may deviate slightly from the perfect I and Q channels. This will still allow noise cancellation at least to some extent, provided the deviation is sufficiently small relative to the frequency bin size of the subsequent frequency translation. Inaccuracies in the motion sensor 110, 500 and its signal processing can be corrected. Such corrections will be explained further below and are optional.

Many variations of the motion sensor 500 are possible. For example, mixing and filtering may be done analog and/or digitally. For example, motion sensor 500 may include one or more antennas. The mixing may be implemented as a multiplication between two signals. For example, in an embodiment, the original received signal is mixed with first and second signals that differ in phase. Some components may be reused, etc.

Returning to fig. 1a, signals 551 and 561 may be received by motion sensor 100 in signal interface 120.

The motion detector 100 includes a frequency domain converter 130, a noise removal unit 140, and a motion detection unit 150. The frequency domain converter 130 converts the received signal from the time domain to the frequency domain. For example, converter 130 may perform a fourier transform. For example, converter 130 may perform a Discrete Fourier Transform (DFT). If desired, converter 130 may first perform an analog-to-digital conversion, such as an ADD conversion, before performing the conversion to the frequency domain.

In an embodiment, the signal processing of the frequency domain converter 130 comprises transforming the motion signal from the time domain to the frequency domain to obtain a plurality of motion components. The motion component represents motion at a particular speed and direction relative to the sensor. The motion component may further represent motion at a particular distance relative to the sensor. Typically, the motion component is sensitive to a range of velocities. Preferably, movements having opposite directions with respect to the sensor correspond to different movement components.

The plurality of motion components may be frequency transform coefficients of the motion signal, such as FFT, DFT, or the like. For example, the plurality of motion components may be frequency bins of a frequency domain converter. In an embodiment, the frequency domain conversion is performed on a combination of two channels, for example a combination of I and Q channels. In particular, the transform may be a complex transform; for example, the frequency transform may be applied to a complex combination (I + jQ), where j represents a complex unit. The result of the frequency transformation may be a complex signal. For example, the complex amplitudes of the frequency bins may be obtained.

In an embodiment, the motion signal received in the input 120 is divided into a plurality of portions, for example a plurality of portions having a predetermined number of time domain samples. Frequency conversion may be performed on each section. As a result, so-called frequency bins are obtained. The frequency bins are the amplitudes of the frequency ranges present in the received signal. For example, one frequency bin may represent a frequency range of 40-42 Hz. The frequency range corresponding to the frequency bins may be, for example, about 2Hz or more or less, for example in the range from 0.5 to 5 Hz. The size of the frequency bins can be considered as the absolute value of the amplitude. In an embodiment, the signal processing may be configured to detect motion components within a time period or time segment. The time period may be one second, one half second, etc. In an embodiment, the time period is less than 30 seconds.

For example, the frequency conversion may be performed after each obtaining of a predetermined number of time domain samples. For example, the frequency domain conversion may be performed every 24 time domain samples. For example, in an embodiment, a 5.8Ghz sensor is combined with 24 time domain samples per time slice.

For example, sampling may be done at a frequency of 250 Hz and an FFT of length 128 points may be performed every 24 new samples. In this case, the FFTs overlap. For an optical switch, it is preferable to report motion quickly, for example, within 0.5 seconds. In the above example, there are some FFTs used to make the decision. For other cases, more time may be required: for example, when a motion is triggered when the light is on, or for occupancy detection.

Thus, the frequency bins show evolution over time; an increase in frequency bins, for example, an increase in the size of a particular frequency range may correspond to an increase in a particular velocity in the area surrounding the sensor. An increase in frequency bins may indicate motion in this region. A high pass or low pass filter or both may be applied to the signal or frequency bins to eliminate frequencies that are too high or too low to be used.

In an embodiment of the frequency domain converter, the motion signal is signal processed to obtain a plurality of motion components. For example, the plurality of motion components may be coefficients of a frequency transform of I + jQ. The motion component is related to the direction and speed of motion in the environment. In particular, two motions with opposite directions contribute to two different motion components corresponding to the motions with opposite directions.

In particular, motions having opposite directions with respect to each other contribute to different motion components, e.g. motion components associated with positive and negative frequencies. In practice, this will be the case even if the direction of motion is detected relative to the direction of view of the motion sensor (e.g. projected onto the motion sensor). In an embodiment, the motion with opposite directions contributes to different motion components of the plurality of motion components.

