Signal processing method and apparatus, storage medium, and vehicle

Abstract

The application belongs to the technical field of sensors and relates to a signal processing method and device, a storage medium and a vehicle. The method comprises the following steps: processing a first received signal to determine first time domain data; performing filtering processing on the first time domain data by using a mismatch filter to obtain first distance spectrum data; obtaining first distance detection data according to the first distance spectrum data; and determining second detection data according to the first distance detection data and first detection data obtained from the first received signal. According to the signal processing method, the accuracy of detecting the first received signal can be improved, the advanced driver assistance system (ADAS) capability of a terminal in automatic driving or auxiliary driving can be improved, the method can be used for target detection and tracking in auxiliary driving and automatic driving, and the method can be applied to vehicle networking, such as vehicle external connection (V2X), inter-vehicle communication long term evolution (LTE-V), vehicle-to-vehicle (V2V) and the like.

Description

Technical Field

[0001] This application relates to the field of sensor technology, and in particular to a signal processing method, apparatus, storage medium, and vehicle. Background Technology

[0002] With societal development, intelligent transportation equipment, smart home devices, robots, and other intelligent terminals are gradually entering people's daily lives. Sensors play a crucial role in these intelligent terminals. Various sensors installed on intelligent terminals, such as millimeter-wave radar, lidar, cameras, and ultrasonic radar, perceive the surrounding environment, collect data, identify and track moving objects, and recognize stationary scenes such as lane lines and signs. They then combine this information with navigation and map data for path planning. Sensors can anticipate potential hazards and assist or even autonomously take necessary avoidance measures, effectively increasing the safety and comfort of intelligent terminals.

[0003] Taking intelligent terminals as an example of intelligent transportation equipment, millimeter-wave radar has become the primary sensor for autonomous driving systems and driver assistance systems due to its lower cost and more mature technology. Currently, Advanced Driver Assistance Systems (ADAS) have developed more than ten functions, among which Adaptive Cruise Control (ACC), Autonomous Emergency Braking (AEB), Lance Change Assist (LCA), and Blind Spot Monitoring (BSD) all rely on millimeter-wave radar. Millimeter waves generally refer to electromagnetic waves with wavelengths between 1-10 mm, corresponding to a frequency range of 30-300 GHz. Within this frequency band, the characteristics of millimeter waves are very suitable for application in the automotive field. For example, it has a large bandwidth, abundant frequency domain resources, and low antenna sidelobes, which is conducive to imaging or quasi-imaging; short wavelength, which reduces the size of radar equipment and antenna aperture, and lightens the weight; narrow beam, with millimeter wave beams being much narrower than microwave beams for the same antenna size, resulting in higher radar resolution; and strong penetration, which is more capable of penetrating smoke, dust and fog compared to lidar and optical systems, and can work in all weather conditions.

[0004] In the use of millimeter-wave radar, the distance between the target and the radar can be determined by transmitting a signal and analyzing the received echo signal reflected from the target. However, due to the influence of the radar's environment, the effective signal in the echo signal may be interfered with by other large-amplitude signals during the echo signal analysis process, making it difficult for millimeter-wave radar to measure the accurate distance. Under these circumstances, improving detection accuracy is a pressing technical problem that needs to be solved. Summary of the Invention

[0005] In view of this, a signal processing method, apparatus, storage medium, and vehicle are proposed. The signal processing method according to the embodiments of this application can reduce the interference of large-amplitude signals and improve the accuracy of echo signal detection.

[0006] In a first aspect, embodiments of this application provide a signal processing method, the method comprising:

[0007] A first received signal is acquired, and the first received signal is processed to obtain two-dimensional distance and velocity spectrum data; based on the two-dimensional distance and velocity spectrum data, first time-domain data is determined; the first time-domain data is filtered using a mismatch filter to obtain first distance spectrum data, wherein the parameters of the mismatch filter are determined based on the time-domain data of a second received signal or the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal; based on the first distance spectrum data, first distance detection data is obtained; based on the first distance detection data and the first detection data obtained from the first received signal, second detection data is determined.

[0008] According to the signal processing method of this application embodiment, the parameters of a mismatch filter can be determined based on the time-domain data of the second received signal or the two-dimensional spectrum data of distance and velocity with the maximum amplitude in the first received signal. The first time-domain data can then be filtered using this mismatch filter to obtain first distance spectrum data. Second detection data can be obtained based on the first distance detection data obtained from the first distance spectrum data and the first detection data obtained from the first received signal. Since the first and second received signals are acquired after passing through the environment of signal generation, transmission, and reception, signal processing based on the mismatch filter determined from the first and second received signals can eliminate the influence of non-ideal characteristics of physical factors in the environment of signal generation, transmission, and reception in the first received signal, thus improving the sidelobe suppression effect. Furthermore, since the second detection data is determined by the first detection data and the first distance detection data of the first received signal, the second detection data contains information from both the first detection data and the first distance detection data, and therefore has high accuracy. When applied to detection devices such as radar, more accurate environmental information can be obtained, improving the detection accuracy of the detection device; when the detection device is applied to automobiles, it can improve the information processing capabilities of the automobile system.

[0009] According to the first aspect, in a first possible implementation of the signal processing method, the second received signal is a transmitted leakage signal.

[0010] In this way, the mismatch filter parameters can be determined before the first received signal is received, and the detection can be completed using the mismatch filter when the first received signal is received, thereby obtaining detection data with high accuracy and high detection efficiency.

[0011] According to a first possible implementation of the first aspect, in a second possible implementation of the signal processing method, the method includes: determining the maximum amplitude of the range sidelobe in the second received signal based on time-domain data of the second received signal; determining desired filtered data of the second received signal based on the maximum amplitude of the range sidelobe in the second received signal, wherein the amplitude of the range sidelobe in the desired filtered data is lower than the maximum amplitude of the range sidelobe in the second received signal; and determining the parameters of the mismatch filter based on the time-domain data of the second received signal and the desired filtered data of the second received signal.

[0012] In this way, it is possible to obtain mismatch filter parameters that achieve ideal signal-to-noise ratio loss and sidelobe amplitude after filtering. The mismatch filter parameters determined by the above method are those that make the time-domain data of the transmitted leakage signal close to the desired filtered data. Using these mismatch filter parameters to filter the data allows the processing trend from the transmitted leakage signal to the desired filtered data to be applied to the data processing process, thus ensuring the processing effect of the mismatch filter.

[0013] According to the first aspect, in a third possible implementation of the signal processing method, the method includes: obtaining distance spectrum data of the maximum amplitude in the first received signal based on two-dimensional distance and velocity spectrum data of the maximum amplitude in the first received signal; and determining the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal.

[0014] In this way, the mismatch filter parameters can be determined based on the range spectrum data of the maximum amplitude of the first received signal, and the first time domain data is determined based on the data information of the first received signal. When the first time domain data is filtered using the mismatch filter parameters, more accurate first range spectrum data can be obtained.

[0015] According to the third possible implementation of the first aspect, in the fourth possible implementation of the signal processing method, determining the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal includes:

[0016] Based on the range spectrum data of the maximum amplitude in the first received signal, the maximum amplitude of the range dimension sidelobe in the first received signal is determined; based on the maximum amplitude of the range dimension sidelobe in the first received signal, the expected filtered data of the maximum amplitude signal in the first received signal is determined, wherein the amplitude of the range dimension sidelobe of the expected filtered data is lower than the maximum amplitude of the range dimension sidelobe in the first received signal; based on the range spectrum data of the maximum amplitude in the first received signal and the expected filtered data of the maximum amplitude signal in the first received signal, the parameters of the mismatch filter are determined.

[0017] By selecting the distance spectrum data with the maximum amplitude in the first received signal, the determined mismatch filter parameters can be made more accurate.

[0018] According to the first aspect, in a fifth possible implementation of the signal processing method, determining the first time-domain data based on the distance and velocity two-dimensional spectrum data includes:

[0019] Based on the transmitted signal, an inversion matrix is ​​constructed; based on the two-dimensional range and velocity spectrum data, second range spectrum data is determined; based on the second range spectrum data and the inversion matrix, first time domain data is determined.

[0020] In this way, all the data information in the first time-domain data comes from the first received signal. After filtering the first time-domain data, the distance information of the target of the first received signal can be obtained. Furthermore, the data rate of the retrieved first time-domain data is relatively low, which can reduce the cost of the mismatch filtering process.

[0021] According to the fifth possible implementation of the first aspect, in the sixth possible implementation of the signal processing method, determining the second range spectrum data based on the range and velocity two-dimensional spectrum data includes:

[0022] Based on the two-dimensional range and velocity spectrum data, the range dimension sidelobe amplitude of the signal in the first received signal is determined; signals with range dimension sidelobe amplitudes greater than or equal to an amplitude threshold are identified as target signals; based on the range spectrum data of the Doppler unit where the target signal is located in the two-dimensional range and velocity spectrum data, the second range spectrum data is determined.

