阅读说明：本技术 一种雷达探测方法及相关装置 (Radar detection method and related device ) 是由 李强 于 2020-09-27 设计创作，主要内容包括：本申请实施例提供一种雷达测距方法及相关装置,该方法包括：获取第一信号,其中,所述第一信号为拍频信号中经低频抑制后的频域信号,所述拍频信号为基于调频连续波FMCW雷达发射的出射信号和接收的回波信号混频后得到的信号；在频域上对所述第一信号进行均值梯度计算,得到第二信号；根据第二信号中的峰值信号计算目标物的速度或距离中至少一项,采用本申请实施例,能够提高雷达探测结果的准确性,同时降低实现成本。(The embodiment of the application provides a radar ranging method and a related device, wherein the method comprises the following steps: acquiring a first signal, wherein the first signal is a frequency domain signal subjected to low-frequency suppression in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing an emergent signal transmitted by a frequency modulation continuous wave FMCW radar and a received echo signal; performing mean gradient calculation on the first signal in a frequency domain to obtain a second signal; at least one of the speed and the distance of the target object is calculated according to the peak signal in the second signal, and by adopting the embodiment of the application, the accuracy of the radar detection result can be improved, and the implementation cost is reduced.)

1. A radar ranging method, comprising:

acquiring a first signal, wherein the first signal is a frequency domain signal subjected to low-frequency suppression in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing an emergent signal transmitted by a frequency modulation continuous wave FMCW radar and a received echo signal;

performing mean gradient calculation on the first signal in a frequency domain to obtain a second signal; wherein the mean gradient calculation is to emphasize a difference between a signal value of each sample point in the first signal and signal values of surrounding sample points;

at least one of a velocity or a distance of the target object is calculated based on the peak signal in the second signal.

2. The method of claim 1, wherein the acquiring the first signal comprises:

carrying out low-frequency suppression on the beat frequency signal to obtain a first transition signal;

and carrying out discrete Fourier transform or short-time Fourier transform on the first transition signal to obtain a first signal.

3. The method of claim 1, wherein the acquiring the first signal comprises:

performing discrete Fourier transform or short-time Fourier transform on the beat frequency signal to obtain a second transition signal;

and suppressing the low frequency of the second transition signal to obtain a first signal.

4. The method according to any of claims 1-3, wherein the low frequency suppression is achieved by a digital tap filter or by a pre-set sequence parameter scaling process.

5. The method according to any one of claims 1-4, wherein the performing a mean gradient calculation on the first signal in the frequency domain to obtain a second signal comprises:

performing a target operation on a signal of each of a plurality of sampling points in the first signal on the frequency domain to obtain a sub-signal corresponding to each of the sampling points in the second signal;

wherein the target operation comprises: and subtracting the signal value of each sampling point from a reference value to obtain a sub-signal of each sampling point, wherein the reference value is an average value calculated according to the signal values of at least two other sampling points except each sampling point.

6. The method according to claim 5, characterized in that in the frequency domain, the interval between said at least two other sampling points and said each sampling point is greater than a first preset threshold and less than a second preset threshold.

7. The method according to claim 6, wherein the subsignals Δ S (k) for each sample point are as follows:

wherein S (k) isSignal value of each sample point, S (k-l)_p-n) is a frequency in the frequency domain which is smaller than said each sample point and is spaced apart from said each sample point by (I)_p+ n) signal values of other sampling points of the sampling points; s (k + l)_p+ n) is a frequency in the frequency domain greater than said each sample point and spaced from said each sample point by (l)_p+ n) signal values of other ones of the sampling points, l_pIs the first predetermined threshold,/_wAnd is the second preset threshold.

8. A signal processing apparatus, characterized by comprising:

the device comprises an acquisition unit, a frequency conversion unit and a processing unit, wherein the acquisition unit is used for acquiring a first signal, the first signal is a frequency domain signal subjected to low-frequency suppression in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing an emergent signal transmitted by a frequency modulation continuous wave FMCW radar and a received echo signal;

the optimization unit is used for carrying out mean gradient calculation on the first signal on a frequency domain to obtain a second signal;

and a calculating unit for calculating at least one of a speed or a distance of the target object according to the peak signal in the second signal.

9. The apparatus according to claim 8, wherein, in acquiring the first signal, the acquiring unit is specifically configured to:

carrying out low-frequency suppression on the beat frequency signal to obtain a first transition signal;

and carrying out discrete Fourier transform or short-time Fourier transform on the first transition signal to obtain a first signal.

10. The apparatus according to claim 8, wherein, in acquiring the first signal, the acquiring unit is specifically configured to:

performing discrete Fourier transform or short-time Fourier transform on the beat frequency signal to obtain a second transition signal;

and suppressing the low frequency of the second transition signal to obtain a first signal.