It is sufficient that the motion sensor only measures the velocity towards or away from the sensor, which may be referred to as the projection velocity. Interestingly, the vibrating object hardly changes position, which makes the velocity amplitudes towards and away from the sensor equal.

Terms like opposite direction and same speed are understood to mean within the threshold. The threshold may be implicit. For example, if two motions contribute to opposite fourier coefficients, they can be considered to be opposite directions.

In an embodiment, the plurality of motion components correspond to a frequency of a frequency transform. In particular, for a dual channel I and Q sensor, motion having opposite directions contributes to motion components having the same frequency but opposite signs.

Fig. 2a shows a graph of the magnitude of the FFT transformation of a single channel motion sensor signal. Shown in fig. 2a is the spectrum obtained when a person walks towards the sensor. The positive frequency is shown at 212 and the negative frequency is shown at 214. In this example, a single channel motion sensor is used, where the motion signal contains no information about the direction of motion. In particular, fig. 2a is obtained by performing a real FFT on only the I-channel data. The obtained motion component does not give directional information. Note that after N/2 FFT bins, the FFT values repeat.

The peak 211 shown in the spectrum 210 corresponds to the pedestrian's motion. However, the peak repeats at 213, indicating a lack of sensitivity to the direction of motion.

Fig. 2b shows a graph of the magnitude of the FFT transformation of the two-channel motion sensor signal. Shown in fig. 2b is the spectrum obtained when a person walks towards the sensor. In this example, a dual channel motion sensor is used, where the motion signal contains information about the direction of motion. In particular, fig. 2b is obtained by performing a complex FFT on the I and Q channel data. The obtained motion component does give directional information. Note that after N/2 FFT bins, the FFT values do not repeat. Fig. 2b shows the size of the frequency bins.

The peak 221 shown in the spectrum 220 corresponds to the pedestrian's motion. The peak does not repeat at the negative frequency 223, indicating a lack of sensitivity to the direction of motion.

Fig. 2c and 2d further illustrate the sensitivity to the direction of movement. Fig. 2c and 2d are similar to fig. 2a and 2b, except that the person is walking away from the sensor. Also in this case, the spectrum 230 of the single channel sensor shows repeating peaks. However, the spectrum 240 of the dual channel sensor shows a single peak. Unlike fig. 2c, the peak is now located at a negative frequency, indicating that the motion is away from the sensor rather than towards the sensor.

The motion sensor 100 includes a noise cancellation unit 140 that utilizes this difference. The noise removing unit 140 is configured to remove two motion components corresponding to motions having opposite directions among the motion components.

For example, a motion component corresponding to a particular frequency may be subtracted from a motion component of the same frequency but opposite sign to eliminate motion components corresponding to motion having opposite directions. For example, assume array F₊[i]Representing a component of motion having a direction towards the sensor, exponentialiDistributed over the motion component. For example, for two motion components F of two different values of the index i₊[i ₀]And F₊[i ₁]Possibly associated with movements of different speeds, although they are all directed towards the sensor. Note the reality in the environmentMotion need not be directed to the sensor; for example, a direction component may be represented in the motion component, such as a direction component obtained by projecting the actual direction of motion onto a line from the moving object to the sensor. Suppose a second array F_-[i]Representing a component of motion having a direction away from the sensor, exponentialiDistributed over the motion component. For example, the motion component F₊[i]And F_-[i]May represent movements having the same speed but different directions relative to the sensor. To eliminate the vibrating motion, for example a so-called humming noise, a new array F [ can be calculatedi]=F₊[i]-F_-[i]. Typical vibratory motion has little positional variation and equal velocity toward and away from the sensor, noting that any orthogonal components associated with the sensor can be ignored. In the array F, non-vibrating moving objects, especially moving, e.g. walking, objects₊One or more values in the array contribute, but to F_-The array does not contribute and vice versa. However, vibrating the object will be paired with F₊And F_-The arrays all contribute and, in fact, do so in the same way, in general. By subtracting these two components, the contribution of the vibrating object to the motion component is eliminated, but the walking motion is not.

