Patent Description:
A frequency modulated continuous wave (frequency modulated continuous wave, FMCW) radar is a ranging device, and the FMCW radar has different subdivided types. For example, a frequency modulated continuous wave radar using radio waves is referred to as FMCW RADAR. For another example, a frequency modulated continuous wave radar using laser light is referred to as FMCW LIDAR. An FMCW radar of any type includes a structure shown in <FIG>. In <FIG>, the radar generates a radio frequency or laser signal on which frequency modulation is performed, and divides the generated frequency modulated signal into two channels. One channel is used as a local reference signal (also referred to as a local oscillator signal), and the other channel is emitted to a detected target object (also referred to as a reflector) and reflected by a surface of the target object to form an echo signal.

<FIG> shows a process of processing a reference signal and an echo signal by an FMCW radar. As shown in (a) in <FIG>, a thick line indicates that a frequency of the frequency modulated signal of a transmitted signal and the reference signal changes over time. In the first half of time, the signal frequency increases from low to high over time, and in the second half of the time, the signal frequency decreases from high to low over time. A thin line indicates the echo signal. A beat frequency signal may be output after the echo signal and the reference signal passing through a frequency mixer. A frequency of the beat frequency signal is a frequency difference between the reference signal frequency and the echo signal frequency, as shown in (b) in <FIG>. In an ideal condition, the beat frequency signal has a fixed frequency (as shown by a part between dashed-lines in the figure). As shown in (c) in <FIG>, the frequency of the beat frequency signal may be detected by performing frequency domain analysis (usually FFT) on the beat frequency signal. The frequency is in a one-to-one correspondence with a distance and a speed of the target object. Therefore, speed and distance information of the target object may be calculated based on the frequency of the beat frequency signal.

In the FMCW radar, the frequency of the beat frequency signal is proportional to the distance of the target object (also referred to as a reflector). A long-distance object corresponds to a higher beat frequency, and a short-distance object forms a lower beat frequency. A common problem in the FMCW radar is low frequency crosstalk. As shown in <FIG>, the low frequency crosstalk is generally caused by energy leakage of an optical device, and a low frequency is formed with a reference signal (also referred to as a local oscillator signal) to form a beat frequency signal. Alternatively, reflected light of an optical device such as a lens and a reference signal (also referred to as a local oscillator signal) form a low frequency beat frequency signal. Energy of low frequency interference tends to far exceed energy of an actual echo signal. As shown in <FIG>, in a relatively low frequency part, energy of a signal far exceeds that of a high frequency part. This brings great difficulties to detection of an actual signal. Currently, crosstalk is generally avoided in a hardware isolation manner, for example, an optical path for isolating a signal transmitted by the FMCW radar and an optical path for isolating a signal received by the FMCW radar. However, isolation achieved by hardware is limited, and interference still exists. In addition, ensuring relatively high isolation significantly increases hardware costs.

Embodiments of this application disclose a radar ranging method and a related apparatus, to improve accuracy of a radar detection result and reduce implementation costs.

According to a first aspect, an embodiment of this application provides a radar ranging method. The method includes:.

In the foregoing method, low frequency suppression is performed on the frequency domain signal of the beat frequency signal, so as to reduce influence of low frequency interference on subsequent calculation of the speed or distance of the target object. To prevent a peak signal that may exist in the low frequency part from being clipped due to low frequency suppression, the peak signal that may exist in the low frequency part is further highlighted by performing mean gradient calculation. Therefore, accuracy of a radar detection result calculated by using the solution in this embodiment of this application is relatively high. In addition, implementation of this embodiment of this application is completed by performing special processing on a signal, and a hardware structure of a radar does not need to be improved. Therefore, implementation costs are relatively low.

With reference to the first aspect, in a possible implementation of the first aspect, the obtaining a first signal includes:.

With reference to the first aspect or any one of the foregoing possible implementations of the first aspect, in still another possible implementation of the first aspect, the obtaining a first signal includes:.

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

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

With reference to the first aspect or any one of the foregoing possible implementations of the first aspect, in still another possible implementation of the first aspect, in frequency domain, a spacing between the at least two other sampling points and the sampling point is greater than a first preset threshold and less than a second preset threshold.

With reference to the first aspect or any one of the foregoing possible implementations of the first aspect, in still another possible implementation of the first aspect, the sub-signal ΔS(k) of each sampling point is as follows: <MAT> where S(k) is a signal value of each sampling point, S(k - lp - n) is a signal value of another sampling point that has a frequency less than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, S(k + lp + n) is a signal value of another sampling point that has a frequency greater than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, lp is the first preset threshold, and lw is the second preset threshold.