11. The apparatus according to any of claims 8-10, wherein the low frequency suppression is implemented by a digital tap filter, or the low frequency suppression is obtained by a preset sequence parameter scaling process.

12. The apparatus according to any one of claims 7 to 11, wherein a mean gradient calculation is performed on the first signal in a frequency domain to obtain a second signal, and the calculating unit is specifically configured to:

performing a target operation on a signal of each of a plurality of sampling points in the first signal on the frequency domain to obtain a sub-signal corresponding to each of the sampling points in the second signal;

wherein the target operation comprises: and subtracting the signal value of each sampling point from a reference value to obtain a sub-signal of each sampling point, wherein the reference value is an average value calculated according to the signal values of at least two other sampling points except each sampling point.

13. The apparatus according to claim 12, wherein the interval between the at least two other sampling points and the each sampling point is greater than a first preset threshold and less than a second preset threshold in the frequency domain.

14. The apparatus according to claim 12 or 13, wherein the sub-signal Δ s (k) of each sampling point is as follows:

wherein S (k) is the signal value of each sampling point, S (k-l)_p-n) is a frequency in the frequency domain which is smaller than said each sample point and is spaced apart from said each sample point by (I)_p+ n) other samplesThe signal value of (a); s (k + l)_p+ n) is a frequency in the frequency domain greater than said each sample point and spaced from said each sample point by (l)_p+ n) signal values of other ones of the sampling points, l_pIs the first predetermined threshold,/_wAnd is the second preset threshold.

15. A radar system comprising a memory for storing a computer program and a processor for invoking the computer program to implement the method of any one of claims 1-7.

16. A computer-readable storage medium, in which a computer program is stored which, when run on a processor, implements the method of any one of claims 1-7.

Technical Field

The invention relates to the technical field of radars, in particular to a radar detection method and a related device.

Background

An FMCW radar is a range finding device, which contains different sub-categories, for example, an fm continuous wave radar using radio waves is called FMCW RADAR, and for example, an fm continuous wave radar using laser light is called FMCW LIDAR. In fig. 1, the radar generates a radio frequency or laser signal that is frequency modulated, and divides the generated frequency modulated signal into two paths, wherein one path is used as a local reference signal (also called local oscillator signal), and the other path is emitted to a target object to be measured (also called reflector) and reflected by the surface of the target object to form an echo signal.

Fig. 2 illustrates the processing procedure of the FMCW radar for the reference signal and the echo signal, as shown in fig. 2 (a), and the thick line illustrates the frequency change of the frequency modulation signals of the transmission signal and the reference signal with time, wherein the signal frequency increases from low to high with time in the first half of the time, and the signal frequency decreases from high to low with time in the second half of the time. The thin lines illustrate the echo signals. The echo signal and the reference signal may output a beat signal through the mixer, and the frequency of the beat signal is the frequency difference between the reference signal and the echo signal, as shown in part (b) of fig. 2. Ideally, the beat signal has a fixed frequency (as shown in the dotted line), and as shown in fig. 2 (c), the frequency of the beat signal can be detected by performing frequency domain analysis (generally, FFT) on the beat signal, where the frequency has a one-to-one correspondence relationship with the distance and velocity of the target object, so that the velocity and distance information of the target object can be calculated from the frequency of the beat signal.

In FMCW radar, the frequency of the beat signal is proportional to the distance of the target (also known as the reflector), with distant objects corresponding to higher beat frequencies and objects in close proximity forming lower beat frequencies. A common problem in FMCW radars is the problem of low frequency crosstalk. This is typically due to energy leakage from the optics, forming a low frequency with the reference signal (also known as the local oscillator signal) forming a beat signal, as shown in fig. 3. Or the reflected light from an optical device such as a lens and a reference signal (also called local oscillator signal) form a low-frequency beat signal. The energy of these low frequency disturbances often far exceeds the energy of the actual echo. As shown in fig. 4, in the lower frequency part, the energy of the signal is far more than in the high frequency part. This can cause great difficulty in the detection of the actual signal. The objective of avoiding crosstalk is generally achieved by means of hardware isolation, such as isolating an optical path of a transmitted signal from an optical path of a received signal of an FMCW radar. However, the isolation achieved by hardware is limited, interference may still exist, and ensuring higher isolation may significantly increase hardware costs.

Disclosure of Invention

The embodiment of the application discloses a radar ranging method and a related device, which can improve the accuracy of radar detection results and reduce the implementation cost.

