Signal processing method and device

Abstract

A signal processing method and apparatus, the method being applicable to the technical field of detection, the method comprising: controlling a detection apparatus to transmit a detection signal, the detection signal comprising a plurality of bursts (S310); determining a step bandwidth of the detection signal (S320); and determining a mode of performing extreme value comparison on a to-be-detected unit according to the stepping bandwidth, wherein the to-be-detected unit belongs to a first spectrogram obtained by performing spectral analysis on a return signal of the detection signal. The method can be applied to an intelligent vehicle or a new energy vehicle, can avoid the situation that the extreme value comparison result is inaccurate due to the fact that detection signals involve steps, and can improve the contour estimation and classification recognition capability of the target.

Description

Signal processing method and device Technical Field

[0001] The embodiments of the present application relate to the field of detection technology, and more specifically, to a method and device for signal processing. Background Art

[0002] Radar can detect surrounding targets by sending detection signals. For example, millimeter-wave radar can use frequency modulated continuous wave (FMCW) signals as detection signals. For radar systems, distinguishing between adjacent targets can be challenging, especially in terms of distinguishing the speed and / or distance of adjacent targets. Increasing the range resolution of the radar can better distinguish between two adjacent targets. The bandwidth of the stepped FMCW signal is the sum of the single chirp bandwidth and the stepped bandwidth. Compared with using traditional FMCW signals, using a stepped FMCW signal as a detection signal can improve radar resolution.

[0003] Actual radar detection targets include many large targets (which can be considered to be composed of multiple point targets), and their amplitude cross-sections on the two-dimensional spectrum present irregular shapes. When processing traditional FMCW signals, the four adjacent units above, below, left, and right of the unit to be tested can be used as its reference units. By comparing extreme values, the cell where the target actually exists in the two-dimensional spectrum graph can be determined, and the speed and / or distance of the target can be determined based on this cell. However, the use of stepped FMCW signals will cause the distribution of the target in the two-dimensional spectrum graph to change. Using the four adjacent units above, below, left, and right of the unit to be tested as its reference units may result in the omission of non-two-dimensional peak targets.

[0004] In view of this, in scenarios where the detection signal may involve steps, how to perform signal processing becomes an urgent problem to be solved.

[0005] Summary of the Invention

[0006] The embodiments of the present application provide a signal processing method and device, which can determine the extreme value comparison method according to the stepping method of the detection signal, can avoid the inaccurate extreme value comparison results caused by the stepping of the detection signal, can improve the accuracy of the signal processing results, and can improve the target contour estimation and classification recognition capabilities.

[0007] In a first aspect, a signal processing method is provided. This method can be performed by an intelligent driving device, or by a computing platform within the intelligent driving device, or by a chip or processor within the computing platform. In some possible implementations, the method can be performed by a system consisting of a detection device (such as a radar) and a computing platform, or by the detection device, or by a chip or processor within the detection device.

[0008] The method includes: controlling a detection device to transmit a detection signal, the detection signal including multiple bursts; determining a step bandwidth of the detection signal; when the step bandwidth is zero, using a first method to perform extreme value comparison on a unit to be tested, the unit to be tested being a unit having an energy amplitude greater than or equal to a first threshold, the unit to be tested belonging to a first spectrum diagram, and the first spectrum diagram being obtained by spectrum analysis of a return signal of the detection signal; or, when the step bandwidth is greater than zero, using a second method to perform extreme value comparison on the unit to be tested; or, when the step bandwidth is less than zero, using a third method to perform extreme value comparison on the unit to be tested.

[0009] In the present application, the method of performing extreme value comparison on the unit to be tested is determined based on the step bandwidth of the detection signal, and the signal processing method can be flexibly determined according to the step form of the detection signal. It can be applicable to the signal processing of detection signals with different step forms, and can avoid the situation where the extreme value comparison results are inaccurate due to the stepping of the detection signal. It can improve the accuracy of the signal processing results and the ability to estimate the contour and classify the target.

[0010] In combination with the first aspect, in certain implementations of the first aspect, the use of the second method to perform extreme value comparison on the unit to be tested, or the use of the third method to perform extreme value comparison on the unit to be tested, may include: determining a first reference line corresponding to the unit to be tested, the slope of the first reference line being determined based on the step bandwidth of the detection signal; determining a reference unit corresponding to the unit to be tested based on the first reference line; and performing extreme value comparison on the unit to be tested and the reference unit corresponding to the unit to be tested.

[0011] In the present application, the slope of the first reference line is determined according to the step bandwidth, and the extension direction of the target energy in the first spectrum diagram can be determined based on the step bandwidth, which can fully utilize the data collected by the radar and improve the target contour estimation and classification recognition capabilities.

[0012] In combination with the first aspect, in certain implementations of the first aspect, the use of the second method to perform extreme value comparison on the unit to be tested may include: when the step bandwidth of the detection signal is the same as the bandwidth of the burst, selecting the upper left and lower right units of the unit to be tested for extreme value comparison; or, when the step bandwidth of the detection signal is different from the bandwidth of the burst, performing fast Fourier transform (FFT) interpolation calculation on the return signal of the detection signal, and selecting the upper left and lower right units of the unit to be tested for extreme value comparison.

[0013] For example, when the step bandwidth is different from the burst bandwidth, the sampling data of the return signal of the detection signal is interpolated and padded with zeros, and then FFT is performed on the interpolated data to obtain the first spectrum diagram. Based on the first spectrum diagram, the upper left and lower right units of the unit to be tested can be selected and compared with the extreme values ​​of the unit to be tested.

[0014] In combination with the first aspect, in certain implementations of the first aspect, the use of the third method to perform extreme value comparison on the unit to be tested may include: when the step bandwidth of the detection signal is the same as the bandwidth of the burst, selecting the lower left and upper right units of the unit to be tested for extreme value comparison; or, when the step bandwidth of the detection signal is different from the bandwidth of the burst, performing FFT interpolation calculation on the return signal of the detection signal, and selecting the lower left and upper right units of the unit to be tested for extreme value comparison.

[0015] In the present application, the extreme value comparison method can be flexibly determined according to the relationship between the step bandwidth and the burst bandwidth, which can further improve the accuracy of the extreme value comparison result.

[0016] In combination with the first aspect, in certain implementations of the first aspect, the detection signal is a stepped frequency modulated continuous wave (FMCW) signal, the stepped FMCW signal includes multiple chirps, each burst in the multiple bursts is a chirp, the bandwidth of the chirp is a single chirp bandwidth, and determining the first reference line corresponding to the unit to be tested may include: determining the first reference line corresponding to the unit to be tested based on the ratio of the stepped bandwidth to the single chirp bandwidth.

[0017] In the present application, the ratio of the step bandwidth and the single chirp bandwidth can characterize the extension direction of the energy of the static extended target in the first spectrum diagram. Therefore, in the process of determining the first reference line and the reference unit, the correlation between the detection signal and the first spectrum diagram can be fully utilized, and a more appropriate reference unit can be determined, thereby further improving the accuracy of the extreme value comparison results.

[0018] In combination with the first aspect, in certain implementations of the first aspect, the FFT interpolation calculation is performed on the return signal of the detection signal, including: obtaining sampling data of the return signal of the detection signal; performing FFT on the sampling data and N data with zero values ​​to obtain the first spectrum diagram.

[0019] In the present application, zero padding is performed on the sampled data, which is beneficial for adapting the FFT acceleration algorithm and also helps to match the distribution of the reference units with the first reference line.

[0020] In combination with the first aspect, in certain implementations of the first aspect, a ratio of N to the number of sampled data is equal to a ratio of the step bandwidth to the burst bandwidth.

[0021] In combination with the first aspect, in certain implementations of the first aspect, the sum of N and the sampled data is an integer power of 2.