[0023] In this way, mismatch filtering can be performed on the range spectrum data of Doppler units with high sidelobe amplitudes in the range dimension, which can reduce the data cost of mismatch filtering.

[0024] According to the first aspect, in a seventh possible implementation of the signal processing method, the method includes: determining the Doppler cell containing the maximum amplitude signal in the first received signal based on the distance and velocity two-dimensional spectrum data of the first received signal; and extracting the distance and velocity two-dimensional spectrum data of the Doppler cell containing the maximum amplitude signal in the first received signal from the distance and velocity two-dimensional spectrum data of the first received signal, as the distance and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal.

[0025] In this way, the data used to determine the mismatch filter parameters can correspond to the maximum amplitude signal in the first received signal, thereby improving the accuracy of the mismatch filter parameters.

[0026] According to the first aspect, and any possible implementation of the first aspect above, in an eighth possible implementation of the signal processing method, the first detection data includes distance detection and / or velocity detection data, and the second detection data is determined based on the first distance detection data and the first detection data obtained from the first received signal, including:

[0027] The second detection data is obtained by replacing the distance detection data in the first detection data with the first distance detection data, or by performing an OR operation on the first distance detection data and the first detection data.

[0028] This approach increases the flexibility of obtaining second detection data. Furthermore, using a substitution method to obtain second detection data improves its accuracy, while using an OR operation method avoids missed detections.

[0029] Secondly, embodiments of this application provide a signal processing apparatus, the apparatus comprising:

[0030] The first acquisition module is used to acquire a first received signal and process the first received signal to obtain two-dimensional spectrum data of distance and velocity.

[0031] The first determining module is used to determine the first time-domain data based on the distance and velocity two-dimensional spectrum data;

[0032] The processing module is used to filter the first time-domain data using a mismatch filter to obtain first distance spectrum data, wherein the parameters of the mismatch filter are determined based on the time-domain data of the second received signal or the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal.

[0033] The second acquisition module is used to obtain first distance detection data based on the first distance spectrum data;

[0034] The second determining module is used to determine the second detection data based on the first distance detection data and the first detection data obtained from the first received signal.

[0035] The signal processing apparatus according to the embodiments of this application can obtain second detection data with high accuracy. This enables the acquisition of more accurate environmental information and improves detection accuracy.

[0036] According to the second aspect, in a first possible implementation of the signal processing device, the second received signal is a transmitted leakage signal.

[0037] According to the first possible implementation of the second aspect, in the second possible implementation of the signal processing apparatus, the apparatus includes:

[0038] The third determining module is used to determine the maximum amplitude of the range-dimensional sidelobe in the second received signal based on the time-domain data of the second received signal.

[0039] The fourth determining module is used to determine the desired filtered data of the second received signal based on the maximum amplitude of the range dimension sidelobe in the second received signal, wherein the amplitude of the range dimension sidelobe of the desired filtered data is lower than the maximum amplitude of the range dimension sidelobe in the second received signal.

[0040] The fifth determining module is used to determine the parameters of the mismatch filter based on the time-domain data of the second received signal and the expected filtering data of the second received signal.

[0041] According to the second aspect, in a third possible implementation of the signal processing apparatus, the apparatus further includes:

[0042] The third acquisition module is used to acquire the distance spectrum data with the maximum amplitude in the first received signal based on the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal.

[0043] The sixth determining module is used to determine the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal.

[0044] According to the third possible implementation of the second aspect, in the fourth possible implementation of the signal processing device, the sixth determining module includes:

[0045] The first determining submodule is used to determine the maximum amplitude of the range dimension sidelobe in the first received signal based on the range spectrum data with the maximum amplitude in the first received signal.

[0046] The second determining submodule is used to determine the expected filtered data of the maximum amplitude signal in the first received signal based on the maximum amplitude of the range dimension sidelobe in the first received signal, wherein the amplitude of the range dimension sidelobe of the expected filtered data is lower than the maximum amplitude of the range dimension sidelobe in the first received signal.

[0047] The third determining submodule is used to determine the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal and the expected filtering data of the maximum amplitude signal in the first received signal.

[0048] According to the second aspect, in a fifth possible implementation of the signal processing apparatus, the first determining module includes:

[0049] The fourth determination submodule is used to construct the inversion matrix based on the transmitted signal;

[0050] The fifth determining submodule is used to determine the second distance spectrum data based on the distance and velocity two-dimensional spectrum data;

[0051] The sixth determining submodule is used to determine the first time-domain data based on the second distance spectrum data and the inversion matrix.

[0052] According to the fifth possible implementation of the second aspect, in the sixth possible implementation of the signal processing device, determining the second range spectrum data based on the range and velocity two-dimensional spectrum data includes:

[0053] Based on the distance and velocity two-dimensional spectral data, the range dimension sidelobe amplitude of the signal in the first received signal is determined;

[0054] Signals whose sidelobe amplitude is greater than or equal to the amplitude threshold in the distance dimension are identified as target signals.

[0055] The second range spectrum data is determined based on the range spectrum data of the Doppler unit where the target signal is located in the two-dimensional range and velocity spectrum data.

[0056] According to the second aspect, in a seventh possible implementation of the signal processing apparatus, the apparatus further includes:

[0057] The seventh determining module is used to determine the Doppler unit where the maximum amplitude signal in the first received signal is located based on the two-dimensional spectrum data of distance and velocity of the first received signal;

[0058] The eighth determining module is used to extract the distance and velocity two-dimensional spectrum data of the Doppler unit where the maximum amplitude signal in the first received signal is located from the distance and velocity two-dimensional spectrum data of the first received signal, and use it as the distance and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal.

[0059] According to the second aspect, and any possible implementation of the second aspect above, in an eighth possible implementation of the signal processing device, the first detection data includes distance detection and / or velocity detection data.

[0060] The second determining module includes:

[0061] The seventh determining submodule is used to replace the distance detection data in the first detection data with the first distance detection data to obtain the second detection data, or...

[0062] The eighth determination submodule is used to perform an OR operation on the first distance detection data and the first detection data to obtain the second detection data.

[0063] Thirdly, embodiments of this application provide a signal processing apparatus, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform one or more of the signal processing methods described in the first aspect or various possible implementations of the first aspect.

[0064] The signal processing apparatus according to the embodiments of this application can obtain second detection data with higher accuracy, and the information such as the distance and speed of the target determined based on the second detection data is also more accurate. When the signal processing apparatus is applied to automobiles, it can be used for target detection and tracking in assisted driving and autonomous driving, thereby improving the information processing capabilities of the vehicle system.

[0065] Fourthly, embodiments of this application provide a non-volatile computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement one or more of the signal processing methods described in the first aspect or various possible implementations of the first aspect.

[0066] Fifthly, embodiments of this application provide a vehicle configured as a signal processing device that may include any one of the various possible implementations of the second or third aspect described above.

[0067] These and other aspects of this application will become more apparent in the description of the following embodiments(s). Attached Figure Description

[0068] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this application together with the specification and serve to explain the principles of this application.

[0069] Figure 1 A schematic diagram of an exemplary structure of a vehicle-mounted millimeter-wave radar device is shown.

[0070] Figure 2 This is an exemplary schematic diagram showing the normalization results of the range spectrum data of two typical baseband signals under ideal conditions.

[0071] Figure 3 This is an exemplary schematic diagram showing the normalization results of the range spectrum data of two typical baseband signals under non-ideal conditions.

[0072] Figure 4 This diagram illustrates the modeling or semi-physical simulation of the non-ideal nature of the transmitting device.

[0073] Figure 5 An exemplary schematic diagram of a signal processing method according to an embodiment of this application is shown.

[0074] Figure 6 An exemplary schematic diagram showing the configuration of the correlator according to an embodiment of this application is provided.

[0075] Figure 7a An exemplary schematic diagram shows two-dimensional spectral data of the distance and velocity of a first received signal according to an embodiment of this application.

[0076] Figure 7b This diagram illustrates an exemplary method for obtaining mismatch filter parameters according to an embodiment of this application.

[0077] Figure 7c This diagram illustrates another exemplary method for obtaining mismatch filter parameters according to an embodiment of this application.

[0078] Figure 8 A schematic diagram illustrating the principle of transmitting leakage signals.

[0079] Figure 9 This diagram illustrates an exemplary implementation of determining the parameters of a mismatch filter from time-domain data of a second received signal according to an embodiment of this application.

[0080] Figure 10 This diagram illustrates an exemplary implementation of determining the parameters of a mismatch filter from time-domain data of a second received signal according to an embodiment of this application.

[0081] Figure 11a This diagram illustrates another exemplary implementation of determining the parameters of a mismatch filter from time-domain data of a second received signal according to an embodiment of this application.

[0082] Figure 11b This diagram illustrates another exemplary implementation of determining the parameters of a mismatch filter from time-domain data of a second received signal according to an embodiment of this application.

[0083] Figure 12 A schematic diagram illustrating an exemplary method for acquiring two-dimensional spectral data of distance and velocity at maximum amplitude in a first received signal according to an embodiment of this application.