Many variations are possible. For example, array F₊、F_-And F may be represented in different ways. In particular, array F₊And F_-May be represented in a single array. For example, array values from 0 to N/2 may represent positive frequencies, while array entries from N/2 to N may represent negative frequencies. If the amplitude at the positive and negative frequencies are of different sign, this can be solved by using a size, for example Fi]=|F₊[i]|-|F_-[i]Neglecting the imaginary or real part, by removing signs from the imaginary and real parts, e.g. mapping all amplitudes to the same quadrant, etc.

Some modifications to this approach are possible. For example, phase differences other than 90 degrees may be corrected, or amplitude differences between two channels, such as caused by imperfect components, may be corrected. This will be further expanded below.

Complex-valued calculations are not required, especially after frequency conversion. For example, F may be replaced by their size₊And F_-Of (2) is low. For example, in the above expression, F2 can be calculatedi]=|F₊[i]|-|F_-[i]L. Interestingly, the subtraction may even reduce the hum if the hum and motion result in elevated frequency bins of the same frequency.

Finally, the motion detector 150 may detect motion in the environment. For example, the motion detector may be configured to detect motion in the environment from motion components that are not eliminated. For example, detecting motion may include determining energy in the motion components that are not eliminated. If the determined energy exceeds a threshold, the environment may be classified as motion. For example, the motion detector 150 may be configured to detect the motion component F [ alpha ]i]=F₊[i]-F_-[i]Detecting motion, e.g. by aligning | F [ ]i]|²And (6) summing.

Detecting motion may include detecting motion on a per frequency bin basis. This has the advantage that different motion thresholds can be used for different frequencies. Detection may be performed after noise is removed, for example, by subtracting all positive frequencies from all negative frequencies. The detection can also be done together. For example, one may decide whether each elevated frequency bin corresponds to motion or hum; in the former case, it is called motion. The presence or absence of elevated frequency bins at the opposite frequency may then be factored into the presence or absence of noise. However, other factors may also be considered. For example, real motion typically results in multiple successively increasing frequency bins, while hum noise typically increases by only one or a few, such as two, frequency bins. After each frequency bin identification is completed, motion detection may be determined based on determining the frequency bin associated with the motion; for example, the energy is summed in frequency bins of the recalled motion.

For example, motion detection may include detecting frequency bins having an elevated size. For each frequency bin having a higher size, for example, the bin may be said to have seen motion as compared to the threshold for that bin. In addition to the hum canceling characteristics of the signal processing described herein, other signal processing may be performed, and in particular other algorithms may be applied to detect hum noise and/or true motion. For example, for each run of the motion algorithm, each elevated frequency bin may be checked for a hum condition. Only the frequency bins that invoke motion and/or are not identified as hum may contribute to detecting motion. Note that real motion triggers a motion invocation even if a buzz condition exists in one or more frequency bins. In an embodiment, for each time segment, the motion detector may check the increased size and motion of all frequency bins.

After the conversion from the time domain to the frequency domain, the motion detection unit 150 detects motion from frequency bins (e.g., from the size of the frequency range).

For example, the motion detection unit 150 may be configured to identify frequency bins having increasing sizes. For example, a size above a threshold may be detected. The threshold may be predetermined. High values in a frequency bin may correspond to a large object or many objects with corresponding velocities. However, frequency bins of increasing size may also be caused by noise. There may be one or several thresholds for all frequency bins, or one threshold for each frequency bin, etc.

For example, the motion detection unit 150 may be configured to estimate whether the identified frequency bins correspond to a source of motion or a source of noise in the environment.

Fig. 4a shows the spectrum of the magnitude of the FFT transformation of the two-channel motion sensor signal. The spectrum 4a is created from a computer simulation of a two-channel doppler motion sensor. In the simulation, there was an object moving and there were two buzz-type noise sources. The complex frequency transform yields an array a (ω) that represents the magnitude of the frequency ω. In this example, the frequency is from-600 Hz to +600 Hz. Fig. 4a illustrates the absolute value of the frequency amplitude. Note that fig. 4a shows a plurality of peaks caused by doppler shift due to motion in the environment. The peak at 411, between about 0 and 200 Hz, is caused by vibrations in the environment. This oscillatory motion also causes a peak at a corresponding negative frequency, which can be seen at 413, for example between about 0 and-200 Hz. The peak at 412 is also shown in FIG. 4 a. The peak is at about 300 Hz, corresponding to non-vibratory motion. Note that peak 413 is not mirrored at-300 Hz.