[0022] In combination with the first aspect, in certain implementations of the first aspect, the use of the first method to perform extreme value comparison on the unit to be tested may include: selecting the left and right units of the unit to be tested for extreme value comparison; or selecting the upper, lower, left and right four units of the unit to be tested for extreme value comparison.

[0023] In a second aspect, a signal processing device is provided, which may include: a control unit for controlling a detection device to transmit a detection signal, wherein the detection signal includes multiple bursts; a processing unit for: determining a step bandwidth of the detection signal; when the step bandwidth is zero, using a first method to perform extreme value comparison on a unit to be tested, wherein the unit to be tested is a unit having an energy amplitude greater than or equal to a first threshold, and the unit to be tested belongs to a first spectrum diagram, which is obtained by spectrum analysis of a return signal of the detection signal; or, when the step bandwidth is greater than zero, using a second method to perform extreme value comparison on the unit to be tested; or, when the step bandwidth is less than zero, using a third method to perform extreme value comparison on the unit to be tested.

[0024] In combination with the second aspect, in certain implementations of the second aspect, the processing unit can be used to: determine a first reference line corresponding to the unit to be tested, the slope of the first reference line being determined based on the step bandwidth of the detection signal; determine a reference unit corresponding to the unit to be tested based on the first reference line; and perform extreme value comparison between the unit to be tested and the reference unit corresponding to the unit to be tested.

[0025] In combination with the second aspect, in certain implementations of the second aspect, the processing unit can be used to, when the step bandwidth of the detection signal is the same as the bandwidth of the burst, select the upper left and lower right units of the unit to be tested for extreme value comparison; or, when the step bandwidth of the detection signal is different from the bandwidth of the burst, perform FFT interpolation calculation on the return signal of the detection signal, and select the upper left and lower right units of the unit to be tested for extreme value comparison.

[0026] In combination with the second aspect, in certain implementations of the second aspect, the processing unit can be used to, when the step bandwidth of the detection signal is the same as the bandwidth of the burst, select the lower left and upper right units of the unit to be tested for extreme value comparison; or, when the step bandwidth of the detection signal is different from the bandwidth of the burst, perform FFT interpolation calculation on the return signal of the detection signal, and select the lower left and upper right units of the unit to be tested for extreme value comparison.

[0027] In combination with the second aspect, in certain implementations of the second aspect, the stepped FMCW signal includes multiple chirps, each burst in the multiple bursts is a chirp, and the bandwidth of the chirp is a single chirp bandwidth. The processing unit can be used to determine the first reference line corresponding to the unit to be tested based on the ratio of the stepped bandwidth to the single chirp bandwidth.

[0028] In combination with the second aspect, in some implementations of the second aspect, the processing unit can be used to obtain sampling data of the return signal of the detection signal; perform FFT on the sampling data and N data with zero values ​​to obtain the first spectrum diagram.

[0029] In combination with the second aspect, in certain implementations of the second aspect, the ratio of N to the number of sampled data is equal to the ratio of the step bandwidth to the burst bandwidth.

[0030] In combination with the second aspect, in certain implementations of the second aspect, the sum of N and the sampled data is an integer power of 2.

[0031] In combination with the second aspect, in some implementations of the second aspect, the processing unit can be used to select two left and right units of the unit to be tested for extreme value comparison; or select four upper, lower, left and right units of the unit to be tested for extreme value comparison.

[0032] In a third aspect, a signal processing device is provided, which includes: a memory for storing a computer program; and a processor for executing the computer program stored in the memory, so that the device performs the method in the above-mentioned first aspect and any possible implementation thereof.

[0033] In a fourth aspect, a signal processing system is provided, which includes a radar and a computing platform, wherein the computing platform includes the device of the second aspect or the third aspect and any possible implementation thereof.

[0034] Exemplarily, the device may acquire a return signal of the detection signal and may perform signal processing on sampling data of the return signal.

[0035] In a fifth aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect and any possible implementation thereof.

[0036] In a sixth aspect, a computer-readable storage medium is provided, wherein the computer-readable medium stores a computer program. When the computer program runs on a computer, the computer executes the method in the first aspect and any possible implementation thereof.

[0037] In a seventh aspect, a chip is provided, which includes a circuit for executing the method in the above-mentioned first aspect and any possible implementation thereof.

[0038] In an eighth aspect, an intelligent driving device is provided, which includes the apparatus of the second aspect or the third aspect and any possible implementation thereof, or includes a system of the fourth aspect and any possible implementation thereof.

[0039] Exemplarily, the intelligent driving device may include a vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] FIG1 is a functional block diagram of an intelligent driving device provided in an embodiment of the present application;

[0041] FIG2 is a schematic diagram of a vehicle-mounted radar and its arrangement location provided in an embodiment of the present application;

[0042] FIG3 is a schematic diagram of the time-frequency characteristics of a frequency modulated continuous wave provided in an embodiment of the present application;

[0043] FIG4 is a schematic diagram of the time-frequency characteristics of a step-frequency modulation continuous wave provided in an embodiment of the present application;

[0044] FIG5 is a schematic diagram of a radar system architecture provided in an embodiment of the present application;

[0045] FIG6 is a schematic diagram of a signal processing scenario provided by an embodiment of the present application;

[0046] FIG7 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application;

[0047] FIG8 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application;

[0048] FIG9 is a flow chart of a signal processing method provided in an embodiment of the present application;

[0049] FIG10 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application;

[0050] FIG11 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application;

[0051] FIG12 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application;

[0052] FIG13 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application;

[0053] FIG14 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application;

[0054] FIG15 is a flow chart of a signal processing method provided in an embodiment of the present application;

[0055] FIG16 is a schematic block diagram of a signal processing apparatus provided in an embodiment of the present application;

[0056] FIG17 is a schematic block diagram of another signal processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is a kind of association relationship that describes associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In this application, "at least one" refers to one or more, and "more than one" refers to two or more. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0058] In the embodiments of this application, prefixes such as "first" and "second" are used only to distinguish different description objects and have no limiting effect on the position, order, priority, quantity, or content of the described objects. The use of prefixes such as ordinal numbers in the embodiments of this application to distinguish description objects does not constitute a limitation on the described objects. For a statement of the described objects, please refer to the description in the context of the claims or embodiments, and the use of such prefixes should not constitute an unnecessary limitation.

[0059] The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.

[0060] Figure 1 is a functional block diagram of an intelligent driving device 100 provided in an embodiment of the present application. The intelligent driving device 100 may include a perception system 120 and a computing platform 150, wherein the perception system 120 may include one or more sensors for sensing information about the environment surrounding the intelligent driving device 100. For example, the perception system 120 may include a positioning system, which may be a global positioning system (GPS), a Beidou system, or other positioning systems. The perception system 120 may include one or more types of radars such as a lidar, a millimeter-wave radar, and an ultrasonic radar, and may also include an inertial measurement unit (IMU) and a camera. In some possible implementations, the intelligent driving device 100 may include a display device 130.

[0061] Some or all functions of the intelligent driving device 100 can be controlled by the computing platform 150. The computing platform 150 may include one or more processors, such as processors 151 to 15n (n is a positive integer). A processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented by an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as a field programmable gate array (FPGA). In a reconfigurable hardware circuit, the process of the processor loading a configuration file to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc. In addition, the computing platform 150 can also include a memory for storing instructions, and some or all of the processors 151 to 15n can call the instructions in the memory to implement corresponding functions.

[0062] The intelligent driving device 100 in this application may include: road vehicles, water vehicles, air vehicles, industrial equipment, agricultural equipment, or entertainment equipment, etc. For example, the intelligent driving device 100 can be a vehicle, which is a vehicle in a broad sense, and can be a vehicle (such as a commercial vehicle, a passenger car, a motorcycle, a flying car, a train, etc.), an industrial vehicle (such as a forklift, a trailer, a tractor, etc.), an engineering vehicle (such as an excavator, a bulldozer, a crane, etc.), agricultural equipment (such as a mower, a harvester, etc.), amusement equipment, a toy vehicle, etc. The embodiment of this application does not specifically limit the type of vehicle. For another example, the intelligent driving device 100 can be a vehicle such as an airplane or a ship. For the sake of convenience of explanation and description, the following is an introduction taking the intelligent driving device 100 as a vehicle as an example.