[0084] Figure 13 This diagram illustrates an exemplary implementation of determining parameters of a mismatch filter using two-dimensional spectral data of distance and velocity at maximum amplitude in a first received signal according to an embodiment of this application.

[0085] Figure 14 This diagram illustrates an exemplary implementation of determining the parameters of a mismatch filter using distance spectrum data of the maximum amplitude of a first received signal according to an embodiment of this application.

[0086] Figure 15This diagram illustrates another exemplary implementation of determining the parameters of a mismatch filter using distance spectrum data of the maximum amplitude of a first received signal according to an embodiment of this application.

[0087] Figure 16a An exemplary application scenario according to an embodiment of this application is shown.

[0088] Figure 16b This illustrates another exemplary application scenario according to an embodiment of this application.

[0089] Figure 17 A schematic block diagram of a signal processing apparatus according to an embodiment of this application is shown.

[0090] Figure 18 This paper illustrates an exemplary application scenario of a signal processing apparatus according to an embodiment of this application. Detailed Implementation

[0091] Various exemplary embodiments, features, and aspects of this application will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0092] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0093] Furthermore, to better illustrate this application, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that this application can be implemented without certain specific details. In some instances, methods, means, components, and circuits well-known to those skilled in the art have not been described in detail in order to highlight the main points of this application.

[0094] The following is an explanation of the terms that may appear in this article.

[0095] Radar: Also known as a radar device, detector, or detection device. Its working principle is to detect target objects by transmitting signals (or detection signals) and receiving the reflected signals (or echo signals) after they have passed through the target object.

[0096] Baseband signal: The raw electrical signal generated by radar that has not undergone modulation (spectral shifting and transformation). The baseband signal can be used as a modulation signal. The baseband signal is the signal that needs to be transmitted.

[0097] Phase Modulation Continuous Wave (PMCW): An electromagnetic wave whose phase changes over time by mixing a baseband signal and a carrier wave.

[0098] Binary Phase Shift Keying (BPSK): In phase modulation, the baseband signal is represented by binary values. The baseband signal and carrier wave are modulated to obtain a transmittable phase-modulated continuous wave. The carrier phase is represented by the binary value 1 or 0 of the baseband signal. Specifically, when the value is "1", the phase-modulated continuous wave is in phase with the unmodulated carrier; when the value is "0", the phase-modulated continuous wave is out of phase with the unmodulated carrier; the phase difference between "1" and "0" is 180°. The binary value 1 or 0 can also be represented by the coded values ​​"+" or "-" of the baseband signal. When the value is "+", the phase-modulated continuous wave is in phase with the unmodulated carrier; when the value is "-", the phase-modulated continuous wave is out of phase with the unmodulated carrier; the phase difference between "+" and "-" is 180°.

[0099] Echo delay: The time from when the radar sends out a transmitted signal to when it receives the echo signal of the transmitted signal reflected by the target in the environment. Based on the echo delay, parameters such as the distance between the target and the radar, the target speed, and the angle can be calculated.

[0100] Periodic autocorrelation: also known as matched filtering. In phase modulation, matched filtering of the echo signal can obtain the frequency domain signal in the echo signal. In the frequency domain signal, the amplitude information of the echo signal can be determined. Through the amplitude information, the main lobe and side lobes in the echo signal can be determined. Among them, the frequency domain signal corresponding to the amplitude of the main lobe can be used to calculate the distance between the target and the radar.

[0101] Coherent accumulation: The radar receives signals consisting of multiple pulses. Since the energy of a single pulse is limited, multiple pulses can be coherently accumulated. By utilizing the phase relationship between the received pulses, the amplitude of the signal can be superimposed to improve the signal-to-noise ratio. The result of the coherent accumulation is then detected and judged.

[0102] Range cell: Within the radar illumination area, the same range ring is considered the same range cell, and the width of the range cell represents the range resolution.

[0103] Doppler cell: also known as Doppler frequency cell, data located in the same Doppler cell have the same Doppler frequency.

[0104] Range main lobe: Also known as the range main lobe, it refers to the main lobe in the range spectrum. The range main lobe is also included in the range-velocity two-dimensional spectrum (RV-map).

[0105] Range sidelobes: also known as range lobes, refer to the sidelobes in the range spectrum. Range sidelobes are also included in the two-dimensional range and velocity spectra.

[0106] The following is combined Figure 1 Explain the process of radar signal generation, transmission, reception, and processing. Figure 1 A schematic diagram of an exemplary structure of a vehicle-mounted millimeter-wave radar device is provided, which generally includes devices such as an oscillator, modulator, transmitting antenna, receiving antenna, demodulator, analog-to-digital converter, correlator, accumulator, processor, and controller. Figure 1 The controller can also be located at the receiving end of the signal output by the vehicle millimeter-wave radar device, rather than in the vehicle millimeter-wave radar device itself. For example, it can be located in the car or in a processing device used to control the car's movement.

[0107] Baseband signals can be in digital form and can be transmitted directly over short distances. For long-distance transmission, the baseband signal can be digitally modulated (usually using a continuous wave as the carrier), and then the modulated signal (phase-modulated continuous wave) is sent to the channel for transmission. This type of digital modulation is called continuous wave digital modulation.

[0108] The baseband signal can be preset and generated by a pseudo-random sequence code generator (not shown in the figure) and output to the modulator. The sequence length of the baseband signal can be Lc. The carrier wave used for digital modulation can be a continuous wave signal with a stable frequency and simple harmonics generated by an oscillator. The carrier wave is output to the modulator and mixed with the baseband signal to complete modulation (binary phase shift keying) to obtain the transmitted signal. The transmitted signal is transmitted through a transmitting antenna and received by a receiving antenna from the echo signal reflected back from the target object in front of the vehicle.

[0109] The echo signal is demodulated in the demodulator and sampled and quantized in the analog-to-digital converter to obtain time-domain data of the echo signal. This time-domain data contains information about the target object, which can be relative parameters between the target object and the vehicle where the vehicle-mounted radar is located, such as at least one of the relative distance, speed, and angle between the target object and the vehicle. A correlator filters the time-domain data to obtain range spectrum data, and an accumulator further processes this data to obtain range spectrum data with a larger amplitude. The processor processes the range spectrum data (e.g., performs a Fast Fourier Transform or spectral analysis) to obtain the target object information, and finally outputs it to the controller for vehicle control.

[0110] The range spectrum data of the echo signal reflected from each target contains one main lobe and multiple side lobes. Under the same conditions, different baseband signals result in different range spectrum data. For example, if the baseband signal is a longest linear feedback shift register sequence (m-sequence) of length Lc, the amplitude of the main lobe of the echo signal is Lc, and the amplitudes of all the side lobes are -1. The baseband signal can also be a zero-correlation sequence, such as an almost perfect autocorrelation sequence (APAS) of length Lc. In this case, the side lobes of the echo signal are 0, but a grating lobe exists at Lc / 2. The grating lobe has the same amplitude as the main lobe, but the distance information is different. For the same target, the detection device may measure two different distances, thus making it impossible to accurately determine the target's distance. Figure 2 This is an exemplary schematic diagram showing the normalization results of the range spectrum data of two typical baseband signals under ideal conditions.

[0111] However, in actual radar systems, due to the presence of non-ideals (such as nonlinearity and noise) and the effects of filtering, the range spectrum data of the obtained echo signal will suffer performance loss, including a reduction in the amplitude of the main lobe in the range dimension and an increase in the amplitude of the side lobes in the range dimension. Figure 3 This is an exemplary schematic diagram showing the normalization results of the range spectrum data of two typical baseband signals under non-ideal conditions.

[0112] Therefore, if we consider the range main lobe and range sidelobe corresponding to a target as a set of range main lobes and range sidelobes, then when the radar receives echo signals reflected from multiple targets, the range spectrum data may contain multiple sets of range main lobes and range sidelobes. The amplitudes of the range main lobe and range sidelobe of the echo signal are related to the target's distance and its physical parameters, such as reflectivity. Given an environment with a target 'a' that is sufficiently close to the radar and has sufficiently high reflectivity, and a target 'b' that is farther away and has lower reflectivity, the amplitude of the range sidelobe generated by the echo signal of target 'a' may be greater than the amplitude of the range main lobe generated by the echo signal of target 'b' in the range spectrum data. If both have the same echo delay, the range main lobe generated by the echo signal of target 'b' will be covered, and the radar will be unable to identify the range main lobe generated by the echo signal of target 'b', thus failing to obtain the range information of target 'b' and resulting in a missed target detection.

[0113] Besides echo signals, the signals received by the radar receiver may also be signals that have not been reflected by the target. For example, signals transmitted directly from the transmitting antenna of radar 1 to the receiving antenna of radar 1, or signals transmitted directly from the transmitting antenna of radar 2 to the receiving antenna of radar 1. After processing by the demodulator and correlator of radar 1, the range spectrum data will also show the range main lobe and range side lobes. Therefore, under certain conditions, such as sufficiently high power and short transmission distance, the range side lobes in the range spectrum data may also obscure the range main lobe of target a or target b, that is, it may also cause the target to be missed.