Fig. 4b shows a graph of the size of the FFT transform with noise cancellation. Fig. 4b is obtained from fig. 4a by subtracting the magnitude of the negative frequency from the corresponding positive frequency. As a result, the peak corresponding to the buzz noise has been completely eliminated, while the 300 Hz peak corresponding to the non-vibratory motion is still present. Motion can be detected reliably with increased from fig. 4b because the false positive from the hum has decreased. Note that fig. 4b contains no noise, which is an analog artifact.

Fig. 4c and 4d are graphs showing the effect of removing true motion from the sensor environment, but leaving a buzz noise. The peak at 412 has been removed because there is no real motion, although the peak caused by the buzz is still present. FIG. 4d shows how the noise cancellation map is generated; no peaks remained. When the motion detection algorithm is applied to fig. 4d instead of fig. 4b, no motion will be detected because there is no residual energy in the spectrum.

Note that the energy difference between fig. 4a and 4c is relatively smaller than the energy difference between fig. 4b and 4d, indicating that it is easier to set the exact threshold values for fig. 4b and 4d to detect motion than fig. 4a and 4 c. Worse still, the number of buzzing sources may change over time. The hum may occur from seconds to hours, from one or more sources. The scale of the axes in fig. 2a-2d and 4a-4d is automatically set.

A problem with motion sensors, particularly those of the doppler type, is a type of noise, known as hum noise. A source of buzzing noise can cause the signal in a frequency bin to rise, usually intermittently. The hum may be caused by vibrations, for example by a driver inside the luminaire or by an external device. Hum may also be caused by mechanical structures in the environment, such as the foil optics present in T-LED fixtures. The hum is often limited to one or two adjacent frequency bins, e.g., having a bandwidth of about a few hertz, but sometimes the hum may span more than 2 frequency bins.

The intermittency of the signal can result in false alarm motion invocation. For example, a source of hum noise, such as an electronic drive or foil optics, may cause an increase in a particular frequency interval, which in turn may be interpreted as movement of the area around the sensor, but in practice this is simply due to the hum noise.

The motion detector 150 may be configured to classify the environment as quiet or moving according to the noise-cancelled motion components (e.g., frequency bins).

The motion detector 150 may be classified in a variety of ways. For example, depending on the application, the motion detector may be configured to detect or not detect small motions. For example, a motion detector used in an office for lighting control may be configured to have a low motion threshold, e.g., to detect motion such as typing. For example, a motion detector for lighting control used in a hallway may be configured to have a larger motion threshold, e.g., to detect larger motions, such as walking. This avoids that in the first case the lights will be off when the occupant is relatively still except for small movements like typing, or in the second case the lights in the corridor will be easily turned on due to false alarms.

For example, the motion detector 150 may be configured to determine the energy in frequency bins (e.g., frequency bins or portions thereof estimated to correspond to a motion source). If the determined energy exceeds a threshold, the environment may be classified as motion. For example, the energy may be calculated by summing the sum of squares and frequency bins. For example, the energy may be weighted energy. For example, frequencies corresponding to walking speed may be given higher weight than those not corresponding to walking speed. If the energy or weighted energy in a frequency bin corresponding to motion (e.g., not corresponding to noise) exceeds a threshold, then the region is classified as motion. If not, the area may be classified as quiet. By adjusting the threshold and/or the weights, the sensitivity of the motion detector can be adjusted according to the needs of the application. This can be done empirically.

Instead of classifying the environment as motion or quiet, for example, in a binary classification, the motion sensor may report a value indicating a likelihood that motion is present in the environment. For example, the energy in the noise cancellation spectrum may be mapped to a floating point value, e.g. a fraction between 0 and 1, e.g. using a sigmoid function.

At the edges of the frequency bins, e.g., at the higher and lower bins, some special considerations may be required. The inventors have also found that at the low end of the frequency, the sensor is generally unreliable. In an embodiment, frequency bins below the frequency floor are estimated to be caused by noise. For example, for a 5.8Ghz sensor, the noise frequency floor may be less than 9.3 Hz. These low frequencies are found to have more spurious signals and are therefore unreliable and inconsistent. For other sensor modes, the value will scale. For example, the cut-off frequency increases with the sensor frequency of the doppler sensor.