[0063] For example, Figure 2 is a schematic diagram of a vehicle-mounted radar and its installation location provided by an embodiment of the present application. As shown in Figure 2, Figure 2 shows the types of some common vehicle-mounted radars and their installation locations.

[0064] As shown in Figure 2, a vehicle can be equipped with one or more types of radar, including lidar, millimeter-wave radar, and ultrasonic radar. Lidar (light detection and ranging) refers to radar that uses laser beams for detection. Due to the advantages of laser light, such as high coherence, directionality, and monochromaticity, lidar is capable of long-range, high-precision ranging. Millimeter-wave radar refers to radar that uses millimeter waves for detection. Compared to optical beams such as infrared and laser, millimeter waves have a strong ability to penetrate fog, smoke, and dust, making millimeter-wave radars usable in all weather conditions. Furthermore, their short wavelength makes it easy to capture detailed features and clearly image the outlines of a target, making them useful for target classification and identification. Millimeter-wave radar can be used to determine the distance and speed of an object. Ultrasonic radar refers to radar that uses ultrasonic waves for detection. Ultrasonic ranging sensors have significant advantages in short-range measurements. As shown in Figure 2, a vehicle can be equipped with three lidars for forward, left, and right directions; six millimeter-wave radars for forward, rear, and side directions, one for the front, one for the rear, and four for the sides; and four ultrasonic radars for the sides.

[0065] It should be understood that the above description of the types, numbers, and locations of radars is provided for ease of explanation only. In one embodiment, a vehicle may be equipped with more or fewer types of radars. In another embodiment, a vehicle may be equipped with a greater or fewer number of millimeter-wave radars.

[0066] For example, radars can be divided into pulse radars and continuous wave radars based on the form of the detection signal emitted. Pulse radars can measure surrounding objects using high-frequency pulses. Continuous wave radars can include single-frequency continuous wave radars, multi-frequency continuous wave radars, and frequency-modulated continuous wave radars. Among them, FMCW radars can detect the distance and speed of surrounding objects by transmitting FMCW signals using relatively low-cost equipment. Frequency modulation methods can include triangle wave modulation, sawtooth wave modulation, etc., and frequency modulation can produce an FMCW signal whose frequency varies with time. FMCW is explained below using triangle wave modulation as an example in conjunction with Figures 3 and 4.

[0067] For example, FIG3 is a schematic diagram of the time-frequency characteristics of a frequency modulated continuous wave provided in an embodiment of the present application. As shown in FIG3, after being modulated by a triangular wave, the frequency of the detection signal can change linearly over time. Each linear change segment can be called a chirp, and multiple chirps (e.g., 256 or 512) sent sequentially can constitute a frame (e.g., frame #1). For FMCW, a frame can also include a greater or lesser number of chirps.

[0068] For example, FIG4 is a schematic diagram of the time-frequency characteristics of the stepped frequency modulated continuous wave provided in an embodiment of the present application. In the waveform of the stepped FMCW, the frequency change mode within a single chirp is similar to that in FIG3. Compared with the traditional FMCW shown in FIG3, the starting frequency of each chirp in the stepped FMCW changes linearly. For example, as shown in (a) in FIG4, frame #2 may include multiple chirps including chirp #1 and chirp #2. Chirp #1 and chirp #2 are still FMCW signals, and the starting frequencies of the multiple chirps in frame #2 are different. In other words, the transmission frequency of chirp #1, chirp #2, etc. in frame #2 can change linearly over time. For another example, as shown in FIG4, the starting frequencies of chirp #1, chirp #2 and chirp #3 are frequency #1, frequency #2 and frequency #3, respectively. The difference between the starting frequencies of adjacent bursts is the step frequency (denoted as Δf). For example, Δf = frequency #2 - frequency #1.

[0069] Exemplarily, step FMCW can include upper step FMCW and lower step FMCW. Upper step FMCW can refer to a step FMCW with a positive step frequency, and lower step FMCW can refer to a step FMCW with a negative step frequency. It can also be understood that upper step FMCW is an FMCW with a step bandwidth greater than zero, and lower step FMCW is an FMCW with a step bandwidth less than zero. For example, (a) in Figure 4 shows the time-frequency characteristics of upper step FMCW, and (b) in Figure 4 shows the time-frequency characteristics of lower step FMCW. For another example, the FMCW in Figure 3 is a traditional FMCW, which can be understood as an FMCW with a step bandwidth of zero, or it can be understood as an FMCW with a step frequency of zero.

[0070] Exemplarily, the bandwidth of a single frame signal of a stepped FMCW may include the sum of the bandwidth of a single chirp signal (which may be referred to as a single chirp bandwidth, or a single chirp bandwidth) and the step bandwidth. The bandwidth of the frame signal may be adjusted in a step-by-step manner, thereby improving the range resolution of the radar. The step bandwidth may refer to the difference between the starting frequencies of the first chirp and the last chirp in the frame signal. For example, as shown in (a) of FIG4 , Chirp #1, Chirp #2, Chirp #3 to Chirp #n in frame #2 have the same bandwidth, i.e., a single chirp bandwidth; the first chirp of frame #2 is Chirp #1, and the last chirp is Chirp #n (n is an integer greater than or equal to 3), and the bandwidth between the starting frequency of Chirp #1 and the starting frequency of Chirp #n is the step bandwidth.

[0071] Exemplarily, the detection signal used by the radar may include multiple bursts. For example, linear frequency modulation can be performed from low frequency to high frequency within a single burst, such as the chirp shown in Figure 3 or Figure 4. For another example, nonlinear frequency modulation can be performed from low frequency to high frequency within a single burst. For another example, step-by-step frequency modulation can be used from low frequency to high frequency within a single burst. For another example, the detection signal may also use a phase modulated continuous wave (PMCW) in a stepped form. The embodiments of the present application do not limit the modulation method of the detection signal.

[0072] For example, FIG5 is a schematic diagram of a system architecture of a radar provided in an embodiment of the present application. As shown in FIG5 , on the transmitting side, the detection signal can be radiated into space through a transmitting antenna (transmit, Tx) after being processed by a voltage controlled oscillator (VCO), a power amplifier (PA), etc. On the receiving side, the echo signal reflected by the target can be received by a receiving antenna (receive, Rx), and after being processed by multiple devices such as a low noise amplifier (LNA), a high-pass filter (HPF), a low-pass filter (LPF), and an analog to digital converter (ADC), a fast time dimension FFT and a slow time dimension FFT can be performed. After two FFT processes, a range-Doppler spectrum can be obtained, which can also be called a two-dimensional spectrum or a range-velocity spectrum.

[0073] Taking an FMCW signal as an example, a radar can continuously transmit multiple FMCW signals (for example, N). These signals are reflected by the target and received by the receiving antenna. After frequency mixing and ADC sampling (for example, each FMCW signal is sampled at M points), they are stored in a memory unit. The N FMCW signals are then sampled by the ADC to produce a total of M*N data. This M*N data can be arranged in a two-dimensional matrix. The dimension formed by the sampled data corresponding to the same FMCW echo signal is called the fast time dimension, while the dimension formed by the sampled data between multiple FMCW signals is called the slow time dimension. Processing the fast time dimension data yields range information, while processing the slow time dimension data yields velocity information. For example, performing an FFT on the fast time dimension data yields a range spectrum, and performing a second-dimensional FFT on all range spectra yields a range-Doppler spectrum. For example, a single point target appears as a dot area on the two-dimensional spectrum. The position of the point on the two-dimensional coordinates can correspond to the distance and speed of the target respectively. The frequency in the fast time dimension can correspond to the distance information of the target, the frequency in the slow time dimension can correspond to the speed information of the target, and the area of ​​the dot area can correspond to the resolution of the target.