According to a second aspect, an embodiment of this application provides a signal processing apparatus. The apparatus includes:.

In the foregoing apparatus, low frequency suppression is performed on the frequency domain signal of the beat frequency signal, so as to reduce influence of low frequency interference on subsequent calculation of the speed or distance of the target object. To prevent a peak signal that may exist in the low frequency part from being clipped due to low frequency suppression, the peak signal that may exist in the low frequency part is further highlighted by performing mean gradient calculation. Therefore, accuracy of a radar detection result calculated by using the solution in this embodiment of this application is relatively high. In addition, implementation of this embodiment of this application is completed by performing special processing on a signal, and a hardware structure of a radar does not need to be improved. Therefore, implementation costs are relatively low.

With reference to the second aspect, in a possible implementation of the second aspect, in terms of obtaining the first signal, the obtaining unit is specifically configured to:.

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

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

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

With reference to the second aspect or any one of the foregoing possible implementations of the second aspect, in still another possible implementation of the second aspect, in frequency domain, a spacing between the at least two other sampling points and the sampling point is greater than a first preset threshold and less than a second preset threshold.

With reference to the second aspect or any one of the foregoing possible implementations of the second aspect, in still another possible implementation of the second aspect, the sub-signal ΔS(k) of each sampling point is as follows: <MAT> where S(k) is a signal value of each sampling point, S(k - lp - n) is a signal value of another sampling point that has a frequency less than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, S(k + lp + n) is a signal value of another sampling point that has a frequency greater than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, lp is the first preset threshold, and lw is the second preset threshold.

According to a third aspect, an embodiment of this application provides a radar system. The radar system includes a memory and a processor. The memory is configured to store a computer program, and the processor is configured to invoke the computer program to implement the method described in any one of the first aspect or the possible implementations of the first aspect.

According to a fourth aspect, an embodiment of this application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program; and when the computer program is run on a processor, the method according to any one of the first aspect or the possible implementations of the first aspect is implemented.

The following describes the accompanying drawings used in embodiments of this application.

The following describes embodiments of this application with reference to the accompanying drawings in the embodiments of this application.

A lidar in this embodiment of this application can be applied to various fields such as intelligent transportation, autonomous driving, atmospheric environment monitoring, geographic surveying and mapping, and unmanned aerial vehicle, and can complete functions such as distance measurement, speed measurement, target tracking, and imaging recognition.

<FIG> is a schematic diagram of a structure of a lidar system according to an embodiment of this application. The lidar system is configured to detect information about a target object <NUM>, and the lidar system includes:.

In this embodiment of this application, the target object <NUM> is also referred to as a reflector. The target object <NUM> may be any object in a scanning direction of the scanner <NUM>, for example, may be a person, a mountain, a vehicle, a tree, or a bridge. <FIG> uses a vehicle as an example for illustration.

In this embodiment of this application, an operation of processing a beat frequency signal obtained by sampling to obtain information such as a speed and a distance of the target object may be completed by one or more processors <NUM>, for example, by one or more DSPs, or may be completed by one or more processors <NUM> in combination with another component, for example, a DSP in combination with one or more central processing units CPUs. When processing the beat frequency signal, the processor <NUM> may specifically invoke a computer program stored in a computer-readable storage medium. The computer-readable storage medium includes but is not limited to a random access memory (random access memory, RAM), a read-only memory (read-only memory, ROM), an erasable programmable read-only memory (erasable programmable read-only memory, EPROM) or a compact disc read-only memory (compact disc read-only memory, CD-ROM). The computer-readable storage medium may be disposed on the processor <NUM>, or may be independent of the processor <NUM>.

In this embodiment of this application, there may be one or more components mentioned above. For example, there may be one or more lasers <NUM>. When there is one laser <NUM>, the laser <NUM> may alternately transmit a laser signal with a positive slope and a laser signal with a negative slope in time domain. When there are two lasers <NUM>, one laser <NUM> transmits a laser signal with a positive slope, and the other laser <NUM> transmits a laser signal with a negative slope, and the two lasers <NUM> may synchronously transmit laser signals.