Motion detectors with noise filtering, such as motion detector 100, run the risk of ignoring motion signals, e.g., misinterpreting true motion as being caused by noise. As noted herein, the various parameters discussed may be adjusted to increase or decrease the likelihood of this occurring. The inventors have found that mistaking real motion for noise in a lighting device (e.g. luminaire 170 or lighting system 171) can have a more serious impact if a person is actually present. In an embodiment, this may be avoided by suppressing noise reduction if a person is present, e.g. if the light emitting element is turned on. The noise reduction may be turned off entirely or different tradeoffs may be configured by changing its parameters.

If the light is on, this means that a person is present in the detection area. If the noise filter detects the motion signal as noise and removes it, this may not immediately have a serious effect, since the lamp may not be turned off immediately; they may be configured to remain on for a period of time after motion is detected. The system is constantly looking for motion and if it sees at least one motion within a configured time interval before shutting down, no previous false positive errors are observed at the system level because the effect is not visible. However, if no other motion is seen within the configured interval, the lamp will eventually turn off, resulting in unpleasant behavior.

Typically, the motion detector 100, the light fixtures 170, 171, the lighting controller 175 each include a microprocessor that executes appropriate software stored in these devices; for example, the software may have been downloaded and/or stored in a corresponding memory, e.g. a volatile memory such as a RAM or a non-volatile memory such as a flash memory. Alternatively, the device may be implemented in whole or in part in programmable logic, for example as a Field Programmable Gate Array (FPGA). The devices may be implemented in whole or in part as so-called Application Specific Integrated Circuits (ASICs), e.g., Integrated Circuits (ICs) tailored to their particular use. For example, the circuit may be implemented in CMOS, for example using a hardware description language such as Verilog, VHDL, etc.

In an embodiment, the motion detector comprises one or more electronic circuits. The circuits implement the respective units described herein. The circuits may be a processor circuit and a storage circuit, the processor circuit executing instructions electronically represented in the storage circuit. The processor circuit may be implemented in a distributed manner, for example, as a plurality of sub-processor circuits. The storage device may be distributed over a plurality of distributed sub-storage devices. Some or all of the memory may be electronic memory, magnetic memory, or the like. For example, the memory may have volatile and non-volatile portions. Part of the storage may be read-only.

One challenge with motion sensors is that there is no false alarm, e.g., false trigger in the case of non-motion signals (such as buzzes/vibrations), which is common. The inventors have observed that sometimes during operation of a motion sensor for motion detection, sudden vibrations are seen in the frequency domain, which tend to be more concentrated in one or two adjacent frequency bins, e.g. having a bandwidth of about a few hertz. Such vibrations typically last at least a few seconds, sometimes even minutes or hours. These vibrations are called buzzes because they are more localized. In contrast, the spectral range of the motion signal is much wider, and therefore this property can be used to isolate the suddenly starting hum signal from the motion signal.

As described above, a noise source may cause intermittently rising signals in a certain frequency bin. The intermittent nature of the signal can lead to false positive motion invocation. This problem may be solved with the noise cancellation unit 140, for example, by reducing the amplitude of frequency bins that may be affected by noise, in particular buzz-type noise. Removing such frequency bins from consideration for motion detection may also be used as a noise filter. The hum detector may be implemented as a filtering enhancement to a motion algorithm that identifies frequency bins that experience a hum condition and eliminates their contribution to the invoked motion. It was found that additional signal processing could detect and interpret hum or vibration so they were not classified as motion.

In a doppler sensor, the frequency of a moving object can be estimated. In general, for a frequency off ₀The following relationship may be used:wherein c is the speed of light,f ₀is the sensor frequency, ΔfThe doppler frequency is described. Vibrations differ from human motion in that, for example, the excitation frequency bins of the vibrations are generally narrower and the vibrations are vibratingfTypically not changing over time. If the time domain signal is sampled at 40 Hz, it can be analyzed using a 128-point FFT.

Although the parameters of the hum detector may be carefully adjusted, the hum filter always risks identifying motion events as vibrations. This is especially important for small movements, such as actions that a human makes behind an office desk. To avoid this problem, the hum filter may be turned off if someone is present. One way to incorporate this is to activate the hum filter with the lamp off, and to turn off the hum filter if the lamp is on.