[0074] It should be understood that the above system architecture is applicable to FMCW radars and is provided as an example for ease of explanation. In some possible implementations, the radar system architecture may include more or fewer modules. For example, when the detection signal is a PMCW signal, the system architecture may include a local oscillator, etc.

[0075] In some possible implementations, the value of each unit of the spectrum graph can be compared with a preset value by means of constant false-alarm rate (CFAR) to determine whether a target is detected on the unit. Through CFAR, the distribution of the target on the spectrum graph can be determined, that is, the unit corresponding to the target can be determined in the spectrum graph. Furthermore, through peak grouping, the unit to be tested among the multiple units is compared with the values ​​of the four adjacent upper, lower, left, and right units to determine the specific cell where the target is located. The following takes the detection signal as FMCW as an example, combined with Figures 6 to 8, to briefly explain the problems existing in the above-mentioned signal processing method when the detection signal involves stepping.

[0076] Exemplarily, Figure 6 is a schematic diagram of a signal processing scenario provided by an embodiment of the present application. As shown in (a) in Figure 6, the single-point target appears as a dot area including multiple units in the two-dimensional spectrum diagram. As shown in (b) in Figure 6, by determining the units in the spectrum diagram whose energy amplitude is greater than the first threshold, the distribution of the target in the spectrum diagram can be determined. For example, through CFAR, the multiple units involved in the dot area can be determined. As shown in (c) in Figure 6, units 2, 5 and 8 can be compared with the values ​​of their respective adjacent left and right units to determine whether they are extreme value units. For example, the two adjacent units on the left and right of unit 2 (i.e., units 1 and 3) can be used as reference units for its one-dimensional extreme value comparison. When the value of unit 2 is greater than the values ​​of unit 1 and unit 3, unit 2 is a one-dimensional extreme value unit. For another example, assuming that cells 2, 5, and 8 are all one-dimensional extreme value cells, cell 5 and its two upper and lower adjacent cells (i.e., cells 2 and 8) can be used as reference cells for comparison of their two-dimensional extreme values ​​(also called cross extreme values). When the value of cell 5 is greater than the values ​​of cells 2 and 8, cell 5 is a two-dimensional extreme value cell. Furthermore, the distance and speed of the cell can be determined based on cell 5.

[0077] In actual scenarios, the targets detected by the FMCW radar may include targets with larger volumes (it can be considered that the larger volume targets are composed of multiple single-point targets). The amplitude section of the target on the two-dimensional spectrum is irregular in shape, and the extension length in distance is greater than the distance resolution, resulting in the target occupying multiple units of the two-dimensional spectrum. After peak aggregation processing, multiple target units will be detected. For example, Figure 7 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application. Among them, the detection signal used can be understood as an FMCW signal with a step frequency of 0. As shown in (a) in Figure 7, the larger target (denoted as target #1) can be reflected as multiple dot areas in the two-dimensional spectrum diagram. By performing CFAR processing on (a) in Figure 7, Figure 7 (b) can be obtained. The units in the shaded part of (b) in Figure 7 are the units corresponding to target #1. As shown in (c) in Figure 7, assuming that units 2, 5, 8, 11, 14 and 17 are one-dimensional extreme value units, by comparing the values ​​of the one-dimensional extreme value units with their reference units, it can be determined that units 5 and 14 are two-dimensional extreme value units, and then the distance and speed information of each part of the target #1 can be determined based on the two-dimensional extreme value units 5 and 14.

[0078] When the step bandwidth of the detection signal is greater than zero or less than zero, the single point target is still reflected as a dot area on the two-dimensional spectrum diagram. However, the extended target is distributed in a diagonal line on the two-dimensional spectrum diagram, and the slope of the diagonal line is related to the step bandwidth. Since the distribution of the extended target is no longer perpendicular to the slow time dimension, the two adjacent units on the left and right of the unit to be tested are still used as its reference units for one-dimensional extreme value comparison, which will cause the non-two-dimensional peak target to be missed. For example, as shown in Figure 8, Figure 8 is a schematic diagram of a signal processing scenario provided by an embodiment of the present application. As shown in (a) of Figure 8, when the upper step FMCW signal is used to determine the distance and speed of the above-mentioned target #1, the multiple single point targets corresponding to the target #1 (the multiple single point targets are the above-mentioned extended targets) are distributed in a diagonal line in the two-dimensional spectrum diagram, and the results of the CFAR of the multiple extended targets can be shown in (b) of Figure 8. The result of peak aggregation processing still performed in the above manner can be shown in (c) of Figure 8, where units 6, 10 and 20 are detected two-dimensional extreme value units. Because the distribution of extended targets in this two-dimensional spectrum is not perpendicular to the slow-time dimension, using the left and right adjacent units of each unit to be tested as reference units for one-dimensional extreme value comparison, and using the upper and lower adjacent units of the one-dimensional extreme value unit as reference units for two-dimensional extreme value comparison, will cause the number of detected extreme value units to be less than the actual number of extended targets, resulting in underreporting. The distance and speed of target #1 determined based on this result will have large errors.

[0079] For example, FIG9 is a flow chart of a signal processing method provided by an embodiment of the present application. For example, the method 300 can be executed by an intelligent driving device, or it can be executed by a computing platform in the intelligent driving device, or it can be executed by a chip or processor in the computing platform. For another example, the method 300 can also be executed by a system consisting of a radar and a computing platform. For another example, the method 300 can be executed by a radar, or it can be executed by a chip or processor in the radar. The method 300 may include the following steps:

[0080] S310, controlling a detection device to transmit a detection signal, where the detection signal includes a plurality of bursts.

[0081] Exemplarily, the detection signal includes multiple bursts, and may include two bursts, or may include a group of bursts, such as the FMCW detection signal shown in FIG. 3 or FIG. 4 .

[0082] In some possible implementations, a single burst of the detection signal may be frequency modulated linearly, such as a chirp as shown in FIG3 or FIG4 , or may be frequency modulated nonlinearly, or may be frequency modulated using a step function. In some possible implementations, the detection signal may also use a stepped phase modulated continuous wave (PMCW).

[0083] For example, the detection device may include a radar. For example, when the method is executed by a computing platform in an intelligent driving device, the computing platform may control the radar to transmit the detection signal through the internal circuitry of the intelligent driving device. For another example, when the method is executed by a processor in the radar, the processor may control the radar to transmit the detection signal. For another example, the detection device may be a millimeter-wave radar or another type of radar.

[0084] S320: Determine the step bandwidth of the detection signal.

[0085] For example, the method for performing extreme value comparison on the unit under test can be determined based on the step bandwidth of the detection signal. Whether the detection signal involves stepping and the adopted stepping method can be determined based on the step bandwidth.

[0086] S330, when the step bandwidth is zero, the extreme value comparison of the unit to be tested is performed in the first manner, the unit to be tested is a unit whose energy amplitude is greater than or equal to the first threshold, and the unit to be tested belongs to the first spectrum diagram, which is obtained by spectrum analysis of the return signal of the detection signal.

[0087] Exemplarily, the first spectrum graph may be obtained by spectrum analysis of the return signal of the detection signal, and the unit to be tested may be a unit in the first spectrum graph having an energy threshold greater than or equal to the first threshold. For example, the first spectrum graph may be the range-Doppler spectrum in FIG5 . For another example, when the detection signal is an FMCW signal, the first spectrum graph may be as shown in FIG6 . For another example, the first threshold may be a threshold used for constant false alarm detection. For another example, the unit to be tested may be the unit corresponding to target #1 as described in (b) of FIG7 .