In a first aspect, an embodiment of the present application provides a radar ranging method, where the method includes:

acquiring a first signal, wherein the first signal is a frequency domain signal subjected to low-frequency suppression in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing an emergent signal transmitted by a frequency modulation continuous wave FMCW radar and a received echo signal;

performing mean gradient calculation on the first signal in a frequency domain to obtain a second signal; wherein the mean gradient calculation is to emphasize a difference between a signal value of each sample point in the first signal and signal values of surrounding sample points;

at least one of a velocity or a distance of the target object is calculated based on the peak signal in the second signal.

In the method, the frequency domain signal of the beat frequency signal is subjected to low-frequency suppression, so that the influence of low-frequency interference on the subsequent calculation of the speed or distance of the target object is reduced; in order to avoid that peak signals possibly existing in the low-frequency part are cut off due to low-frequency suppression, the peak signals possibly existing in the low-frequency part are highlighted in a mean value gradient calculation mode; therefore, the accuracy of the radar detection result calculated by the scheme of the embodiment of the application is high. In addition, the implementation of the embodiment of the application is completed by performing special processing on the signals, and the hardware structure of the radar is not required to be improved, so the implementation cost is low.

With reference to the first aspect, in a possible implementation manner of the first aspect, the acquiring the first signal includes:

carrying out low-frequency suppression on the beat frequency signal to obtain a first transition signal;

and carrying out discrete Fourier transform or short-time Fourier transform on the first transition signal to obtain a first signal.

With reference to the first aspect, or any one of the foregoing possible implementations of the first aspect, in a further possible implementation of the first aspect, the acquiring the first signal includes:

performing discrete Fourier transform or short-time Fourier transform on the beat frequency signal to obtain a second transition signal;

and suppressing the low frequency of the second transition signal to obtain a first signal.

With reference to the first aspect or any one of the foregoing possible implementations of the first aspect, in yet another possible implementation of the first aspect, the low frequency suppression is implemented by a digital tap filter, or the low frequency suppression is obtained by a preset sequence parameter scaling process.

With reference to the first aspect, or any one of the foregoing possible implementations of the first aspect, in a further possible implementation of the first aspect, the performing mean gradient calculation on the first signal in a frequency domain to obtain a second signal includes:

performing a target operation on a signal of each of a plurality of sampling points in the first signal on the frequency domain to obtain a sub-signal corresponding to each of the sampling points in the second signal;

wherein the target operation comprises: and subtracting the signal value of each sampling point from a reference value to obtain a sub-signal of each sampling point, wherein the reference value is an average value calculated according to the signal values of at least two other sampling points except each sampling point.

With reference to the first aspect or any one of the foregoing possible implementations of the first aspect, in a further possible implementation of the first aspect, on the frequency domain, an interval between the at least two other sampling points and each sampling point is greater than a first preset threshold and smaller than a second preset threshold.

With reference to the first aspect or any one of the foregoing possible implementations of the first aspect, in a further possible implementation of the first aspect, the sub-signal Δ s (k) of each sampling point is as follows:

wherein S (k) is the signal value of each sampling point, S (k-l)_p-n) is a frequency in the frequency domain which is smaller than said each sample point and is spaced apart from said each sample point by (I)_p+ n) signal values of other sampling points of the sampling points; s (k + l)_p+ n) is a frequency in the frequency domain greater than said each sample point and spaced from said each sample point by (l)_p+ n) signal values of other ones of the sampling points, l_pIs the first predetermined threshold,/_wAnd is the second preset threshold.

In a second aspect, an embodiment of the present application provides a signal processing apparatus, including:

the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a first signal, the first signal is a frequency domain signal subjected to low-frequency suppression in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing an emergent signal transmitted by a frequency modulation continuous wave FMCW radar and a received echo signal;

the optimization unit is used for carrying out mean gradient calculation on the first signal on a frequency domain to obtain a second signal; wherein the mean gradient calculation is to emphasize a difference between a signal value of each sample point in the first signal and signal values of surrounding sample points;

and a calculating unit for calculating at least one of a speed or a distance of the target object according to the peak signal in the second signal.

In the device, the frequency domain signal of the beat frequency signal is subjected to low-frequency suppression, so that the influence of low-frequency interference on the speed or distance of a subsequently calculated target object is reduced; in order to avoid that peak signals possibly existing in the low-frequency part are cut off due to low-frequency suppression, the peak signals possibly existing in the low-frequency part are highlighted in a mean value gradient calculation mode; therefore, the accuracy of the radar detection result calculated by the scheme of the embodiment of the application is high. In addition, the implementation of the embodiment of the application is completed by performing special processing on the signals, and the hardware structure of the radar is not required to be improved, so the implementation cost is low.