[0114] Existing technologies propose to compensate the baseband signal of the radar transmitter through physical simulation, so that the transmitted signal generated based on the compensated baseband signal is not affected by the non-ideal characteristics of the physical devices at the transmitter. Figure 4 This diagram illustrates the modeling or semi-physical simulation of non-ideal transmitter devices. For example... Figure 4 As shown, the encoder inputs a baseband signal to the modulator for digital modulation and outputs a corresponding continuous waveform, which is then input into the physical simulation model. This physical simulation model can evaluate the performance of the transmission path (transmitter) by considering physical factors affecting the transmitter (mixer, filter, amplifier, antenna / other signal transceiver devices), allowing the encoder to re-encode the compensated baseband signal based on the transmission path's performance. The compensated baseband signal is then used to obtain a phase-modulated continuous wave, which is transmitted. The echo signal is then subjected to mismatch filtering to obtain range spectrum data.

[0115] However, existing technologies still do not take into account the effects of non-ideal characteristics of physical factors at the radar receiver, such as low-noise amplifiers, mixers, and filters, and only improve the effect of filter design to a limited extent.

[0116] In view of this, this application provides a signal processing method. The signal processing method of this application proposes two methods for determining the mismatch filter parameters. According to the mismatch filter parameters determined in this application, the range dimension sidelobes after filtering can be low, thus avoiding impact on the detection of other targets. This method can be applied to detection devices such as radar, thereby improving the detection accuracy of the detection device.

[0117] Figure 5 An exemplary schematic diagram of a signal processing method according to an embodiment of this application is shown. Figure 5 As shown, the method includes:

[0118] S10, acquire the first received signal, and process the first received signal to obtain two-dimensional spectrum data of distance and velocity;

[0119] S11, determine the first time-domain data based on the distance and velocity two-dimensional spectrum data;

[0120] S12, the first time-domain data is filtered using a mismatch filter to obtain first distance spectrum data, wherein the parameters of the mismatch filter are determined based on the time-domain data of the second received signal or the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal.

[0121] S13, obtain first distance detection data based on the first distance spectrum data;

[0122] S14, determine the second detection data based on the first distance detection data and the first detection data obtained from the first received signal.

[0123] According to the signal processing method of this application embodiment, the parameters of a mismatch filter can be determined based on the time-domain data of the second received signal or the two-dimensional spectrum data of distance and velocity with the maximum amplitude in the first received signal. The first time-domain data can then be filtered using this mismatch filter to obtain first distance spectrum data. Second detection data can be obtained based on the first distance detection data obtained from the first distance spectrum data and the first detection data obtained from the first received signal. Since the first and second received signals are acquired after passing through the environment of signal generation, transmission, and reception, signal processing based on the mismatch filter determined from the first and second received signals can eliminate the influence of non-ideal characteristics of physical factors in the environment of signal generation, transmission, and reception in the first received signal, thus improving the sidelobe suppression effect. Furthermore, since the second detection data is determined by the first detection data and the first distance detection data of the first received signal, the second detection data contains information from both the first detection data and the first distance detection data, and therefore has high accuracy. When applied to detection devices such as radar, more accurate environmental information can be obtained, improving the detection accuracy of the detection device; when the detection device is applied to automobiles, it can improve the information processing capabilities of the automobile system.

[0124] The signal processing method of this application embodiment can improve the advanced driver assistance system (ADAS) capability of the terminal in autonomous driving or assisted driving, and can be applied to vehicle networking, such as vehicle-to-everything (V2X), long-term evolution technology for vehicle-to-vehicle communication (LTE-V), vehicle-to-vehicle (V2V), etc.

[0125] The first received signal includes signals received during radar use, which may include echo signals mentioned above and signals that have not been reflected by the target.

[0126] In step S10, the first received signal is processed to obtain two-dimensional spectral data of range and velocity, which can be referred to... Figure 1The relevant description is as follows. For example, the first received signal can be received by a receiving antenna and sequentially input into a demodulator, an analog-to-digital converter, a correlator, an accumulator, and a processor. The demodulator is also used to receive the carrier wave generated by the oscillator at the radar receiver and demodulate the first received signal based on the first received signal and the carrier wave. The demodulated signal is output to the analog-to-digital converter for sampling and quantization. For example, if the phase of the transmitted signal is {0, 0, 0, π}, ideally, if the amplitude of the first received signal is 'a', then the time-domain data after demodulation and sampling can be {a, a, a, -a}. This time-domain data can, for example, be fed into a 1-bit correlator for filtering. The 1-bit correlator can be used to sum the product of the correlator parameters and the time-domain data to obtain the range spectrum information of the echo signal. For example, if the correlator parameters are {1, 1, 1, -1}, then the time delay of the correlator matches the time-domain data of the echo signal, resulting in a*1 + a*1 + a*1 + (-a)*(-1) = 4a, which is the amplitude of the main lobe in the range dimension of the first received signal's range spectrum data. Based on the distance information corresponding to the main lobe, the target's distance can be determined. If the correlator parameters are {1, 1, -1, 1}, then the time delay of the correlator does not match the time-domain data of the echo signal, resulting in a*1 + a*1 + a*(-1) + (-a)*1 = 0, which is the amplitude of the sidelobes in the range dimension of the first received signal's range spectrum data. Multiple correlators can be set; see [link to relevant documentation]. Figure 6 Each correlator parameter corresponds to a possible case of the time delay of the time domain data of the first received signal. For example, when the phase of the transmitted signal is {0, 0, 0, π}, the first correlator can be set to {1, 1, 1, -1}, the second correlator to {1, 1, -1, 1}, the third correlator to {1, -1, 1, 1}, and the fourth correlator to {-1, 1, 1, 1}. In this case, the parameter of one of the correlators must match the time delay of the time domain data of the first received signal. Based on this, the distance spectrum data of the first received signal can be obtained. One implementation method of using correlators to perform matched filtering on time domain data is shown in formula (1):

[0127]

[0128] Where τ represents the delay time, s(t) represents the result of the first received signal after processing by the analog-to-digital converter, and h(t) = s * The expression s(t) is called matched filtering, and s0(t) represents the autocorrelation result, which is the result of matched filtering (range spectrum data). Matched filtering is the filtering method with relatively optimal signal-to-noise ratio.

[0129] The aforementioned range spectrum data s0(t) can be composed of multiple pulses, with a relatively high data rate and low energy per pulse. Therefore, the range spectrum data s0(t) can be input into an accumulator for multiple coherent accumulations. Through amplitude superposition, range spectrum data s0′(t) with a lower data rate and higher signal-to-noise ratio is obtained. The range spectrum data s0′(t) can be input into a processor, which processes the range spectrum data s0′(t) (for example, by performing a fast Fourier transform or a spectrum analysis) to obtain the velocity and distance two-dimensional spectrum data of the target object, determine the time delay of the first received signal, and thus determine the target's distance, velocity, angle, and other information. Figure 7a This diagram illustrates an exemplary schematic of the range and velocity two-dimensional spectrum data of a first received signal according to an embodiment of this application. The range main lobe has significantly higher amplitude, the range sidelobes have moderate amplitude, and the system noise floor has the lowest amplitude. It can be seen that the range sidelobes have relatively large amplitudes.

[0130] In step S11, first time-domain data for mismatch filtering can be obtained based on the two-dimensional range and velocity spectrum data obtained in step S10. For example, the two-dimensional range and velocity spectrum data of the first received signal are frequency-domain data, while the first time-domain data are time-domain data. Therefore, one or more sets of range main lobes and range sidelobes with relatively large amplitudes can be extracted from the range and velocity spectrum data of the first received signal, and the first time-domain data can be obtained by inversion based on the extracted data.

[0131] In step S12, mismatch filtering can be performed on the first time-domain data to obtain first range spectrum data (frequency domain data) including range information. For example, Figure 7b and Figure 7c As shown, the mismatch filter parameter h can be determined in two ways. Firstly, see [reference needed]. Figure 7b In addition to the first received signal, the radar can also receive a second received signal with a different transmission path than the first received signal. The time-domain data of the second received signal can be obtained, for example, through a receiving antenna, demodulator, and analog-to-digital converter. The mismatch filter parameters can be determined using the time-domain data of the second received signal; secondly, see... Figure 7c The time-domain data can be obtained by inverting the two-dimensional spectrum data of the distance and velocity of the maximum amplitude of the first received signal. The parameters of the mismatch filter can be determined by the time-domain data obtained by inversion.

[0132] After determining the mismatch filter parameters h, the matrix H of the mismatch filter parameters h can be constructed as shown in formula (2), where Lc represents the length of the transmitted signal (the sequence length of the baseband signal), and h (n) This can be represented as a circular shift of column vector h, with n shifts and the shift direction being upwards.

[0133] H = [hh] (1) …h (Lc-1) (2)

[0134] Define the first time-domain data as y, and perform mismatch filtering on the first time-domain data y as shown in formula (3):

[0135] x′=H T y (3)

[0136] Where x′ is the first distance spectrum data obtained by mismatch filtering.