[0088] Exemplarily, performing extreme value comparison on the unit under test may be to compare the value of the unit under test with the value of the corresponding reference unit to determine whether the unit under test is an extreme value unit. For example, as shown in FIG6 , taking unit 5 as the unit under test, the value of unit 5 may be compared with the values ​​of its corresponding reference units (e.g., units 4 and 6) to determine whether unit 5 is an extreme value unit.

[0089] Exemplarily, using the first method to perform extreme value comparison on the unit to be tested may include: selecting two units on the left and right of the unit to be tested for extreme value comparison; or selecting four units above, below, left, and right of the unit to be tested for extreme value comparison. For example, as shown in FIG6 , taking unit 5 as the unit to be tested as an example, the values ​​of unit 5 can be compared with those of units 4 and 6 to determine whether unit 5 is a one-dimensional extreme value unit. For another example, the values ​​of unit 5 can be compared with those of units 2, 4, 6, and 8 to determine whether unit 5 is a cross extreme value unit.

[0090] S340: When the step bandwidth is greater than zero, perform extreme value comparison on the unit under test using a second method.

[0091] In some possible implementations, using the second method to perform extreme value comparison on the unit to be tested may include: when the step bandwidth of the detection signal is the same as the bandwidth of the burst, selecting the upper left and lower right units of the unit to be tested for extreme value comparison.

[0092] In some possible implementations, the second method is used to perform extreme value comparison on the unit to be tested, which may include: when the step bandwidth of the detection signal is different from the bandwidth of the burst, performing FFT interpolation calculation on the return signal of the detection signal, and selecting the upper left and lower right units of the unit to be tested for extreme value comparison.

[0093] S350: When the step bandwidth is less than zero, use the third method to perform extreme value comparison on the unit under test.

[0094] In some possible implementations, using the third method to perform extreme value comparison on the unit to be tested may include selecting the upper left and lower right units of the unit to be tested for extreme value comparison when the step bandwidth of the detection signal is the same as the bandwidth of the burst.

[0095] In some possible implementations, the third method is used to perform extreme value comparison on the unit to be tested, which may include, when the step bandwidth of the detection signal is different from the bandwidth of the burst, performing FFT interpolation calculation on the return signal of the detection signal, and selecting the upper left and lower right units of the unit to be tested for extreme value comparison.

[0096] Exemplarily, a step bandwidth greater than zero can be understood as a step frequency greater than zero, i.e., the stepping mode of multiple bursts in the detection signal is upward stepping; a step bandwidth less than zero can be understood as a step frequency less than zero, i.e., the stepping mode of multiple bursts in the detection signal is downward stepping; a step bandwidth equal to zero can be understood as a step frequency equal to zero, and the starting frequency of each burst is the same.

[0097] In some possible implementations, when the step bandwidth is not zero, a first reference line corresponding to the unit under test can be determined based on the step bandwidth; a reference cell corresponding to the unit under test can be determined based on the first reference line; and an extreme value comparison can be performed on the unit under test based on the reference cell corresponding to the unit under test. In other words, performing an extreme value comparison on the unit under test using the second method or performing an extreme value comparison on the unit under test using the third method can include: determining a first reference line corresponding to the unit under test, the slope of the first reference line being determined based on the step bandwidth; and determining the reference cell corresponding to the unit under test based on the first reference line.

[0098] In some possible implementations, the detection signal may be an FMCW signal, which may include multiple chirps. That is, multiple bursts in the detection signal may be the multiple chirps, each burst may be a chirp, the bandwidth of a chirp may be a single chirp bandwidth, and the first reference line may be determined based on the step bandwidth and the single chirp bandwidth. The first reference line corresponding to the unit under test may intersect with the unit under test.

[0099] In some possible implementations, performing FFT interpolation calculation on the return signal of the detection signal may include: obtaining sampling data of the return signal of the detection signal; performing fast Fourier transform on the sampling data and N zero data to determine a first spectrum diagram.

[0100] In some possible implementations, the ratio of N to the number of sampled data is equal to the ratio of the step bandwidth to the burst bandwidth.

[0101] In some possible implementations, the sum of N and the number of sampled data is an integer power of 2. For example, if the number of sampled data is 510, N may be 2, and the sum of the two is 2 to the power of 9.

[0102] The following briefly describes the method 300 by taking the detection signal as a stepped FMCW signal as an example in conjunction with FIG. 10 to FIG. 15 . The method embodiments in FIG. 10 to FIG. 15 can be understood as an extension of the method 300 .

[0103] For example, FIG10 is a schematic diagram of a signal processing scenario provided by an embodiment of the present application. For example, as shown in (a) of FIG10 , when an upper step FMCW signal is adopted, the upper left unit and the lower right unit of the unit under test can be used as its reference unit. When the amplitude of the unit under test is greater than the amplitude of its reference unit, the unit under test can be determined as an extreme value unit (also referred to as a "slanted extreme value"). This extreme value comparison method can be understood as the second method in method 300. For another example, as shown in (b) of FIG10 , when a lower step FMCW signal is adopted, the lower left unit and the upper right unit of the unit under test can be used as its reference unit. When the amplitude of the unit under test is greater than the amplitude of its reference unit, the unit under test can be determined as an extreme value unit (also referred to as a "reverse slanted extreme value"). This can be understood as the third method in method 300 for performing extreme value comparison on the unit under test.

[0104] 11 , taking an upward-stepped FMCW signal as an example, a method for determining a reference unit for a unit under test is briefly described below.

[0105] For example, FIG11 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application. For example, when an upper stepped FMCW signal is adopted, the distribution of the extended target in the range-Doppler dimension spectrum diagram can be as shown in (a) of FIG11, and the distribution line of the target (also referred to as the target distribution line) is no longer perpendicular to the slow time dimension. The vertical line of the target distribution line corresponding to the unit to be tested can intersect with the unit to be tested and intersect with the reference unit of the unit to be tested. The vertical line corresponding to the unit to be tested can be understood as the first reference line in method 300. For another example, as shown in (b) of FIG11, for unit 6, the vertical line of the target distribution line passing through unit 6 can pass through unit 1 and unit 11, and the upper left unit 1 and the lower right unit 11 of unit 6 can be used as its reference unit, and it is determined whether unit 6 is an oblique extreme value. When the unit 6 is an oblique extreme value, the distance and speed of the target can be determined based on the position of the unit 6 in the spectrum diagram. For another example, as shown in FIG11(b), the target distribution line passes through cell 6, and its corresponding two reference cells (i.e., cell 1 and cell 11) are located on either side of the target distribution line, and the perpendicular line of the target distribution line corresponding to cell 6 intersects with cell 1 and cell 11. For another example, the first reference line corresponding to the cell under test can be determined based on the slope of the target distribution line of the stationary extended target on the two-dimensional spectrum graph.

[0106] Because the slope of the target distribution line is related to the step bandwidth of the stepped FMCW, and the reference cells are distributed on the perpendicular line of the target distribution line, the energy amplitude of the reference cells can be regarded as an extension of the target energy itself. In this embodiment of the present application, the reference cells of each unit under test can be determined based on the characteristics of the stepped FMCW signal, and then the extreme value cells can be determined. This can improve the reported point data of the FMCW waveform, thereby fully utilizing the data of the radar point cloud and improving the target contour estimation and classification recognition capabilities.

[0107] For ease of explanation, the following briefly introduces the method for determining extreme value units involved in FIG. 10 and FIG. 11 in the scenario shown in FIG. 8 in conjunction with FIG. 12 .