With reference to the second aspect, in a possible implementation manner of the second aspect, in acquiring the first signal, the acquiring unit is specifically configured to:

carrying out low-frequency suppression on the beat frequency signal to obtain a first transition signal;

and carrying out discrete Fourier transform or short-time Fourier transform on the first transition signal to obtain a first signal.

With reference to the second aspect, or any one of the foregoing possible implementations of the second aspect, in yet another possible implementation of the second aspect, in acquiring the first signal, the acquiring unit is specifically configured to:

performing discrete Fourier transform or short-time Fourier transform on the beat frequency signal to obtain a second transition signal;

and suppressing the low frequency of the second transition signal to obtain a first signal.

With reference to the second aspect or any one of the foregoing possible implementations of the second aspect, in yet another possible implementation of the second aspect, the low frequency suppression is implemented by a digital tap filter, or the low frequency suppression is obtained by a preset sequence parameter scaling process.

With reference to the second aspect, or any one of the foregoing possible implementations of the second aspect, in a further possible implementation of the second aspect, a mean gradient calculation is performed on the first signal in a frequency domain to obtain a second signal, where the calculation unit is specifically configured to:

performing a target operation on a signal of each of a plurality of sampling points in the first signal on the frequency domain to obtain a sub-signal corresponding to each of the sampling points in the second signal;

wherein the target operation comprises: and subtracting the signal value of each sampling point from a reference value to obtain a sub-signal of each sampling point, wherein the reference value is an average value calculated according to the signal values of at least two other sampling points except each sampling point.

With reference to the second aspect or any one of the foregoing possible implementations of the second aspect, in a further possible implementation of the second aspect, in the frequency domain, an interval between the at least two other sampling points and each of the sampling points is greater than a first preset threshold and smaller than a second preset threshold.

With reference to the second aspect or any one of the foregoing possible implementations of the second aspect, in a further possible implementation of the second aspect, the sub-signal Δ s (k) of each sampling point is as follows:

wherein S (k) is the signal value of each sampling point, S (k-l)_p-n) is a frequency in the frequency domain which is smaller than said each sample point and is spaced apart from said each sample point by (I)_p+ n) signal values of other sampling points of the sampling points; s (k + l)_p+ n) is a frequency in the frequency domain greater than said each sample point and spaced from said each sample point by (l)_p+ n) signal values of other ones of the sampling points, l_pIs the first predetermined threshold,/_wAnd is the second preset threshold.

In a third aspect, an embodiment of the present application provides a radar system, which includes a memory and a processor, where the memory is used to store a computer program, and the processor is used to invoke the computer program to implement the method described in the first aspect or any possible implementation manner of the first aspect.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, in which a computer program is stored, which, when run on a processor, implements the method described in the first aspect or any one of the possible implementation manners of the first aspect.

Drawings

The drawings used in the embodiments of the present application are described below.

Fig. 1 is a schematic diagram of a laser radar provided in an embodiment of the present application;

FIG. 2 is a schematic diagram of a beat signal provided by an embodiment of the present application;

FIG. 3 is a schematic view of a low frequency interference generating scenario of an optical device according to an embodiment of the present disclosure;

FIG. 4 is a diagram illustrating the effect of low frequency interference according to an embodiment of the present application;

fig. 5 is a schematic diagram of an architecture of a laser radar system according to an embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a beat signal generated by a triangular wave according to an embodiment of the present disclosure;

fig. 7 is a schematic flowchart of a radar detection method according to an embodiment of the present application;

fig. 8 is a schematic flowchart of another radar detection method provided in an embodiment of the present application;

fig. 9 is a schematic diagram illustrating an operation principle of a digital tap filter according to an embodiment of the present application;

fig. 10 is a schematic diagram illustrating the effect of low frequency suppression provided by an embodiment of the present application;

fig. 11 is a schematic flowchart of another radar detection method provided in an embodiment of the present application;

fig. 12 is a schematic structural diagram of a signal processing apparatus according to an embodiment of the present application.

Detailed Description

The embodiments of the present application will be described below with reference to the drawings.

Laser radar in the embodiment of the application can be applied to various fields such as intelligent transportation, autopilot, atmospheric environment monitoring, geographical mapping, unmanned aerial vehicle, can accomplish functions such as distance measurement, speed measurement, target tracking, formation of image discernment.

Referring to fig. 5, fig. 5 is a schematic structural diagram of a lidar system according to an embodiment of the present disclosure, where the lidar system is configured to detect information of a target 505, and the lidar system includes:

the Laser 501, which may be a Tunable Laser (TL), is used to generate a Laser signal, which may be a chirped Laser signal, and the modulation waveform of the Laser signal frequency may be a sawtooth wave, a triangular wave, or other waveform.