As shown in <FIG>, for example, a modulation waveform of a frequency of the laser signal is triangular wave linear frequency modulation. After a period of time of flight, an echo signal is mixed with a local oscillator signal LO. This period of time of flight is a time from a moment at which a transmitted signal divided from the laser signal starts to be emitted to a moment at which the echo signal returns. After the time of flight, a beat frequency signal generated by the echo signal and the local oscillator signal is constant in a period of time, can accurately reflect information about a distance and a speed of the target object. This period of time is a beat frequency time. The beat frequency signal needs to include a beat frequency f<NUM> corresponding to a positive slope and a beat frequency f<NUM> corresponding to a negative slope, a spectrum fspeed related to the speed of the target object may be represented as fspeed = (f<NUM> - f<NUM>)/<NUM>, and a frequency fdistance related to the distance of the target object may be represented as fdistance = (f<NUM> + f<NUM>)/<NUM>. After fspeed and fdistance are obtained, the distance of the target object (to the lidar) and the moving speed of the target object may be calculated.

<FIG> shows a radar detection method according to an embodiment of this application. The method may be implemented based on components in the lidar system shown in <FIG>. Some operations in subsequent descriptions are completed by a signal processing apparatus, and the signal processing apparatus may be the foregoing processor <NUM>, or an apparatus in which the foregoing processor <NUM> is deployed. For example, a lidar system in which the foregoing processor <NUM> is deployed or a module in the lidar system. The method includes but is not limited to the following steps.

Step S701: A signal processing apparatus obtains a first signal.

Specifically, the first signal is a frequency domain signal obtained after low frequency suppression is performed in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing a 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 (that is, weaken the energy of the low frequency part). There are many specific implementation manners to implement the low frequency suppression. For example, the low frequency suppression may be implemented by using a digital tap filter. For another example, the low frequency suppression may be implemented by performing scaling processing on a preset sequence parameter. A specific implementation is not limited in this application.

In a manner, as shown in <FIG>, the obtaining a first signal may specifically include the following operations.

First, low frequency suppression is performed on the beat frequency signal to obtain a first transition signal. For example, a digital tap filter is used to suppress a low frequency component of a beat frequency signal. A working principle of the digital tap filter when the digital tap filter suppresses a low frequency is shown in <FIG>. The digital tap filter includes a delayer Z-<NUM>, a multiplier ⓧ, and an adder⊕. It is assumed that a filtering coefficient of the digital tap filter is [h<NUM>, h<NUM>,. , hN], where N is an order of the digital tap filter (<FIG> uses an example in which N is equal to <NUM>), and a first transition signal s'(n) may be obtained by using formula <NUM>-<NUM>.

In formula <NUM>-<NUM>, s(n) is an input beat frequency signal, and a low frequency part of the beat frequency signal s(n) may be suppressed by selecting the filtering coefficient [h<NUM>, h<NUM>,. , hN] of the digital tap filter. Therefore, energy of the low frequency part of the obtained first transition signal s'(n)is relatively low.

Then, discrete Fourier transform (FFT) or short-time Fourier transform is performed on the first transition signal to obtain the first signal.

Optionally, the first transition signal may be converted into a frequency domain signal by using discrete Fourier transform (FFT), and the frequency domain signal is the first signal. An expression of the discrete Fourier transform (FFT) is shown in formula <NUM>-<NUM>: <MAT>.

In formula <NUM>-<NUM>, F( ) represents Fourier transform, and S(k) is a frequency signal obtained after discrete Fourier transform FFT is performed on the first transition signal s'(n), that is, the first signal described above.

Optionally, the first transition signal may be converted into a time-frequency two-dimensional signal by using short-time Fourier transform (STFT), and the time-frequency two-dimensional signal is the first signal. An expression of the short-time Fourier transform (STFT) is shown in formula <NUM>-<NUM>: <MAT>.

In formula <NUM>-<NUM>, STFT( ) represents short-time Fourier transform, and S(k) is a time-frequency two-dimensional spectrum obtained after short-time Fourier transform STFT is performed on the first transition signal s'(n), that is, the first signal described above.

An upper part of <FIG> shows the first signal obtained after discrete Fourier transform FFT is performed. It can be learned that an amplitude of a low frequency part of the first signal is relatively low, because a low frequency suppression operation is performed previously to suppress the amplitude of the low frequency signal.

In another manner, as shown in <FIG>, the obtaining a first signal may specifically include the following operations.

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

Optionally, the beat frequency signal may be converted into a frequency domain signal by using discrete Fourier transform (FFT), and the frequency domain signal is the second transition signal. An expression of the discrete Fourier transform (FFT) is shown in formula <NUM>-<NUM>: <MAT>.

In formula <NUM>-<NUM>, F( ) represents Fourier transform, and S(k)' is a frequency signal obtained after discrete Fourier transform FFT is performed on the beat frequency signal s(n), that is, the second transition signal described above.