The vibrations are typically due to mechanical structures in the environment, such as the foil optics present in T-LED fixtures. These vibrations generally have the same characteristics. For this reason, the hum detector typically has to handle very similar vibrations. Instead of relying on the instantaneous capability of the hum detector to filter out these, the hum detector may also ignore those frequency bins that have experienced vibration problems at some point, for example, if the frequency at which the vibration occurs is high enough.

The buzz history may be used to more accurately identify the buzz. The motion detection algorithm runs at a certain rate, e.g., iteratively every 100 milliseconds, for example, and the motion detector may report motion/no motion. If a motion signal is observed, immediate reporting is generally not required. In an embodiment, there are multiple iterations, e.g., 4 iterations that may be 400ms, before reporting the observed signal. This reduces the chance of false positive motion signals. Although the buzzes start almost immediately, they hardly change after the start. This means that the history of the hum also has little change. Since there is a few frames of time, this time can be used to monitor the change in the hum history. If these changes are below the threshold, one can more confidently identify the signal as a vibration and report no motion. If the history does change above a certain threshold, motion may be reported.

Noise detection may be used in any product that utilizes a time-varying sensor signal. For example, noise detection has been found to be effective for doppler motion sensors. Noise detection may also be used for different types of sensors. For example, ambient light sensors are subject to similar noise sources, such as vibration noise, electrical noise, and the like.

Returning to fig. 1 a. The noise cancellation described herein removes or reduces the contribution to the motion component of the hum noise. If the motion sensor is less than ideal, for example, if the amplification or sensitivity in the I and Q channels is different, the reduction may degrade. Another problem may arise if the mixers of motion sensor 110 (e.g., mixers 530 and 540) are not exactly orthogonal. If the phase difference is not 90 degrees, it is possible to obtainβA(ω)|²The mirror image of the energy. Note that energy is typically calculated as the square of the amplitude.

Furthermore, if the loss of the mixed signal is small and accurate, the reduction is improved, as this results in the amplitudes of the two frequencies being closer to each other. Unfortunately, in embodiments, motion sensors may be less than ideal, resulting in a deviation between expected behaviors in the spectrum.

The noise cancellation unit 140 may be configured to correct defects in the motion sensor 110.

Fig. 5a schematically shows an example of an embodiment of the motion detector 101. The detector 101 may be the same as the detector 100 except for the addition of a correction term memory 164 and a modified noise cancellation unit 141. For example, the correction term memory 164 may store a correction factor β. The noise cancellation unit 141 may be configured to multiply one of the two motion components by the correction factor β before subtracting them. The correction factor β may be a real number, e.g., a usage magnitude. The correction factor β may be complex if a complex value (e.g., amplitude) is corrected.

One particularly advantageous way of calculating the difference between the motion components is to use the following equation:therein without a fluorineA(ω) | represents frequencyωThe magnitude of the motion component.

For example, assume that the choice of signal configuration is such that: a positive frequency corresponds to motion towards the sensor and a negative frequency corresponds to motion away from the sensor. If the signal amplification is slightly different between I and Q, the motion towards the sensor has a non-zero FFT magnitude not only at some positive frequency, but also a smaller non-zero FFT magnitude at the corresponding negative frequency, smaller here referring to a norm, since the magnitude is complex. As an example, assuming that the frequency conversion is obtained at ω =12, the values of a (12) and a (-12) are different, although they are known to correspond to the same motion, and therefore, one of them should be zero. The correction factor can then correct this. For example, assume that a (12) = 5+5iAnd A (-12) = 1-1i. In this case, β can be chosen to be |1-1i|/|5+5i|=1/5。

For ω =12, the above expression can now be calculated and read as:

note that the above expression is non-zero as expected, since it represents motion. Note that the reduction in the magnitude of the motion component is much smaller than the equationWith a reduced amount. In the former case, the value |5+5iForReduce rather than use |1-1 as in the latter caseiThe | is reduced. Note that the latter term is much larger. Thus, in the case of less than ideal sensors, the above equation reduces the unintentional elimination of real motion. Interestingly, however, in the case of vibration, | a (12) | = | a (-12) |, one still finds that the expression in the claims is equal to 0. In general, in the case of vibration, it is really about | a: (b)ω)|=|A(-ω) The situation because the unintentional contribution of excitation A (- ω) instead of A (ω) is about the same as the unintentional contribution of excitation to A (ω) instead of A (- ω).