[0108] Exemplarily, FIG12 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application. For example, according to (a) in FIG10 , the target distribution line can be determined, and in combination with (b) in FIG10 , the unit corresponding to the target #1 and the unit to be tested therein can be determined. The reference unit of each unit to be tested can be determined by the method in FIG9 , and when the energy amplitude of each unit to be tested is greater than the energy amplitude of its reference unit, the unit to be tested is determined as an oblique extreme value. In one embodiment, as shown in FIG12 , units 6, 10, 15, 20 and 24 are oblique extreme values. It should be understood that units 6, 10 and 20 are also the two-dimensional extreme value units in (c) in FIG8 . In other words, the number of extreme value units determined by the oblique extreme value can be greater than or equal to the number of the determined two-dimensional extreme value units, and can be greater than or equal to the number of extended targets, thereby avoiding omission. In an embodiment of the present application, by determining the oblique extreme value, the reporting point data can be improved according to the stepping method adopted by the detection signal.

[0109] For example, Figure 13 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application. Among them, Figure 13 takes the lower stepped FMCW signal as an example, and briefly introduces a method for determining the speed and distance of a larger target (for example, recorded as target #2) using the signal processing method involved in Figure 10. As shown in (a) in Figure 13, when the lower stepped FMCW signal is adopted, the extended target corresponding to the target #2 is distributed in a slanted shape in the two-dimensional spectrum diagram. The result of the CFAR processing of the extended target can be shown in (b) in Figure 13. In one embodiment, as shown in (c) in Figure 13, units 5, 10, 15, 20 and 25 are inverse slant extreme values, and units 6, 10 and 20 are two-dimensional extreme value units. In the embodiment of the present application, the use of inverse slant extreme values ​​to determine the speed and distance of the target #2 can combine the characteristics of the FMCW signal to improve the reported point data of the FMCW waveform, thereby making full use of the data of the radar point cloud.

[0110] In some possible implementations, when the step bandwidth is not equal to the single chirp bandwidth, using the diagonal cells of the unit under test (i.e., the upper left and lower right cells, or the lower left and upper right cells) as the reference cells for the unit under test may result in an extension of the adjacent target, leading to incorrect peak aggregation judgments. Interpolation can be performed in the fast time dimension so that the line connecting the diagonal cells of the unit under test is perpendicular to the target distribution line.

[0111] Exemplarily, Figure 14 is a schematic diagram of another signal processing scenario provided by an embodiment of the present application. (a) in Figure 14 shows the distribution of the extended target in the two-dimensional spectrum diagram when the step bandwidth is not equal to the single chirp bandwidth in the case of an upper stepped FMCW signal. As shown in (b) in Figure 14, in the result of the CFAR processing of the extended target, the line connecting the upper left unit and the lower right unit of the target to be measured is not perpendicular to the target distribution line. In one embodiment, as shown in (c) in Figure 14, units 8, 9, 12 and 13 are oblique extreme values, and units 8 and 9 are two-dimensional extreme value units. Since the line connecting the upper left unit and the lower right unit of the target to be measured is not perpendicular to the target distribution line, the process of determining the extreme value unit in this way may be interfered with by nearby targets.

[0112] In order to avoid this situation, FFT interpolation can be performed in the fast time dimension, that is, the sampling data of the stepped FMCW can be padded with zeros so that the line connecting the diagonal units of the unit to be tested is perpendicular to the target distribution line. For example, by performing FFT interpolation in the fast time dimension, the distribution of the target in the distance-speed dimension spectrum can be shown as (d) in Figure 14. For another example, by performing CFAR processing on (d) in Figure 14, the result shown in (e) in Figure 14 can be obtained. As shown in (e) in Figure 14, the unit to be tested located on the target distribution line can be perpendicular to the line connecting the upper left unit and the lower right unit adjacent to it. Accordingly, it can be determined that units 6, 10, 15 and 19 are oblique extreme values, among which units 6, 10, and 19 are two-dimensional extreme values. In this way, the probability of peak judgment error can be reduced.

[0113] For example, FIG15 is a flow chart of a signal processing method provided by an embodiment of the present application. The method 400 may include some or all of the following steps:

[0114] S410: Determine whether the step bandwidth is zero.

[0115] Exemplarily, it may be determined whether the step bandwidth is zero based on ADC sampling data and / or system parameters, that is, whether a stepped FMCW signal is used.

[0116] When the step bandwidth is zero, step S420 may be executed; or, when the step bandwidth is greater than zero, step S440 may be executed; or, when the step bandwidth is less than zero, step S450 may be executed.

[0117] That is, when the step frequency is zero, step S420 may be executed; or, when the step frequency is greater than zero, step S440 may be executed; or, when the step frequency is less than zero, step S450 may be executed.

[0118] S420: Perform FFT in the fast time dimension and the slow time dimension.

[0119] Exemplarily, when the step frequency of the adopted FMCW signal is zero, FFT of the fast time dimension and the slow time dimension may be performed according to the method in FIG6 and / or FIG7 to obtain a range-Doppler dimension spectrum diagram.

[0120] When performing one-dimensional extreme value comparison, step S422 may be executed; when performing cross extreme value comparison, step S426 may be executed.

[0121] S422, comparing the energy amplitudes of the unit to be tested and its two adjacent units on the left / right.

[0122] Exemplarily, the left and right adjacent units of the unit to be tested may be used as reference units of the unit to be tested.

[0123] S424, obtain one-dimensional extreme value.

[0124] When the amplitude of the unit under test is greater than the amplitude of its reference unit, the unit under test can be determined as a one-dimensional extreme unit. For example, as shown in (c) of Figure 6, unit 2 can be determined as a one-dimensional extreme unit based on the amplitudes of unit 2 and its reference units (i.e., unit 1 and unit 3).

[0125] S426 , comparing the energy amplitudes of the unit under test with the four adjacent units above / below / left / right thereof.

[0126] For example, four adjacent cells above, below, left, and right of the unit to be tested may be used as reference cells.

[0127] In some possible implementations, when determining a cross extreme value, two adjacent one-dimensional extreme value units above / below the one-dimensional extreme value unit to be measured may be used as reference units.

[0128] S428, obtain the cross extreme value.

[0129] When the amplitude of the unit under test is greater than the amplitude of its reference unit, the unit under test can be determined as a two-dimensional extreme value unit. For example, as shown in (c) of Figure 6, units 2, 5, and 8 are one-dimensional extreme value units. When the amplitude of unit 5 is greater than the amplitudes of units 2 and 8, unit 5 can be determined as a two-dimensional extreme value.

[0130] Exemplarily, when Δf is greater than zero, the detection signal adopts an upward stepping mode, and step S440 may be executed. For example, the extreme value unit may be determined according to the method in any of the embodiments in FIG. 10 to FIG. 13 .

[0131] Exemplarily, when Δf is less than zero, the detection signal adopts a down-stepping mode, and step S450 may be executed. For example, the extreme value unit may be determined according to the method embodiment in FIG10 or FIG13 .

[0132] S440: Determine whether the step bandwidth (denoted as Bs) is equal to the single chirp bandwidth (denoted as Bc).

[0133] When Bs is equal to Bc, step S442 may be executed; or, when Bs is not equal to Bc, step S444 may be executed.

[0134] S442, perform two-dimensional FFT.

[0135] A two-dimensional FFT can be used to obtain a range-Doppler spectrum, and the distribution of targets within this spectrum can be determined. For example, a two-dimensional spectrum such as that shown in Figure 8(a) can be obtained. This means that FFT calculations can be performed without interpolating the return signal of the detection signal.

[0136] S444 , performing zero padding processing in the fast time dimension so that the ratio between the number of zero-padded data (for example, denoted as Mpad) and the number of FMCW sampling data (for example, denoted as M) is equal to Bs / Bc.

[0137] For example, when Mpad / M is equal to Bs / Bc through interpolation and zero padding, the connection line between the diagonally opposite reference units of each unit under test can be made perpendicular to the target distribution line.

[0138] S446, perform two-dimensional FFT.

[0139] In one embodiment, by performing zero padding and then performing a two-dimensional FFT, a two-dimensional spectrum diagram as shown in (d) of Figure 14 can be obtained. In other words, through steps S444 and S446, FFT interpolation calculation of the return signal of the detection signal can be implemented.