[0137] In step S13, after obtaining the first distance spectrum data, threshold detection can be performed to output the first distance detection data. The first distance detection data indicates the distance to the target.

[0138] In one possible implementation, first detection data can also be obtained based on the first received signal, wherein the first detection data indicates the target's distance, and optionally, the first detection data also indicates the target's velocity. The first detection data can be determined using the velocity and distance two-dimensional spectrum data of the first received signal. For example, a fast Fourier transform can be performed on the distance spectrum data of the first received signal to obtain the distance and velocity two-dimensional spectrum data of the first received signal, and then false alarm detection or other threshold detection can be performed on the velocity and distance two-dimensional spectrum data. In step S14, the target's distance information can be confirmed by combining the first distance detection data and the first detection data to obtain more accurate distance information.

[0139] In one possible implementation, the second received signal is a transmitted leakage signal. The principle of generating the transmitted leakage signal is described below.

[0140] Radar transmitting antennas emit signals for target detection. Ideally, the received signal should only include echoes reflected from targets in the environment. However, due to factors such as the non-infinite isolation between the transmitting and receiving antennas (meaning signal transmission between them cannot be completely isolated) and the relatively high relative field strength (normalized modulus) of the receiving antenna's radiation field in a certain direction, some transmitted signals are not reflected by targets in the environment but are directly transmitted to and received by the receiving antenna. See [link to details]. Figure 8 This part of the signal is the transmitted leakage signal.

[0141] Typically, radars place their transmitting and receiving antennas relatively close (typically a few centimeters apart). Therefore, the power of the transmitted leakage signal is very close to the power of the transmitted signal, resulting in a very high signal-to-noise ratio. When the receiving antenna simultaneously receives both the transmitted leakage signal and the echo signal reflected from the target, the transmitted leakage signal is usually one of the largest amplitude signals received by the receiving antenna, making it easy to identify. For the transmitted leakage signal, the entire process from transmission to reception occurs within the radar, without traversing external space or being reflected by a target. Its amplitude, phase, and time delay characteristics are relatively stable. Furthermore, aside from not traversing external space and not contacting the target, the transmitted leakage signal and the echo signal contact the same hardware within the radar system. Therefore, the transmitted leakage signal can be used to estimate the non-ideal characteristics of the received signal caused by the radar system's hardware in the signal generation, transmission, and reception environments.

[0142] In one possible implementation, when determining the mismatch filter parameters using the time-domain data of the second received signal, the determination of the mismatch filter parameters can be completed before receiving the first received signal. For example, when the method of this application embodiment is applied to a detection device such as radar, the acquisition of the second received signal can be performed in an environment with no reflection conditions, such as an anechoic chamber. In this case, after the detection device emits a transmission signal, it can only receive the transmission leakage signal, making the received second received signal a transmission leakage signal. After determining the mismatch filter parameters based on the second received signal, and then acquiring the first received signal in the environment where the target is located, the signal processing method of this application embodiment can be executed.

[0143] In this way, the mismatch filter parameters can be determined before the first received signal is received, and the detection can be completed using the mismatch filter when the first received signal is received, thereby obtaining detection data with high accuracy and high detection efficiency.

[0144] Figure 9 and Figure 10 This diagram illustrates an exemplary implementation of determining the parameters of a mismatch filter from time-domain data of a second received signal according to an embodiment of this application.

[0145] like Figure 9 As shown, in one possible implementation, the parameters of the mismatch filter can be determined using an optimization method. Determining the parameters of the mismatch filter based on the time-domain data of the second received signal includes:

[0146] S20, determine the maximum amplitude of the range sidelobe in the second received signal based on the time-domain data of the second received signal;

[0147] S21, Based on the maximum amplitude of the range dimension sidelobe in the second received signal, determine the desired filtered data of the second received signal, wherein the amplitude of the range dimension sidelobe of the desired filtered data is lower than the maximum amplitude of the range dimension sidelobe in the second received signal;

[0148] S22, determine the parameters of the mismatch filter based on the time-domain data of the second received signal and the desired filtering data of the second received signal.

[0149] For example, the second received signal is the transmitted leaked signal, such as... Figure 10 As shown, the time-domain data of the second received signal can be obtained, for example, by quantizing the received transmitted leakage signal. In step S20, based on the time-domain data of the transmitted leakage signal, range spectrum data can be obtained by processing with a correlator, and the maximum amplitude m of the range-dimensional sidelobe of the transmitted leakage signal can be determined based on the range spectrum data.

[0150] In step S21, based on the maximum amplitude m of the range-dimensional sidelobe of the transmitted leakage signal, it can be determined that the sidelobe of the desired filtered data should be less than m. The desired filtered data indicates the preset mismatch filtering result. The desired filtered data may include the range-dimensional main lobe and the range-dimensional sidelobe. The range-dimensional main lobe can be preset to be the same as the length of the transmitted signal (the sequence length of the baseband signal) Lc, and the range-dimensional sidelobe can be preset to 0. The desired filtered data is defined as e, and an example of the desired filtered data e is shown in formula (4):

[0151] e = [Lc 0…0] (4)

[0152] The range sidelobes in the desired filtered data of the transmitted leakage signal can also be determined to other values. For example, the range main lobe amplitude of the desired filtered data can be Lc, and the range sidelobe amplitude can be m1 (e.g., m > m1). Those skilled in the art should understand that as long as the range sidelobe amplitude of the desired filtered data is less than the range sidelobe amplitude of the transmitted leakage signal, it is acceptable. In practical applications, the amplitude values ​​of the range sidelobes of the desired filtered data can be adjusted according to requirements, and this application does not impose any restrictions on this.

[0153] In step S22, a matrix can be constructed based on the length of the transmitted signal (the sequence length of the baseband signal) and the time-domain data of the second received signal. For example, when the length of the transmitted signal is Lc, the time-domain data of the transmitted leakage signal can be defined as a, and A is defined as the Toplitz matrix constructed from the time-domain data of the transmitted leakage signal. An example of matrix A is shown in formula (5).

[0154]

[0155] Among them, a (-n)It is expressed as a circular shift of the column vector a, the number of shifted bits is n (1 ≤ n ≤ Lc and n is an integer), and the shift direction is upward.

[0156] Those skilled in the art should understand that the matrix A can also be constructed in other ways, as long as it can satisfy that the mismatch filter parameter h can be calculated through the matrix A and the expected filtered data, and this application does not limit this.

[0157] Define the signal-to-noise ratio loss after mismatch filtering as SNR loss , then the calculation of the filter parameter can be expressed as formula (6):

[0158]

[0159] where ∈ is the error tolerance boundary of the range dimension sidelobe amplitude of the expected filtered data, ∈ < m. Through formula (6), the mismatch filter parameter h that satisfies the signal-to-noise ratio loss of SNR loss minimized can be solved. In formula (6), the signal-to-noise ratio loss SNR loss and the mismatch filter parameter h are correlated. In practical applications, it is not necessary for the range dimension sidelobe to reach zero. Therefore, the zero-sidelobe requirement after filtering can be relaxed through an optimization method, such as making the range dimension sidelobe lower than the background noise of the detection device (which can be preset, for example, determined according to the transmission power of the detection device), etc., to obtain the mismatch filter parameter that makes both the signal-to-noise ratio loss and the sidelobe amplitude after filtering relatively ideal.

[0160] In this way, the mismatch filter parameter with a better signal-to-noise ratio effect of filtering can be obtained.

[0161] Figure 11a and Figure 11b shows a schematic diagram of another exemplary implementation manner for determining the parameter of the mismatch filter according to the time-domain data of the second received signal in an embodiment of the present application.

[0162] In one possible implementation manner, the parameter of the mismatch filter can also be determined through matrix operations. As Figure 11a shown, determining the parameter of the mismatch filter according to the time-domain data of the second received signal includes:

[0163] S90, according to the transmitted signal, determine the expected filtered data of the second received signal, where the range dimension sidelobe amplitude of the expected filtered data is zero;

[0164] S91, according to the transmitted signal, the time-domain data of the second received signal, and the expected filtered data, determine the parameter of the mismatch filter.

[0165] where, in step S90, as Figure 11bAs shown, the desired filtering data can be directly determined based on the length of the transmitted signal. For example, in the desired filtering data determined in this embodiment, the main lobe amplitude is Lc, and the side lobe amplitude is 0. Compared with the optimization method, the step of determining the maximum amplitude of the range-dimensional side lobes in the second received signal can be saved.

[0166] In one possible implementation, in step S91, matrix A can be constructed first based on the length of the transmitted signal (the sequence length of the baseband signal) and the time-domain data of the second received signal. For a detailed implementation, please refer to the description of step S22.