The correction factors need not be linear or pseudo-like, e.g. the function G may be defined, e.g. a non-linear mapping. The function G may act directly on the complex values, for example, as follows:

instead of acting on complex values, the function G may act on magnitude values.

Fig. 5b schematically shows an example of an embodiment of the motion detector 102. The detector 102 may be the same as the detector 101 except that a correction term estimator 162 is added. The correction factor or function may be estimated and stored in the motion detector 101. For example, the correction factor may be estimated under laboratory conditions. Another approach is to estimate the correction factor during sensor use. For example, the correction term estimator 162 may be configured to estimate the correction factor during use of the motion sensor.

For example, the correction term estimator 162 may include an algorithm that determines that the motion component is likely to be caused by non-vibratory motion. For example, the algorithm may include comparing the magnitude of the motion component to a threshold on the assumption that true motion typically gives a large motion component. For example, the algorithm may verify that neighboring motion components are also elevated, as true motion is typically distributed over multiple motion components, e.g., a string of ± k consecutive motion components before and after a particular motion component should exceed another threshold to conclude that the particular motion component corresponds to motion. For example, k may be 2 or 3, or more, etc. If the signal is considered to be motion, e.g. determined by an algorithm, a correction factor may be estimated. For example, when using the above formula, assuming true motion at ω, it can be estimated that β = | A-ω)|/|A(ω) I, for example, if | A: (A:ω) | is greater than | A-ω)|。

Estimating the correction factor risks that the motion signal may be mixed with low amplitude vibrations. To eliminate this effect, a moving average line can be used that averages β over the last n observations.

Fig. 6 schematically shows an example of an embodiment of a motion detection method 700. The motion detection method (700) comprises:

-receiving (710) a motion signal from a motion sensor, the motion signal relating to motion in a motion sensor environment,

-signal processing (720) the motion signal to obtain a plurality of motion components, the motion components being related to a direction and a velocity of motion in the environment,

-eliminating (730) two motion components corresponding to motions having opposite directions among the motion components,

-detecting (740) motion in the environment from the motion components that are not eliminated.

Many different ways of performing the method are possible, as will be apparent to a person skilled in the art. For example, the steps may be performed in the order shown, but the order of the steps may also be changed or some of the steps may be performed in parallel. In addition, other method steps may be inserted between the steps. The intervening steps may represent modifications of the methods, such as those described herein, or may be unrelated to the methods. For example, steps 730, 740 may be performed at least partially in parallel. Furthermore, a given step may not have been completely completed before starting the next step.

Embodiments of the method may be performed using software that includes instructions for causing a processor system to perform method 700. The software may include only those steps taken by a particular sub-entity of the system. The software may be stored on a suitable storage medium such as a hard disk, floppy disk, memory, optical disk, etc. The software may be transmitted as signals along a wired or wireless or using a data network, such as the internet. The software may be downloaded on a server and/or used remotely. Embodiments of the method may be performed using a bitstream arranged to configure programmable logic, e.g., a Field Programmable Gate Array (FPGA), to perform the method.

It will be appreciated that the invention also extends to computer programs, particularly computer programs on or in a carrier, adapted for putting the invention into practice. The program may be in the form of source code, object code, a code intermediate source and object code such as partially compiled form, or in any other form suitable for use in the implementation of the embodiment of the method. Embodiments relating to computer program products include computer-executable instructions corresponding to each processing step of at least one of the methods. These instructions may be subdivided into subroutines and/or stored in one or more files that may be linked statically or dynamically. Another embodiment directed to a computer program product comprises computer executable instructions for each apparatus corresponding to at least one of the set forth systems and/or products.

Fig. 7a shows a computer-readable medium 1000 with a writeable section 1010, the writeable section 1010 comprising a computer program 1020, the computer program 1020 comprising instructions for causing a processor system to perform a motion detection method according to an embodiment. The computer program 1020 may be embodied on the computer readable medium 1000 as physical indicia or by magnetization of the computer readable medium 1000. However, any other suitable embodiment is also conceivable. Further, it should be understood that although the computer-readable medium 1000 is illustrated herein as an optical disk, the computer-readable medium 1000 may be any suitable computer-readable medium, such as a hard disk, solid state memory, flash memory, or the like. And may be non-recordable or recordable. The computer program 1020 comprises instructions for causing a processor system to perform the motion detection method.