The splitter device 502 is configured to split laser light generated by the laser 501 to obtain a transmit signal and a Local Oscillator (LO), where the LO is also referred to as a reference signal. Optionally, a collimating lens 500 may be disposed between the laser 501 and the branching device, and the lens 500 is used for beam shaping the laser signal transmitted to the branching device 502.

A collimator 503 for coupling the transmit signal into the scanner 504 with maximum efficiency.

The scanner 504, also called as a 2D scanning mechanism, is configured to emit the emission signal at a certain angle, and after the emission signal is emitted, the emission signal is reflected by the target 505 to form an echo signal; the scanner 504 is then also configured to receive the echo signals, which are combined with the local oscillator signal at a mixer 510 after passing through corresponding optics, such as a mirror 506 (optional) and a receive optic 508 (optional).

And the mixer 510 is configured to perform frequency mixing processing on the local oscillation signal and the echo signal to obtain a beat signal.

A detector 520 for extracting the beat signal from the mixer. For example, the detector 520 may be a balanced detector (BPD).

An Analog Digital Converter (ADC) 511 is used for sampling the beat frequency signal, and this sampling is essentially the process of converting the Analog signal into a digital signal.

And a processor 512, which may include devices with computing power, such as a Digital Signal Processor (DSP), a Central Processing Unit (CPU), an Accelerated Processing Unit (APU), an image processing unit (GPU), a microprocessor or a microcontroller, for example, and which is not shown in the drawings, and is configured to process the sampled beat frequency signal to obtain information, such as speed and distance of the target object.

In the embodiment of the present application, the target 505 is also referred to as a reflector, the target 505 may be any object in the scanning direction of the scanner 504, for example, a person, a mountain, a vehicle, a tree, a bridge, etc., and fig. 5 illustrates a vehicle as an example.

In the embodiment of the present application, the operation of processing the beat signals obtained by sampling to obtain the information of the speed, the distance, and the like of the target object may be performed by one or more processors 512, for example, by one or more DSPs, or may be performed by one or more processors 512 in combination with other devices, for example, by one DSP in combination with one or more Central Processing Units (CPUs). The processing of the beat signal by the processor 512 may be realized by calling a computer program stored in a computer-readable storage medium, which includes but is not limited to a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a portable read-only memory (CD-ROM), and may be configured in the processor 512 or independent of the processor 512.

In the embodiment of the present application, some of the above-mentioned devices may be single-part or multiple-part, for example, the laser 501 may be one or multiple, and in the case of one laser 501, the one laser 501 may alternately emit a laser signal with a positive slope and a laser signal with a negative slope in the time domain; when there are two lasers 501, one of which emits a laser signal with a positive slope and the other of which emits a laser signal with a negative slope, the two lasers 501 may emit laser signals synchronously.

As shown in fig. 6, for example, the modulation waveform of the laser signal frequency is triangular chirp, and the echo signal passes through a flight timeAnd then mixing the frequency with a local oscillator signal LO, wherein the flight time is the time from the emergence of a transmitting signal divided by the laser signal to the return of an echo signal, the echo signal is constant within a certain time with a beat frequency signal generated by the local oscillator signal after the flight time, the distance and speed information of a target object can be accurately reflected, and the time is the beat frequency time. The beat signal needs to include a beat frequency f corresponding to a positive slope₁And a beat frequency f corresponding to a negative slope₂Frequency spectrum f related to the velocity of the object_{Speed of rotation}Can be expressed as f_{Speed of rotation}＝(f₁-f₂) /2, frequency f related to distance of target_{Distance between two adjacent plates}Can be expressed as f_{Distance between two adjacent plates}＝(f₁+f₂)/2. To obtain f_{Speed of rotation}And f_{Distance between two adjacent plates}Then the distance of the target object (and the laser radar) and the moving speed of the target object can be calculated.

Referring to fig. 7, fig. 7 is a radar detection method provided by an embodiment of the present application, which may be implemented based on components in the laser radar system shown in fig. 5, and some operations in the following description are performed by a signal processing apparatus, which may be the processor 512 or an apparatus in which the processor 512 is disposed, for example, a laser radar system in which the processor 512 is disposed or a module in the laser radar system, and the method includes, but is not limited to, the following steps:

step S701: the signal processing device acquires a first signal.

Specifically, the first signal is a frequency domain signal subjected to low-frequency suppression in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing an outgoing signal transmitted by a frequency-modulated continuous wave FMCW radar and a received echo signal.

The low-frequency suppression is to suppress energy of a low-frequency part in a signal (i.e. to weaken the energy of the low-frequency part), and there are many specific implementation means of the low-frequency suppression, for example, the low-frequency suppression can be implemented by a digital tap filter; for another example, the method can also be implemented by preset sequence parameter scaling; the present application is not limited to specific means for realizing this.