[0167] The time-domain data of the transmitted leakage signal is filtered using a mismatch filter as shown in formula (7):

[0168] A T h = e (7)

[0169] Assuming matrix A is of full rank, the corresponding mismatch filter parameter h is obtained as shown in formula (8):

[0170] h=(A T ) -1 e (8)

[0171] In this way, the parameters of the mismatch filter can be obtained. The mismatch filter parameters determined by the above method are those that make the time-domain data of the transmitted leakage signal approximate the desired filtered data. Using these mismatch filter parameters to filter the data allows the processing trend from the transmitted leakage signal to the desired filtered data to be applied to the data processing process, ensuring the processing effect of the mismatch filter. Furthermore, the method for determining the mismatch filter parameters is relatively simple and direct, easy to implement in practical applications, and can improve signal processing efficiency.

[0172] In one possible implementation, the mismatch filter parameters of this application embodiment can also be calculated using information from the first received signal, and the mismatch filter parameters can also be determined after receiving the first received signal.

[0173] For example, when the first received signal is the signal received by the detection device, the first received signal also includes the transmitted leakage signal. Referring to the description above, due to the short transmission distance, the power of the transmitted leakage signal is close to the power of the transmitted signal. If the target in outer space is far from the radar, the echo signal reflected by the target may have significant power loss. In this case, the range and velocity two-dimensional spectrum data with the maximum amplitude in the first received signal is the data information of the transmitted leakage signal. If the target in outer space is also very close to the radar, the echo signal reflected by the target may have greater power than the transmitted leakage signal. In this case, the range and velocity two-dimensional spectrum data with the maximum amplitude in the first received signal is the data information of the echo signal. Those skilled in the art should understand that the accuracy of the mismatch filter parameters calculated based on the data information with greater power is also higher. Therefore, the range and velocity two-dimensional spectrum data with the maximum amplitude in the first received signal can be used to determine the mismatch filter parameters.

[0174] Specifically, before using the two-dimensional range and velocity spectrum data with the maximum amplitude in the first received signal to determine the parameters of the mismatch filter, the two-dimensional range and velocity spectrum data with the maximum amplitude in the first received signal must first be obtained. Figure 12 This diagram illustrates an exemplary method for acquiring two-dimensional spectral data of distance and velocity at maximum amplitude in a first received signal according to an embodiment of this application. Figure 12 As shown, in one possible implementation, acquiring the two-dimensional spectral data of range and velocity with the maximum amplitude in the first received signal includes:

[0175] S30, based on the distance and velocity two-dimensional spectrum data of the first received signal, determine the Doppler unit where the maximum amplitude signal in the first received signal is located;

[0176] S31, extract the distance and velocity two-dimensional spectrum data of the Doppler unit where the maximum amplitude signal in the first received signal is located from the distance and velocity two-dimensional spectrum data of the first received signal, and use it as the distance and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal.

[0177] For example, the range and velocity two-dimensional spectrum data of the first received signal are data obtained after sampling, quantization, matched filtering, coherent accumulation, and velocity-dimensional fast Fourier transform of the first received signal. Figure 7a Taking the two-dimensional spectrum data of distance and velocity as an example, the maximum amplitude signal is approximately at velocity unit 35. Furthermore, in related technologies, velocity and Doppler frequency are correlated; for a signal emitted by a detection device, its Doppler frequency is proportional to its velocity. Therefore, in step S30, the Doppler unit corresponding to velocity unit 35 in this application scenario (e.g., Doppler unit Q) can be determined first, thus confirming that the Doppler unit containing the maximum amplitude signal in the first received signal is Doppler unit Q.

[0178] In this case, in step S31, the data information of the determined Doppler units can be extracted, and the extracted data information has the same velocity. The extracted data information can be used as the two-dimensional range and velocity spectrum data with the maximum amplitude in the first received signal, for determining the parameters of the mismatch filter.

[0179] In this way, the data used to determine the mismatch filter parameters can correspond to the maximum amplitude signal in the first received signal, thereby improving the accuracy of the mismatch filter parameters.

[0180] The following section explains how to obtain the mismatch filter parameters from the two-dimensional spectral data of distance and velocity at the maximum amplitude of the first received signal.

[0181] Figure 13 This diagram illustrates an exemplary implementation of determining the parameters of a mismatch filter using two-dimensional spectral data of distance and velocity at maximum amplitude in a first received signal according to an embodiment of this application. Figure 13 As shown, in one possible implementation, the parameters of the mismatch filter are determined based on the two-dimensional spectral data of distance and velocity with the maximum amplitude in the first received signal, including:

[0182] S40, based on the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal, obtain the distance spectrum data with the maximum amplitude in the first received signal;

[0183] S41, determine the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal.

[0184] For example, in one possible implementation, the range spectrum data corresponding to each Doppler unit in the velocity and range two-dimensional spectrum data of the first received signal is obtained by matched filtering of the first received signal. That is, the velocity and range two-dimensional spectrum data of the maximum amplitude of the first received signal can be obtained by matched filtering of the maximum amplitude signal in the first received signal. Furthermore, the velocity information in data from the same source (e.g., all from the maximum amplitude signal) is also the same; therefore, the range and velocity two-dimensional spectrum data of the maximum amplitude signal should be located in the same Doppler unit. The time-domain data of the maximum amplitude signal of the first received signal can be determined using the range and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal. Since the velocity spectrum data in the range and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal is not related to the determination of the mismatch filter parameters, the range spectrum data can be extracted from the range and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal for calculation.

[0185] In one possible implementation, the two-dimensional range and velocity spectrum data with the maximum amplitude in the first received signal includes multiple range cells, where the amplitude of the data information in each range cell may be the same or different. The data information in each range cell can be shifted so that the data information with the maximum amplitude is located in the 0 range cell. The data information of the multiple shifted range cells can then be used as the range spectrum data with the maximum amplitude in the first received signal.

[0186] In this way, the mismatch filter parameters can be determined based on the range spectrum data of the maximum amplitude of the first received signal, and the first time domain data is determined based on the data information of the first received signal. When the first time domain data is filtered using the mismatch filter parameters, more accurate first range spectrum data can be obtained.

[0187] Figure 14 This diagram illustrates an exemplary implementation of determining the parameters of a mismatch filter using range spectrum data of the maximum amplitude of a first received signal according to an embodiment of this application. Figure 14 As shown, in one possible implementation, the parameters of the mismatch filter can be determined by an optimization method. Determining the parameters of the mismatch filter based on the range spectrum data of the maximum amplitude in the first received signal further includes:

[0188] S410, determine the maximum amplitude of the range dimension sidelobe in the first received signal based on the range spectrum data with the maximum amplitude in the first received signal;

[0189] S411, based on the maximum amplitude of the range sidelobe in the first received signal, determine the expected filtered data of the maximum amplitude signal in the first received signal, wherein the amplitude of the range sidelobe of the expected filtered data is lower than the maximum amplitude of the range sidelobe in the first received signal.

[0190] S412, determine the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal and the expected filtering data of the maximum amplitude signal in the first received signal.

[0191] For example, in step S410, the range spectrum data with the maximum amplitude in the first received signal can be processed. The processing method could be, for instance, determining the range-dimensional sidelobes in the first received signal using the range spectrum data, and based on this, obtaining the maximum amplitude m1 of the range-dimensional sidelobes in the first received signal. For example, it is generally assumed that range-dimensional main lobes will not exist in range cells that are far from the radar. If the range spectrum data with the maximum amplitude in the first received signal is located in Doppler cell J, and the seventh, eighth, and ninth range cells are three adjacent range cells that are far from the radar, then the maximum amplitude m1 of the range-dimensional sidelobes can be determined by comparing the amplitudes of the data information from the seventh, eighth, and ninth range cells in Doppler cell J. For example, if the amplitude of the seventh range cell is the largest, then the amplitude of the seventh range cell is the maximum amplitude m1 of the range-dimensional sidelobes.

[0192] In step S411, based on the maximum amplitude m1 of the range-dimensional sidelobes in the first received signal, it can be determined that the sidelobes of the desired filtered data should be less than m1. For example, in the desired filtered data determined in this embodiment, the main lobe amplitude is L. c The side lobe amplitude is 0; or the main lobe amplitude is L. c The side lobe amplitude is m2(m2 <m1)。

[0193] As described above, the parameters of the mismatch filter are determined by the time-domain data and the expected filtering data of the time-domain data. Therefore, when determining the mismatch filter based on the relevant information of the first received signal, the time-domain data of the first received signal can also be obtained first.

[0194] Since the time-domain data obtained by quantizing the first received signal has a high data rate, directly using the time-domain data of the first received signal to obtain the mismatch filter parameters would significantly increase the data processing cost. Therefore, this application proposes to obtain the time-domain data of the maximum amplitude signal of the first received signal through inversion, and determine the mismatch filter parameters based on the inverted time-domain data.

[0195] For example, in step S412, the time domain data of the maximum amplitude signal in the first received signal can be obtained first based on the distance spectrum data of the maximum amplitude in the transmitted signal and the first received signal.