[0140] S448, comparing the amplitudes of the unit under test with its two adjacent units to the upper left and lower right.

[0141] In one embodiment, as shown in (a) of FIG10 , when an upward-stepped FMCW signal is used, the reference units of the unit under test are the upper left unit and the lower right unit thereof.

[0142] S449, obtain the oblique extreme value.

[0143] For example, by comparing the amplitude of each unit under test with its reference unit in the spectrum graph, multiple slant extreme values ​​in the spectrum graph can be obtained. For example, as shown in FIG12 , the slant extreme values ​​are units 6, 10, 15, 20, and 24.

[0144] S450, determine whether Bs is equal to Bc.

[0145] When Bs is equal to Bc, step S452 may be executed; or, when Bs is not equal to Bc, step S454 may be executed.

[0146] S452, perform two-dimensional FFT.

[0147] S454 , performing zero padding processing in the fast time dimension so that the ratio between the number of zero-padded data (denoted as Mpad) and the number of FMCW sampling data (denoted as M) is equal to Bs / Bc.

[0148] S456, perform two-dimensional FFT.

[0149] S458, comparing the amplitudes of the unit under test with its two adjacent units to the lower left and upper right.

[0150] S459, obtain the anti-skew extreme value.

[0151] In some possible implementation scenarios, when performing zero-padding processing, the sum of the number of zero-padding data and the number of FMCW sampling data can be approximately an integer power of 2, so as to facilitate adaptation to the FFT acceleration algorithm.

[0152] The method provided in the embodiments of the present application is described in detail above with reference to Figures 3 to 15 . The apparatus provided in the embodiments of the present application will be described in detail below with reference to Figures 16 and 17 . The description of the apparatus embodiment corresponds to the description of the method embodiment. Therefore, any details not described in detail can be referred to in the method embodiment above.

[0153] For example, FIG16 shows a schematic block diagram of a signal processing device 1000 (hereinafter referred to as device 1000 ) provided in an embodiment of the present application. The device may include a control unit 1010 and a processing unit 1020 .

[0154] The apparatus 1000 may include a unit for executing any one of the methods in FIG. 3 to FIG. 15 , and each unit in the apparatus 1000 may be used to execute a corresponding process in any one of the method embodiments in FIG. 3 to FIG. 15 .

[0155] When the device 1000 is used to execute the method 300 in FIG. 9 , the control unit 1010 may be used to execute step S310 in the method 300 , and the processing unit 1020 may be used to execute steps S320 and S350 in the method 300 .

[0156] Specifically, the control unit 1010 can be used to control the detection device to transmit a detection signal, which includes multiple bursts; the processing unit 1020 can be used to determine the step bandwidth of the detection signal; when the step bandwidth is zero, the first method is used to perform extreme value comparison on the unit to be tested, and the unit to be tested is a unit whose energy amplitude is greater than or equal to the first threshold, and the unit to be tested belongs to the first spectrum diagram, which is obtained by spectrum analysis of the return signal of the detection signal; or, when the step bandwidth is greater than zero, the second method is used to perform extreme value comparison on the unit to be tested; or, when the step bandwidth is less than zero, the third method is used to perform extreme value comparison on the unit to be tested.

[0157] Exemplarily, the device 1000 may be the radar sensor in FIG. 2 , or may be the vehicle in FIG. 2 , or may be a terminal in the vehicle for performing signal processing on the radar (such as the computing platform in FIG. 1 ), or may be a processor or chip in the terminal.

[0158] Optionally, the processing unit 1020 can be used to determine a first reference line corresponding to the unit under test, where the slope of the first reference line is determined based on the step bandwidth of the detection signal; determine a reference unit corresponding to the unit under test based on the first reference line; and perform extreme value comparison between the unit under test and the reference unit corresponding to the unit under test.

[0159] Optionally, the processing unit 1020 can be used to, when the step bandwidth of the detection signal is the same as the bandwidth of the burst, select the upper left and lower right units of the unit to be tested for extreme value comparison; or, when the step bandwidth of the detection signal is different from the bandwidth of the burst, perform FFT interpolation calculation on the return signal of the detection signal, and select the upper left and lower right units of the unit to be tested for extreme value comparison.

[0160] Optionally, the processing unit 1020 can be used to, when the step bandwidth of the detection signal is the same as the bandwidth of the burst, select the lower left and upper right units of the unit to be tested for extreme value comparison; or, when the step bandwidth of the detection signal is different from the bandwidth of the burst, perform FFT interpolation calculation on the return signal of the detection signal, and select the lower left and upper right units of the unit to be tested for extreme value comparison.

[0161] Optionally, the detection signal is a stepped frequency modulated continuous wave (FMCW) signal, which includes multiple chirps, each of the multiple bursts is a chirp, and the bandwidth of the chirp is a single chirp bandwidth. The processing unit 1020 can be used to determine the first reference line corresponding to the unit to be tested based on the ratio of the stepped bandwidth to the single chirp bandwidth.

[0162] Optionally, the processing unit 1020 may be configured to obtain sampling data of the return signal of the detection signal; and perform FFT on the sampling data and N data with a value of zero to obtain the first spectrum diagram.

[0163] Optionally, the ratio of N to the number of sampled data is equal to the ratio of the step bandwidth to the burst bandwidth.

[0164] Optionally, the sum of N and the sampled data is an integer power of 2.

[0165] Optionally, the processing unit 1020 may be configured to select two left and right units of the unit to be tested for extreme value comparison; or select four upper, lower, left and right units of the unit to be tested for extreme value comparison.

[0166] It should be understood that the division of the various units in the above devices is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a single physical entity, or physically separated. All units in the above devices may be implemented entirely through a processor calling software, entirely through hardware circuits, or partially through a processor calling software, with the remainder implemented through hardware circuits.

[0167] In a specific implementation process, the control unit 1010 can be implemented by at least one transceiver or transceiver-related circuits, and the processing unit 1020 can be implemented by at least one processor or processor-related circuits. In one example, one or more processors can determine the step bandwidth of the detection signal. In one example, one or more processors can use a first method to perform extreme value comparison on the unit under test. In one example, one or more processors can use a second method to perform extreme value comparison on the unit under test. Exemplarily, in a specific implementation process, the device 1000 can be the vehicle shown in FIG2 , or a signal processing device provided in the vehicle, or a processor or chip provided in the vehicle. In another embodiment, the device can be the intelligent driving device 100 in FIG1 , or a chip or processor provided in the intelligent driving device.

[0168] For example, FIG17 is a schematic block diagram of another control device 2000 (hereinafter referred to as device 2000) provided in an embodiment of the present application. The device 2000 may include: a processor 2010, an interface circuit 2020, and a memory 2030. The processor 2010, the interface circuit 2020, and the memory 2030 are connected via an internal connection path. The memory 2030 is used to store instructions, and the processor 2010 is used to execute the instructions stored in the memory 2030 and receive / send some parameters through the interface circuit 2020. Optionally, the memory 2030 can be coupled to the processor 2010 via an interface or integrated with the processor 2010.

[0169] In some possible implementations, the apparatus 2000 may be provided in the intelligent driving device 100 shown in FIG. 1 .

[0170] It should be noted that the interface circuit 2020 may include, but is not limited to, a transceiver device such as an input / output interface to enable communication between the device 2000 and other devices or communication networks. For example, communication with a radar and / or internal circuits of an intelligent driving device may be achieved through the interface circuit 2020.

[0171] An embodiment of the present application further provides a signal processing system, which includes a radar and the above-mentioned device 1000 or device 2000.

[0172] An embodiment of the present application also provides a computer program product, which includes: computer program code, which, when running on a computer, enables the computer to execute any one of the method embodiments in Figures 4 to 9 above, and any possible implementation thereof.