In one mode, as shown in fig. 8, the acquiring the first signal may specifically include the following operations:

firstly, the beat frequency signal is subjected to low-frequency suppression to obtain a first transition signal. For example, the beat signal is suppressed in the low frequency component by a digital tap filter including a delay Z, and the operation principle when the digital tap filter suppresses the low frequency is shown in fig. 9^-1Multiplier, and method for producing the sameSum adderAssume that the filter coefficient of the digital tap filter is [ h ]₁,h₂,……,h_N]Where N is the order of the digital tap filter (fig. 9 illustrates that N is equal to 3), the first transition signal s' (N) is obtained by equation 1-1.

In formula 1-1, s (n) is the input beat frequency signal, and is filtered by the filter coefficient [ h ] of the digital tap filter₁,h₂,……,h_N]Is chosen such that the low frequency part of the beat signal s (n) can be suppressed and thus the low frequency part of the resulting first transition signal s' (n) is of lower energy.

Then, the first transition signal is subjected to discrete fourier transform (FFT) or short-time fourier transform to obtain a first signal.

Optionally, the first transition signal may be converted into a frequency-domain signal by a discrete fourier transform (FFT), where the frequency-domain signal is the first signal, and an expression of the discrete fourier transform (FFT) is shown in formula 1-2:

S(k)＝F(s′(n)) 1-2

in the formula 1-2, F () represents fourier transform, and s (k) is a frequency signal obtained by performing discrete fourier transform FFT on the first transition signal s' (n), i.e., the aforementioned first signal.

Optionally, the first transition signal may be converted into a time-frequency two-dimensional signal through short-time fourier transform (STFT), where the time-frequency two-dimensional signal is the first signal, and an expression of the short-time fourier transform (STFT) is shown in formulas 1 to 3:

S(k)＝STFT(s′(n)) 1-3

in the formulas 1 to 3, STFT () represents a short-time fourier transform, and s (k) is a time-frequency two-dimensional spectrum obtained by performing the short-time fourier transform STFT on the first transition signal s' (n), that is, the first signal.

The upper part of fig. 10 illustrates the first signal after the discrete fourier transform FFT, and it can be seen that the amplitude of the low frequency part of the first signal is low because the amplitude of the low frequency signal is suppressed by the previous low frequency suppression operation.

In another mode, as shown in fig. 11, the acquiring the first signal may specifically include the following operations:

firstly, discrete Fourier transform or short-time Fourier transform is carried out on the beat frequency signal to obtain a second transition signal.

Optionally, the beat signal may be converted into a frequency-domain signal by a discrete fourier transform (FFT), where the frequency-domain signal is the second transition signal, and an expression of the discrete fourier transform (FFT) is shown in formulas 1 to 4:

S(k)′＝F(s(n)) 1-4

in equations 1-4, F () represents fourier transform, and s (k)' is a frequency signal obtained by performing discrete fourier transform FFT on the beat signal s (n), i.e. the aforementioned second transition signal.

Optionally, the beat signal may be converted into a time-frequency two-dimensional signal through short-time fourier transform (STFT), where the time-frequency two-dimensional signal is the second transition signal, and an expression of the short-time fourier transform (STFT) is shown in formulas 1 to 5:

S(k)′＝STFT(s(n)) 1-5

in the formulas 1 to 5, STFT () represents a short-time fourier transform, and s (k)' is a time-frequency two-dimensional spectrum obtained by short-time fourier transform STFT on the beat signal s (n), that is, the aforementioned second transition signal.

And then, carrying out low-frequency suppression on the second transition signal to obtain a first signal.

For example, this can be achieved by using a frequency-domain equalizer to multiply the frequency-domain sequence of the second transition signal by a preset sequence parameter, which has a lower coefficient in the low frequency part and a higher coefficient in the high frequency part, so as to achieve low frequency suppression, as shown in equations 1-6.

S(k)＝E(n)*S(k)′ 1-6

In the formulas 1-6, s (k) is the first signal, s (k)' is the second transition signal, and e (n) is the predetermined sequence number parameter.

Step S702: and the signal processing device performs mean gradient calculation on the first signal on a frequency domain to obtain a second signal.

Specifically, after the foregoing low-frequency suppression, although the interference signal can be suppressed, the amplitude of the low-frequency signal may be suppressed too deeply, thereby causing gain imbalance of the entire frequency band. As can be seen from the upper part signal of fig. 10, in the low frequency part, the signal amplitude is lower than that in the high frequency part as a whole, because the energy of the low frequency part is suppressed as a whole when the low frequency is suppressed.