Optionally, the beat frequency signal may be converted into a time-frequency two-dimensional signal by using short-time Fourier transform (STFT), and the time-frequency two-dimensional signal is the second transition signal. An expression of the short-time Fourier transform (STFT) is shown in formula <NUM>-<NUM>: <MAT>.

In formula <NUM>-<NUM>, STFT( ) represents short-time Fourier transform, and S(k)' is a time-frequency two-dimensional spectrum obtained after short-time Fourier transform STFT is performed on the beat frequency signal s(n), that is, the second transition signal described above.

Then, low frequency suppression is performed on the second transition signal to obtain the first signal.

For example, a frequency domain sequence of the second transition signal is multiplied by a preset sequence parameter, which may be specifically implemented by using a frequency domain equalizer. The preset sequence parameter has a relatively low coefficient in a low frequency part and a relatively high coefficient in a high frequency part. In this way, low frequency suppression is completed. For details, refer to formulas <NUM>-<NUM>.

In formula <NUM>-<NUM>, S(k) is the first signal, S(k)' is the second transition signal, and E(n) is the preset sequence number parameter.

Step S702: The signal processing apparatus performs mean gradient calculation on the first signal in frequency domain to obtain a second signal.

Specifically, after the low frequency suppression, although an interference signal may be suppressed, an amplitude of a low frequency signal may be suppressed severely, thereby causing gain imbalance of an entire frequency band. It can be learned from the upper part of the signal in <FIG> that, a signal amplitude in the low frequency part is lower than a signal amplitude in the high frequency part on the whole. This is because energy of the low frequency part is weakened as a whole during the low frequency suppression.

The gain imbalance of the entire frequency band results in a situation that a wave peak originally exists in the low frequency part. However, because low frequency suppression is performed, an amplitude of a wave peak in the low frequency part is lower than an amplitude of a non-wave peak in the high frequency part, that is, a real wave peak is masked. As a result, a subsequent calculation of the speed and/or distance based on the wave peak is inaccurate. To resolve a problem that a real wave peak may be masked, this application specifically provides a signal optimization manner for calculating a mean gradient. The mean gradient calculation is used to highlight a difference between a signal value of each sampling point in the first signal and a signal value of a surrounding sampling point. A specific principle is as follows:.

Optionally, in frequency domain, a spacing between the at least two other sampling points and the sampling point is greater than a first preset threshold and less than a second preset threshold. It should be noted that, it is mentioned that the distance is less than the second preset threshold, so that each sampling point is compared with a nearby sampling point for calculation, because if the sampling point is too far from each sampling point, comparison value is lost. However, the another sampling point cannot be too close to each sampling point either, because a sampling point that is too close to each sampling point may have a same problem as that of each sampling point, for example, is severely interfered. Therefore, when the another sampling point is too close to each sampling point, the sub-signal obtained through calculation may be unstable. Therefore, in this application, the first preset threshold and the second preset threshold are introduced, so that another sampling point used for calculating the sub-signal is near each sampling point, but is not too close.

For ease of understanding, the following provides a method for calculating a sub-signal ΔS(k) of each sampling point as follows: <MAT> where S(k) is a signal value of each sampling point, S(k - lp - n) is a signal value of another sampling point that has a frequency less than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, S(k + lp + n) is a signal value of another sampling point that has a frequency greater than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, lp is the first preset threshold, and lw is the second preset threshold.

As shown in <FIG>, the second signal obtained after mean gradient calculation is performed on the upper part of the signal (that is, the first signal) in <FIG> is the lower part of the signal (that is, the second signal) in <FIG>. It can be learned from the lower part of the signal that even if the low frequency part is suppressed, a wave peak in the low frequency part is highlighted, and a problem that the wave peak in the low frequency part is masked basically does not occur.

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

Optionally, as shown in <FIG>, the transmitted FMCW signal includes an up-chirp (chirp) signal and a down-chirp (chirp) signal. Through the foregoing operations, a peak signal may be obtained respectively from the up-chirp and the down-chirp, frequency positions of the two peak signals are found, and the two found frequency domain positions are respectively fu and fd. If a recorded frequency modulation slope of the FMCW is α, then:.

The distance from the target object to the radar obtained through calculation is <MAT>, where c is the speed of light.

The moving speed of the target object obtained through calculation is <MAT>, where λ is the wavelength of the emitted laser.