[0173] An embodiment of the present application also provides a computer-readable storage medium, which stores program code or instructions. When the computer program code or instructions are executed by a computer processor, the processor implements any method embodiment in Figures 3 to 15 above, and any possible implementation method thereof.

[0174] An embodiment of the present application also provides a chip, including a circuit, for executing any method embodiment in Figures 3 to 15 above, and any possible implementation thereof.

[0175] An embodiment of the present application also provides a cloud server, which may include the above-mentioned device 1000 or the above-mentioned device 2000.

[0176] It should be understood that for the convenience and brevity of description, the specific working processes and beneficial effects of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0177] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0178] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0179] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0180] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0181] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0182] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk, or an optical disk.

[0183] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A signal processing method, characterized in that: include: Controlling the detection device to transmit a detection signal, wherein the detection signal includes a plurality of bursts; determining a step bandwidth of the detection signal; When the step bandwidth is zero, a first method is used to perform extreme value comparison on a unit to be tested, wherein the unit to be tested is a unit whose energy amplitude is greater than or equal to a first threshold value, and the unit to be tested belongs to a first spectrum diagram, and the first spectrum diagram is obtained by spectrum analysis of a return signal of the detection signal; or When the step bandwidth is greater than zero, the second method is used to perform extreme value comparison on the unit under test; or, When the step bandwidth is less than zero, a third method is used to perform extreme value comparison on the unit under test.

2. The method according to claim 1, characterized in that The adopting the second method to compare the extreme values ​​of the unit under test, or the adopting the third method to compare the extreme values ​​of the unit under test, includes: Determine a first reference line corresponding to the unit under test, wherein the slope of the first reference line is determined according to the step bandwidth of the detection signal; Determine a reference unit corresponding to the unit under test according to the first reference line; An extreme value comparison is performed between the unit under test and a reference unit corresponding to the unit under test.

3. The method according to claim 1 or 2, characterized in that The adopting the second method to compare the extreme values ​​of the unit under test includes: When the step bandwidth of the detection signal is the same as the bandwidth of the burst, selecting the upper left and lower right units of the unit to be tested for extreme value comparison; or, When the step bandwidth of the detection signal is different from the burst bandwidth, a Fast Fourier Transform (FFT) interpolation calculation is performed on the return signal of the detection signal, and the upper left and lower right units of the unit to be tested are selected for extreme value comparison.

4. The method according to claim 1 or 2, characterized in that: The adopting the third method to compare the extreme values ​​of the unit under test includes: When the step bandwidth of the detection signal is the same as the bandwidth of the burst, selecting the lower left and upper right units of the unit to be tested for extreme value comparison; or, When the step bandwidth of the detection signal is different from the burst bandwidth, a Fast Fourier Transform (FFT) interpolation calculation is performed on the return signal of the detection signal, and the lower left and upper right units of the unit to be tested are selected for extreme value comparison.

5. The method according to any one of claims 2 to 4, characterized in that The detection signal is a stepped frequency modulated continuous wave (FMCW) signal, the stepped FMCW signal includes a plurality of chirps, each of the plurality of bursts is a chirp, the bandwidth of the chirp is a single chirp bandwidth, and determining the first reference line corresponding to the unit under test includes: The first reference line corresponding to the unit under test is determined according to the ratio of the step bandwidth to the single chirp bandwidth.

6. The method according to claim 3 or 4, characterized in that The performing fast Fourier transform (FFT) interpolation calculation on the return signal of the detection signal comprises: Acquiring sampling data of a return signal of the detection signal; Perform fast Fourier transform on the sampled data and N data with values ​​of zero to obtain the first spectrum diagram.

7. The method according to claim 6, characterized in that The ratio of N to the number of sampled data is equal to the ratio of the step bandwidth to the burst bandwidth.

8. The method according to claim 6 or 7, characterized in that The sum of N and the sample data is an integer power of 2.

9. The method according to claim 1, characterized in that The adopting the first method to perform extreme value comparison on the unit under test includes: Selecting two units on the left and right of the unit to be tested for extreme value comparison; or, Four upper, lower, left and right units of the unit to be tested are selected for extreme value comparison.

10. A signal processing device, characterized in that: include: A control unit, used for controlling the detection device to transmit a detection signal, wherein the detection signal includes a plurality of bursts; A processing unit, configured to determine a step bandwidth of the detection signal; When the step bandwidth is zero, a first method is used to perform extreme value comparison on a unit to be tested, wherein the unit to be tested is a unit whose energy amplitude is greater than or equal to a first threshold value, and the unit to be tested belongs to a first spectrum diagram, and the first spectrum diagram is obtained by spectrum analysis of a return signal of the detection signal; or When the step bandwidth is greater than zero, the second method is used to perform extreme value comparison on the unit under test; or, When the step bandwidth is less than zero, a third method is used to perform extreme value comparison on the unit under test.

11. The device according to claim 10, characterized in that The processing unit is used for: Determine a first reference line corresponding to the unit under test, wherein the slope of the first reference line is determined according to the step bandwidth of the detection signal; Determine a reference unit corresponding to the unit under test according to the first reference line; An extreme value comparison is performed between the unit under test and a reference unit corresponding to the unit under test.

12. The device according to claim 10 or 11, characterized in that The processing unit is used for: When the step bandwidth of the detection signal is the same as the bandwidth of the burst, selecting the upper left and lower right units of the unit to be tested for extreme value comparison; or, When the step bandwidth of the detection signal is different from the burst bandwidth, a Fast Fourier Transform (FFT) interpolation calculation is performed on the return signal of the detection signal, and the upper left and lower right units of the unit to be tested are selected for extreme value comparison.

13. The device according to claim 10 or 11, characterized in that The processing unit is used for: When the step bandwidth of the detection signal is the same as the bandwidth of the burst, selecting the lower left and upper right units of the unit to be tested for extreme value comparison; or, When the step bandwidth of the detection signal is different from the burst bandwidth, a Fast Fourier Transform (FFT) interpolation calculation is performed on the return signal of the detection signal, and the lower left and upper right units of the unit to be tested are selected for extreme value comparison.

14. The device according to any one of claims 11 to 13, characterized in that The detection signal is a stepped frequency modulated continuous wave (FMCW) signal, the stepped FMCW signal includes a plurality of chirps, each of the plurality of bursts is a chirp, the bandwidth of the chirp is a single chirp bandwidth, and the processing unit is configured to: The first reference line corresponding to the unit under test is determined according to the ratio of the step bandwidth to the single chirp bandwidth.

15. The device according to claim 12 or 13, characterized in that The processing unit is used for: Acquiring sampling data of a return signal of the detection signal; Perform fast Fourier transform on the sampled data and N data with values ​​of zero to obtain the first spectrum diagram.

16. The device according to claim 15, characterized in that The ratio of N to the number of sampled data is equal to the ratio of the step bandwidth to the burst bandwidth.

17. The device according to claim 15 or 16, characterized in that The sum of N and the sample data is an integer power of 2.

18. The device according to claim 10, characterized in that The processing unit is used for: Selecting two units on the left and right of the unit to be tested for extreme value comparison; or, Four upper, lower, left and right units of the unit to be tested are selected for extreme value comparison.

19. A signal processing device, characterized in that: The device comprises: Memory for storing computer programs; A processor, configured to execute the computer program stored in the memory, so that the apparatus performs the method according to any one of claims 1 to 9.

20. A signal processing system, characterized in that: The system comprises a radar and a computing platform, wherein the computing platform comprises the apparatus according to any one of claims 10 to 19.

21. An intelligent driving device, characterized in that: The intelligent driving device comprises the apparatus as described in any one of claims 10 to 19, or comprises the system as described in claim 20.

22. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a computer, the method according to any one of claims 1 to 9 is implemented.

23. A computer program product, characterized in that The computer program product comprises a computer program code. When the computer program code is run on a computer, the method according to any one of claims 1 to 9 is executed.

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