The gain imbalance of the whole frequency band may occur in a case that a peak originally exists in the low frequency part, but because of the low frequency suppression, the amplitude of the peak of the low frequency part is lower than that of the non-peak of the high frequency part, that is, the true peak is masked, and thus the subsequent calculation of the velocity and/or distance based on the peak is inaccurate. In order to solve the problem that the real peak may be masked, the present application particularly proposes a signal optimization way of calculating a mean gradient, where the mean gradient calculation is used to highlight the difference between the signal value of each sampling point in the first signal and the signal values of surrounding sampling points; the specific principle is as follows:

performing a target operation on a signal of each of a plurality of sampling points in the first signal on the frequency domain to obtain a sub-signal corresponding to each of the sampling points in the second signal;

wherein the target operation comprises: and subtracting the signal value of each sampling point from a reference value to obtain a sub-signal of each sampling point, wherein the reference value is an average value calculated according to the signal values of at least two other sampling points except each sampling point.

Optionally, in the frequency domain, the interval between the at least two other sampling points and each sampling point is greater than a first preset threshold and smaller than a second preset threshold. It should be noted that, the reference to be smaller than the second preset threshold is to make each sampling point perform comparison calculation with nearby sampling points, because too far away from each sampling point, the comparison value is lost; however, the other sampling points may not be too close to each of the sampling points, because too close sampling points may have the same problem as each of the sampling points, for example, the interference is severe, and thus, when the other sampling points are too close to each of the sampling points, the calculated sub-signals may be unstable. Therefore, the first preset threshold and the second preset threshold are introduced, so that other sampling points used in the calculation of the sub-signals are close to each sampling point, but not too close.

For ease of understanding, the following provides a method for calculating the sub-signal Δ s (k) of each sampling point as follows:

wherein S (k) is the signal value of each sampling point, S (k-l)_p-n) is a frequency in the frequency domain which is smaller than said each sample point and is spaced apart from said each sample point by (I)_p+ n) signal values of other sampling points of the sampling points; s (k + l)_p+ n) is a frequency in the frequency domain greater than said each sample point and spaced from said each sample point by (l)_p+ n) signal values of other ones of the sampling points, l_pIs the firstA predetermined threshold value,/_wAnd is the second preset threshold.

As shown in fig. 10, the second signal obtained by performing the mean gradient calculation on the upper portion signal (i.e., the first signal) of fig. 10 is the lower portion signal (i.e., the second signal) of fig. 10, and it can be seen from the lower portion signal that even if the low frequency portion is suppressed, the peak thereof is clearly prominent, and the problem that the peak of the low frequency portion is masked does not substantially occur.

Step S703: the signal processing device calculates at least one of a speed or a distance of the target object based on the peak signal in the second signal.

Alternatively, as shown in fig. 2, the transmitted FMCW signal is divided into an up-chirp signal (chirp) and a down-chirp signal (chirp). Through the operation, a peak signal can be obtained at the upper chirp and the lower chirp respectively, the frequency positions of the two peak signals are found, and the two found frequency domain positions are respectively f_uAnd f_dIf the chirp rate of the recorded FMCW is α, then:

calculating the distance from the target object to the radar asWhere c is the speed of light.

Calculating the moving speed of the target object asWhere λ is the wavelength of the emitted laser light.

In the method depicted in fig. 7, the frequency domain signal of the beat signal is subjected to low frequency suppression, so as to reduce the influence of low frequency interference on the subsequently calculated target object speed or distance; in order to avoid that peak signals possibly existing in the low-frequency part are cut off due to low-frequency suppression, the peak signals possibly existing in the low-frequency part are highlighted in a mean value gradient calculation mode; therefore, the accuracy of the radar detection result calculated by the scheme of the embodiment of the application is high. In addition, the implementation of the embodiment of the application is completed by performing special processing on the signals, and the hardware structure of the radar is not required to be improved, so the implementation cost is low.

The method of the embodiments of the present application is set forth above in detail and the apparatus of the embodiments of the present application is provided below.

Referring to fig. 12, fig. 12 is a schematic structural diagram of a signal processing apparatus 120 according to an embodiment of the present disclosure, where the apparatus 120 may be the laser radar system, or a processor in the laser radar system, or a related device deployed in the laser radar system. The signal processing apparatus 120 may include an acquisition unit 1201, an optimization unit 1202, and a calculation unit 1203, wherein the respective units are described in detail below.