Fig. 7b illustrates an exemplary hardware diagram 1100 for implementing a device according to an embodiment. As shown, the device 1100 includes a processor 1120, a memory 1130, a user interface 1140, a communication interface 1150, and a storage 1160 interconnected by one or more system buses 1110. It should be appreciated that this figure constitutes an abstraction in some respects and that the actual organization of the components of device 1100 may be more complex than that illustrated.

The processor 1120 may be any hardware device capable of executing instructions or otherwise processing data stored in the memory 1130 or storage 1160. Thus, the processor may comprise a microprocessor, Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), or other similar device. For example, the processor may be an Intel Core i7 processor, an ARM Cortex-R8 processor, or the like. In an embodiment, the processor may be an ARM Cortex M0.

Memory 1130 may include various memories such as, for example, an L1, L2, or L3 cache or a system memory. Thus, the memory 1130 may include Static Random Access Memory (SRAM), Dynamic RAM (DRAM), flash memory, Read Only Memory (ROM), or other similar storage devices. It will be apparent that in embodiments where the processor includes one or more ASICs (or other processing devices) that implement in hardware one or more of the functions described herein, software that is described as corresponding to such functions in other embodiments may be omitted.

User interface 1140 may include one or more devices capable of communicating with a user, such as an administrator. For example, user interface 1140 may include a display, mouse, and keyboard for receiving user commands. In some embodiments, user interface 1140 may include a command line interface or a graphical user interface that may be presented to a remote terminal through communication interface 1150.

Communication interface 1150 may include one or more devices used to enable communication with other hardware devices. For example, communication interface 1150 may include a Network Interface Card (NIC) configured to communicate according to an ethernet protocol. For example, communication interface 1150 may include an antenna, a connector, or both. Further, communication interface 1150 may implement a TCP/IP stack for communicating according to a TCP/IP protocol. Various alternative or additional hardware or configurations for communication interface 1150 will be apparent.

Storage 1160 may include one or more machine-readable storage media, such as Read Only Memory (ROM), Random Access Memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, or similar storage media. In various embodiments, the storage 1160 may store instructions for execution by the processor 1120 or data that may be manipulated by the processor 1120. For example, the storage 1160 may store a basic operating system 1161 for controlling various basic operations of the hardware 1100. For example, the memory may store instructions 1162 for signal processing the motion signal to obtain a plurality of motion components (e.g., converting the sensor signal to a frequency domain, obtaining a plurality of frequency bins), instructions 1163 for canceling two motion components corresponding to motions having opposite directions in the motion components (e.g., for reducing a magnitude of a first motion component associated with a first motion in response to a second motion component associated with a second motion opposite the first motion), and instructions 1164 for detecting motion in the environment from the motion components that are not canceled.

It will be appreciated that various information described as being stored in the memory device 1160 may additionally, or alternatively, be stored in the memory 1130. In this regard, the memory 1130 may also be considered to constitute a "storage device apparatus" and the storage 1160 may be considered to be a "memory". Various other arrangements will be apparent. Further, both the memory 1130 and the storage 1160 may be considered "non-transitory machine-readable media". As used herein, the term "non-transitory" will be understood to exclude transitory signals but include all forms of storage, including both volatile and non-volatile memory.

Although device 1100 is shown to include one each of the described components, various components may be duplicated in various embodiments. For example, the processor 1120 may include multiple microprocessors configured to independently perform the methods described herein or configured to perform the steps or subroutines of the methods described herein, such that the multiple processors cooperate to achieve the functions described herein. Further, where the device 1100 is implemented in a cloud computing system, the various hardware components may belong to separate physical systems. For example, the processor 1120 may include a first processor in a first server and a second processor in a second server.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative embodiments.

In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. Use of the verb "comprise" and its conjugations does not exclude the presence of elements or steps other than those stated in a claim. The article "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Expressions such as "at least one of them" when preceding a list of elements mean that all elements or any subset of elements are selected from the list. For example, the expression "at least one of A, B and C" should be understood to include only a, only B, only C, A and both B, both a and C, both B and C, or both A, B and C.

In the claims, reference signs placed between parentheses shall mean the reference signs in the drawings or formula for an embodiment illustrating the embodiment, thereby increasing the intelligibility of the claims. These reference signs should not be construed as limiting the claims.