[0196] In one possible implementation, c can be defined as a column vector consisting of the transmitted signals, and vector c can be defined. (u) Let u be the periodic shift of vector c, where u is the number of bits shifted (1 ≤ u ≤ Lc-1 and is an integer). Here, a shift down is defined as positive, and a shift up as negative. The inversion matrix C is then shown in formula (9):

[0197] C = [cc] (1) …c (Lc-1 (9)

[0198] The inversion matrix C is constructed to correspond to the application scenario of the maximum amplitude signal in the first received signal in the 0 distance cell. In the inversion matrix constructed in this way, the data in the first row corresponds to the first distance cell (0 distance cell). k can be defined as the distance spectrum data of the maximum amplitude in the first received signal, and y can be defined as the time domain data obtained by inversion. The time domain data is obtained as shown in formula (10):

[0199] y = C -1 k (10)

[0200] As can be seen from the above, the maximum amplitude data k in the first received signal is also located in the 0 distance cell. Thus, by multiplying the inverse matrix of the inversion matrix with the maximum amplitude data k in the first received signal, the time domain data of the maximum amplitude signal in the first received signal can be obtained.

[0201] In one possible implementation, matrix C can also be constructed in other ways. For example, the range dimension data of the two-dimensional spectrum data of the maximum amplitude of the first received signal and the velocity spectrum data can be directly used as the range spectrum data of the maximum amplitude in the first received signal. In this case, the data information with the largest amplitude may be located in any range cell (e.g., the second range cell), and an inversion matrix C can be constructed such that the data in the first row of the inversion matrix C corresponds to the second range cell. This application does not limit the specific construction method of the inversion matrix.

[0202] In one possible implementation, a matrix can be constructed based on time-domain data. The mismatch filter parameters can be optimized by combining the matrix, the desired filter data, the error allowable boundary of the sidelobe amplitude of the desired filter data (the maximum amplitude of the range dimension sidelobe in the first received signal), and the signal-to-noise ratio loss. The specific implementation method can be referred to the description of step S22 above.

[0203] In this way, the mismatch filter parameters can be determined. The data rate of the inverted time-domain data is relatively low, which reduces the data processing cost of the filtering process. Furthermore, by selecting the range spectrum data with the maximum amplitude in the first received signal, the determined mismatch filter parameters can be made more accurate.

[0204] Figure 15 This diagram illustrates another exemplary implementation of determining the parameters of a mismatch filter using range spectrum data of the maximum amplitude of a first received signal according to an embodiment of this application. Figure 15 As shown, in another possible implementation, the parameters of the mismatch filter can be determined using matrix operations. Determining the parameters of the mismatch filter based on the range spectrum data of the maximum amplitude in the first received signal further includes:

[0205] S81, based on the distance spectrum data of the maximum amplitude signal in the first received signal and the transmitted signal, obtain the time domain data of the maximum amplitude signal in the first received signal;

[0206] S82, based on the transmitted signal, determine the desired filtered data of the time-domain data of the maximum amplitude signal in the first received signal, wherein the distance dimension sidelobe amplitude of the desired filtered data is zero;

[0207] S83, determine the parameters of the mismatch filter based on the time-domain data of the maximum amplitude signal in the transmitted signal and the first received signal and the desired filtering data.

[0208] In one possible implementation, the method for obtaining the time-domain data of the maximum amplitude signal in the first received signal in step S81 can refer to the description of step S412. In step S82, based on the length of the transmitted signal (the sequence length of the baseband signal) Lc, desired filtered data of the time-domain data of the maximum amplitude signal in the first received signal can be constructed. For example, in the desired filtered data determined in the embodiments of this application, the main lobe amplitude is Lc and the side lobe amplitude is 0.

[0209] In step S83, the mismatch filter parameters can be determined based on the inverted time-domain data and the desired filtering data. For example, a matrix can be constructed first based on the length of the transmitted signal and the inverted time-domain data. The parameters of the mismatch filter can also be determined through matrix operations. For a detailed implementation, please refer to [reference needed]. Figure 15 The description of step S91 above will not be repeated here for the sake of brevity.

[0210] In this way, when using the data information of the first received signal to determine the parameters of the mismatch filter, it is not necessary to determine the maximum amplitude of the range dimension sidelobe in the first received signal, which can improve the efficiency of determining the parameters of the mismatch filter.

[0211] Based on this, the detection device can determine the mismatch filter parameters upon receiving the first received signal. In practical applications, the determined mismatch filter parameters can be directly used to process other first received signals received by the detection device in subsequent operations. Alternatively, the mismatch filter parameters can be redefined after a certain period of time following the initial determination. This ensures that the redefined mismatch filter parameters, when used for data processing, can eliminate the impact of new changes in the non-ideal characteristics of the detection device's physical components (such as aging) on ​​the first received signal since the previous determination. This improves the accuracy of the second detection data obtained through signal processing. To further improve the accuracy of the second detection data, the detection device can be configured to redetermine the mismatch filter parameters each time it receives a first received signal. This application does not impose any limitations on this.

[0212] In this way, when using mismatch filters for signal processing, the non-ideal characteristics caused by the radar transmitter and receiver on the received signal can be eliminated, and the accuracy of the obtained mismatch filter parameters can be improved. Furthermore, there are multiple options for determining the mismatch filter parameters, which increases the flexibility of signal processing.

[0213] In one possible implementation, in step S12, the mismatch filter filters time-domain data. Since the quantized time-domain data of the first received signal has a high data rate, in step S11, to reduce the data cost of the filtering process, a portion of the data information in the two-dimensional spectrum data of the distance and velocity of the first received signal can be inverted to obtain the first time-domain data with a lower data rate. In another possible implementation, step S11 may include:

[0214] Construct the inversion matrix based on the transmitted signal;

[0215] Based on the aforementioned two-dimensional distance and velocity spectrum data, determine the second distance spectrum data;

[0216] The first time-domain data is determined based on the second distance spectrum data and the inversion matrix.

[0217] The specific implementation of constructing the inversion matrix based on the transmitted signal can be found in the description of S412 above. The second range spectrum data, i.e., the data to be inverted, can be determined using the range and velocity two-dimensional spectrum data of the first received signal. Thus, the data information in the first time-domain data all comes from the first received signal. After filtering the first time-domain data, the range information of the target in the first received signal can be obtained. Furthermore, the data rate of the inverted first time-domain data is relatively low, which can reduce the cost of the mismatch filtering process.

[0218] In one possible implementation, determining the second range spectrum data based on the range and velocity two-dimensional spectrum data may include:

[0219] Based on the distance and velocity two-dimensional spectral data, the range dimension sidelobe amplitude of the signal in the first received signal is determined;

[0220] Signals whose sidelobe amplitude is greater than or equal to the amplitude threshold in the distance dimension are identified as target signals.

[0221] The second range spectrum data is determined based on the range spectrum data of the Doppler unit where the target signal is located in the two-dimensional range and velocity spectrum data.

[0222] For example, the first received signal may include multiple signals, such as a transmitted leakage signal and multiple echo signals obtained from reflected transmitted signals from multiple targets. The sidelobe amplitudes of these multiple signals can be determined using the range and velocity two-dimensional spectrum data of the first received signal. An amplitude threshold can be preset, and data information of signals whose sidelobe amplitude exceeds the threshold can be identified as target signals. The range spectrum data of the target signals can then undergo mismatch filtering to suppress excessively high sidelobes.

[0223] The data information of signals whose sidelobe amplitudes exceed the amplitude threshold can be determined by extracting the data information of the Doppler cells containing the signals whose sidelobe amplitudes exceed the amplitude threshold. Therefore, by extracting the data information of the same Doppler cells from the data information of sidelobe amplitudes exceeding the amplitude threshold, the data information of the target signal, i.e., the second range spectrum data, can be obtained.

[0224] In this way, mismatch filtering can be performed on the range spectrum data of Doppler units with high sidelobe amplitudes in the range dimension, which can reduce the data cost of mismatch filtering.

[0225] In one possible implementation, the first detection data includes distance detection and / or velocity detection data. Determining the first time-domain data based on the second distance spectrum data and the inversion matrix may include: replacing the distance detection data in the first detection data with the first distance detection data to obtain the second detection data, or performing an OR operation on the first distance detection data and the first detection data to obtain the second detection data.

[0226] For example, the first detection data can be obtained by threshold detection or false alarm detection on the two-dimensional spectrum data of the distance and velocity of the first received signal. Alternatively, only distance detection can be performed to obtain the distance detection data of the first received signal, or both distance and velocity detection can be performed to obtain both distance detection data and velocity detection data.

[0227] The first distance detection data can be fused with the first detection data to obtain the second detection data with higher accuracy. For example, when the first detection data includes distance detection data, the first distance detection data can be used to replace the distance detection data in the first detection data to obtain the second detection data; or, the first distance detection data and the first detection data can be ORed to obtain the second detection data.

[0228] This approach increases the flexibility of obtaining secondary detection data. Furthermore, using substitution methods can improve data accuracy, and using OR operations can further enhance accuracy and prevent missed detections.