An obtaining unit 1201, configured to obtain a first signal, where the first signal is a frequency domain signal in a beat signal after low frequency suppression, and the beat signal is a signal obtained by mixing an outgoing signal transmitted by a frequency modulated continuous wave FMCW radar and a received echo signal;

an optimizing unit 1202, configured to perform mean gradient calculation on the first signal in a frequency domain to obtain a second signal; wherein the mean gradient calculation is to emphasize a difference between a signal value of each sample point in the first signal and signal values of surrounding sample points;

a calculating unit 1203, configured to calculate at least one of a speed and a distance of the target object according to the peak signal in the second signal.

In the scheme, the frequency domain signal of the beat frequency signal is subjected to low-frequency suppression, so that the influence of low-frequency interference on the speed or distance of a subsequently calculated target object is reduced; in order to avoid that peak signals possibly existing in the low-frequency part are cut off due to low-frequency suppression, the peak signals possibly existing in the low-frequency part are highlighted in a mean value gradient calculation mode; therefore, the accuracy of the radar detection result calculated by the scheme of the embodiment of the application is high. In addition, the implementation of the embodiment of the application is completed by performing special processing on the signals, and the hardware structure of the radar is not required to be improved, so the implementation cost is low.

In an optional scheme, in terms of acquiring the first signal, the acquiring unit 1201 is specifically configured to:

carrying out low-frequency suppression on the beat frequency signal to obtain a first transition signal;

and carrying out discrete Fourier transform or short-time Fourier transform on the first transition signal to obtain a first signal.

In another optional scheme, in terms of acquiring the first signal, the acquiring unit 1201 is specifically configured to:

performing discrete Fourier transform or short-time Fourier transform on the beat frequency signal to obtain a second transition signal;

and suppressing the low frequency of the second transition signal to obtain a first signal.

In yet another alternative, the low frequency suppression is implemented by a digital tap filter, or the low frequency suppression is obtained by a preset sequence parameter scaling process.

In another alternative, a mean gradient calculation is performed on the first signal in the frequency domain to obtain a second signal, and the calculating unit 1203 is specifically configured to:

performing a target operation on a signal of each of a plurality of sampling points in the first signal on the frequency domain to obtain a sub-signal corresponding to each of the sampling points in the second signal;

wherein the target operation comprises: and subtracting the signal value of each sampling point from a reference value to obtain a sub-signal of each sampling point, wherein the reference value is an average value calculated according to the signal values of at least two other sampling points except each sampling point.

In yet another alternative, in the frequency domain, the interval between the at least two other sampling points and each sampling point is greater than a first preset threshold and less than a second preset threshold.

In yet another alternative, the sub-signal Δ s (k) of each sampling point is as follows:

wherein S (k) is the signal value of each sampling point, S (k-l)_p-n) is a frequency in the frequency domain which is smaller than said each sample point and is spaced apart from said each sample point by (I)_p+ n) signal values of other sampling points of the sampling points; s (k + l)_p+ n) is a frequency in the frequency domain greater than said each sample point and spaced from said each sample point by (l)_p+ n) signal values of other ones of the sampling points, l_pIs the first predetermined threshold,/_wAnd is the second preset threshold.

It should be noted that the implementation of each unit may also correspond to the corresponding description of the method embodiment shown in fig. 7. The above units may be implemented by software, hardware, or a combination of the two, the hardware may be the processor described above, and the software may include a driver code running on the processor, which is not limited in this embodiment.

The embodiment of the present application further provides a chip system, where the chip system includes at least one processor, a memory and an interface circuit, where the memory, the interface circuit and the at least one processor are interconnected by a line, and the at least one memory stores instructions; the instructions, when executed by the processor, implement the method flow shown in fig. 7.

Embodiments of the present application also provide a computer-readable storage medium, which stores instructions that, when executed on a processor, implement the method flow illustrated in fig. 7.

Embodiments of the present application also provide a computer program product, which when executed on a processor implements the method flow illustrated in fig. 7.

In conclusion, the frequency domain signal of the beat frequency signal is subjected to low-frequency suppression, so that the influence of low-frequency interference on the speed or distance of a subsequently calculated target object is reduced; in order to avoid that peak signals possibly existing in the low-frequency part are cut off due to low-frequency suppression, the peak signals possibly existing in the low-frequency part are highlighted in a mean value gradient calculation mode; therefore, the accuracy of the radar detection result calculated by the scheme of the embodiment of the application is high. In addition, the implementation of the embodiment of the application is completed by performing special processing on the signals, and the hardware structure of the radar is not required to be improved, so the implementation cost is low.

One of ordinary skill in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by hardware related to instructions of a computer program, which may be stored in a computer-readable storage medium, and when executed, may include the processes of the above method embodiments. And the aforementioned storage medium includes: various media capable of storing program codes, such as ROM or RAM, magnetic or optical disks, etc.