In the method described in <FIG>, low frequency suppression is performed on the frequency domain signal of the beat frequency signal, so as to reduce influence of low frequency interference on subsequent calculation of the speed or distance of the target object. To prevent a peak signal that may exist in the low frequency part from being clipped due to low frequency suppression, the peak signal that may exist in the low frequency part is further highlighted by performing mean gradient calculation. Therefore, accuracy of a radar detection result calculated by using the solution in this embodiment of this application is relatively high. In addition, implementation of this embodiment of this application is completed by performing special processing on a signal, and a hardware structure of a radar does not need to be improved. Therefore, implementation costs are relatively low.

The foregoing describes in detail the method in embodiments of this application. The following provides an apparatus in embodiments of this application.

<FIG> is a schematic diagram of a structure of a signal processing apparatus <NUM> according to an embodiment of this application. The apparatus <NUM> may be the foregoing lidar system, or a processor in the lidar system, or a related component on which the processor is deployed and deployed in the laser radar system. The signal processing apparatus <NUM> may include an obtaining unit <NUM>, an optimization unit <NUM>, and a calculation unit <NUM>. Detailed descriptions of the units are as follows:.

In this solution, low frequency suppression is performed on the frequency domain signal of the beat frequency signal, so as to reduce influence of low frequency interference on subsequent calculation of the speed or distance of the target object. To prevent a peak signal that may exist in the low frequency part from being clipped due to low frequency suppression, the peak signal that may exist in the low frequency part is further highlighted by performing mean gradient calculation. Therefore, accuracy of a radar detection result calculated by using the solution in this embodiment of this application is relatively high. In addition, implementation of this embodiment of this application is completed by performing special processing on a signal, and a hardware structure of a radar does not need to be improved. Therefore, implementation costs are relatively low.

In an optional solution, in terms of obtaining the first signal, the obtaining unit <NUM> is specifically configured to:.

In still another optional solution, the low frequency suppression is implemented by using a digital tap filter, or the low frequency suppression is implemented by performing scaling processing on a preset sequence parameter.

In still another optional solution, when mean gradient calculation is performed on the first signal in frequency domain to obtain a second signal, the calculation unit <NUM> is specifically configured to:.

In still another optional solution, in frequency domain, a spacing between the at least two other sampling points and the sampling point is greater than a first preset threshold and less than a second preset threshold.

In still another optional solution, a sub-signal ΔS(k) of each sampling point is as follows: <MAT> where S(k) is a signal value of each sampling point, S(k - lp - n) is a signal value of another sampling point that has a frequency less than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, S(k + lp + n) is a signal value of another sampling point that has a frequency greater than that of each sampling point in frequency domain and that is separated from each sampling point by (lp + n) sampling points, lp is the first preset threshold, and lw is the second preset threshold.

It should be noted that, for implementations of the units, reference may be correspondingly made to corresponding descriptions of the method embodiment shown in <FIG>. The foregoing units may be implemented by software, hardware, or a combination thereof. The hardware may be the foregoing processor, and the software may include driver code running on the processor. This is not limited in this embodiment.

An embodiment of this application further provides a chip system. The chip system includes at least one processor, a memory, and an interface circuit. The memory, the interface circuit, and the at least one processor are interconnected through lines, and the at least one memory stores instructions. When the instructions are executed by the processor, the method procedure shown in <FIG> is implemented.

An embodiment of this application further provides a computer-readable storage medium. The computer-readable storage medium stores instructions, and when the instructions are run on a processor, the method procedure shown in <FIG> is implemented.

An embodiment of this application further provides a computer program product. When the computer program product is run on a processor, the method procedure shown in <FIG> is implemented.

In conclusion, low frequency suppression is performed on the frequency domain signal of the beat frequency signal, so as to reduce influence of low frequency interference on subsequent calculation of the speed or distance of the target object. To prevent a peak signal that may exist in the low frequency part from being clipped due to low frequency suppression, the peak signal that may exist in the low frequency part is further highlighted by performing mean gradient calculation. Therefore, accuracy of a radar detection result calculated by using the solution in this embodiment of this application is relatively high. In addition, implementation of this embodiment of this application is completed by performing special processing on a signal, and a hardware structure of a radar does not need to be improved. Therefore, implementation costs are relatively low.

Claim 1:
A radar ranging method, comprising:
obtaining a first signal, wherein the first signal is a frequency domain signal obtained after low frequency suppression is performed in a beat frequency signal, and the beat frequency signal is a signal obtained by mixing a transmitted signal transmitted by a frequency modulated continuous wave FMCW radar and a received echo signal;
performing mean gradient calculation on the first signal in frequency domain to obtain a second signal, wherein the mean gradient calculation is used to highlight a difference between a signal value of each sampling point in the first signal and a signal value of a surrounding sampling point; and
calculating at least one of a speed or a distance of a target object based on a peak signal in the second signal.