[0229] Figure 16a and Figure 16bExemplary application scenarios according to embodiments of this application are shown respectively. Figure 16a In the application scenario shown, the mismatch filter parameters are obtained in an anechoic chamber environment. In an anechoic chamber, signal reflection is impossible, and the radar's receiving antenna only receives the second received signal. The radar can demodulate and sample-quantize the second received signal to obtain its time-domain data. Based on this time-domain data, the mismatch filter parameters can be calculated. After determining the mismatch filter parameters, the radar can implement the signal processing method of this embodiment in a non-anechoic chamber environment. In this non-anechoic chamber environment, at least one target may be within the detection range of the detection device. In this case, the radar's receiving antenna can receive a first received signal, which may include the echo signal reflected by the target and the transmission leakage signal directly transmitted from the transmitting antenna to the receiving antenna. The radar can first obtain first detection data including range information and / or velocity information based on the matched filtering processing result. Based on the range and velocity two-dimensional spectrum data obtained during the matched filtering process, the radar can also extract the range spectrum data to be processed. Then, according to the mismatch filter parameters determined in the anechoic chamber, the first time-domain data obtained by inverting the extracted range spectrum data is processed. Based on the processing result of the mismatch filtering (the first range spectrum data), a first range detection data including range information is obtained. In this case, the radar can obtain a second detection data with higher accuracy based on the first detection data and the first range detection data.

[0230] exist Figure 16bIn the application scenario shown, the mismatch filter parameters are obtained in a non-anechoic chamber environment. In this environment, at least one target may be present within the detection range of the detection device. In this case, the radar's receiving antenna can receive a first received signal, which may include the echo signal reflected from the target and the transmission leakage signal directly transmitted from the transmitting antenna to the receiving antenna. The radar can demodulate, sample and quantize, perform matched filtering, coherent accumulation, and velocity-dimensional fast Fourier transform processing on the first received signal to obtain two-dimensional range and velocity spectrum data. This two-dimensional range and velocity spectrum data has three uses: First, the radar can obtain first detection data including range and / or velocity information based on the two-dimensional range and velocity spectrum data. Second, based on the two-dimensional range and velocity spectrum data of the first received signal, the range spectrum data with the maximum amplitude of the first received signal can be obtained. The mismatch filter parameters can be calculated from the time-domain data obtained by inverting the extracted maximum amplitude range spectrum data. Third, the radar can also extract range spectrum data to be processed from the range and velocity two-dimensional spectrum data, and process the first time-domain data obtained by inverting the extracted range spectrum data according to the determined mismatch filter parameters. Based on the processing result of the mismatch filter (the first range spectrum data), a first range detection data including range information is obtained. In this case, the radar can obtain a second detection data with higher accuracy based on the first detection data and the first range detection data.

[0231] The signal processing method provided in the embodiments of this application has been described in detail above. The signal processing apparatus provided in the embodiments of this application will be described below.

[0232] Figure 17 A schematic block diagram of a signal processing apparatus according to an embodiment of this application is shown.

[0233] like Figure 17 As shown, the signal processing apparatus 1400 of this application embodiment includes:

[0234] The first acquisition module 1410 is used to acquire a first received signal and process the first received signal to obtain two-dimensional spectrum data of distance and velocity.

[0235] The first determining module 1420 is used to determine the first time-domain data based on the distance and velocity two-dimensional spectrum data;

[0236] Processing module 1430 is used to filter the first time-domain data using a mismatch filter to obtain first distance spectrum data, wherein the parameters of the mismatch filter are determined based on the time-domain data of the second received signal or the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal.

[0237] The second acquisition module 1440 is used to obtain first distance detection data based on the first distance spectrum data;

[0238] The second determining module 1450 is used to determine the second detection data based on the first distance detection data and the first detection data obtained from the first received signal.

[0239] The signal processing apparatus according to the embodiments of this application can obtain second detection data with higher accuracy, and the information such as the distance and speed of the target determined based on the second detection data is also more accurate. When the signal processing apparatus is applied to automobiles, it can be used for target detection and tracking in assisted driving and autonomous driving, thereby improving the information processing capabilities of the vehicle system.

[0240] The signal processing device 1400 in this application embodiment can be a detection device, or one or more chips within the detection device. The signal processing device 1400 can be used to perform some or all of the functions of the detection device in this application embodiment. Optionally, the signal processing device 1400 may further include a storage module.

[0241] The storage module can be used to store instructions for implementing the signal processing method of the embodiments of this application.

[0242] In one possible implementation, the second received signal is a transmitted leakage signal.

[0243] In one possible implementation, the signal processing device includes:

[0244] The third determining module is used to determine the maximum amplitude of the range-dimensional sidelobe in the second received signal based on the time-domain data of the second received signal.

[0245] The fourth determining module is used to determine the desired filtered data of the second received signal based on the maximum amplitude of the range dimension sidelobe in the second received signal, wherein the amplitude of the range dimension sidelobe of the desired filtered data is lower than the maximum amplitude of the range dimension sidelobe in the second received signal.

[0246] The fifth determining module is used to determine the parameters of the mismatch filter based on the time-domain data of the second received signal and the expected filtering data of the second received signal.

[0247] In one possible implementation, the device further includes:

[0248] The third acquisition module is used to acquire the distance spectrum data with the maximum amplitude in the first received signal based on the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal.

[0249] The sixth determining module is used to determine the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal.

[0250] In one possible implementation, the sixth determining module includes:

[0251] The first determining submodule is used to determine the maximum amplitude of the range dimension sidelobe in the first received signal based on the range spectrum data with the maximum amplitude in the first received signal.

[0252] The second determining submodule is used to determine the expected filtered data of the maximum amplitude signal in the first received signal based on the maximum amplitude of the range dimension sidelobe in the first received signal, wherein the amplitude of the range dimension sidelobe of the expected filtered data is lower than the maximum amplitude of the range dimension sidelobe in the first received signal.

[0253] The third determining submodule is used to determine the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal and the expected filtering data of the maximum amplitude signal in the first received signal.

[0254] In one possible implementation, the first determining module includes:

[0255] The fourth determination submodule is used to construct the inversion matrix based on the transmitted signal;

[0256] The fifth determining submodule is used to determine the second distance spectrum data based on the distance and velocity two-dimensional spectrum data;

[0257] The sixth determining submodule is used to determine the first time-domain data based on the second distance spectrum data and the inversion matrix.

[0258] In one possible implementation, determining the second range spectrum data based on the range and velocity two-dimensional spectrum data includes:

[0259] Based on the distance and velocity two-dimensional spectral data, the range dimension sidelobe amplitude of the signal in the first received signal is determined;

[0260] Signals whose sidelobe amplitude is greater than or equal to the amplitude threshold in the distance dimension are identified as target signals.

[0261] The second range spectrum data is determined based on the range spectrum data of the Doppler unit where the target signal is located in the two-dimensional range and velocity spectrum data.

[0262] In one possible implementation, the device further includes:

[0263] The seventh determining module is used to determine the Doppler unit where the maximum amplitude signal in the first received signal is located based on the two-dimensional spectrum data of distance and velocity of the first received signal;

[0264] The eighth determining module is used to extract the distance and velocity two-dimensional spectrum data of the Doppler unit where the maximum amplitude signal in the first received signal is located from the distance and velocity two-dimensional spectrum data of the first received signal, and use it as the distance and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal.

[0265] In one possible implementation, the first detection data includes distance detection and / or speed detection data, and the second determining module includes:

[0266] The seventh determining submodule is used to replace the distance detection data in the first detection data with the first distance detection data to obtain the second detection data, or...

[0267] The eighth determination submodule is used to perform an OR operation on the first distance detection data and the first detection data to obtain the second detection data.

[0268] In one possible implementation, this application also provides a signal processing apparatus, including a processor and a memory for storing processor-executable instructions; wherein the processor can be used to implement the signal processing method described above.

[0269] The signal processing apparatus according to embodiments of this application can obtain second detection data with higher accuracy, and the information such as the distance and speed of the target determined based on the second detection data is also more accurate. When the signal processing apparatus is applied to an automobile, it can improve the information processing capability of the automobile system.

[0270] like Figure 18 As shown, signal processing devices such as radar can be installed in motor vehicles, drones, railcars, bicycles, traffic lights, speed measuring devices, or network equipment (such as base stations and terminal equipment in various systems), etc. This application applies not only to vehicle-to-vehicle radar systems, but also to radar systems between vehicles and drones or other devices, or radar systems between other devices. For example, radar can be installed on intelligent transportation equipment, smart home devices, robots, and other intelligent terminals. This application does not limit the type of terminal equipment on which the radar is installed, the installation location of the radar, or the function of the radar.

[0271] The signal processing device may include a processor, memory, a transmitting antenna, a receiving antenna, and a monolithic microwave integrated circuit (MMIC). The MMIC may include a modulator, an oscillator, an analog-to-digital converter (ADC), a demodulator, a correlator, an accumulator, an encoder, etc. The transmitting antenna is connected to the modulator, and the receiving antenna, demodulator, ADC, correlator, and accumulator are connected sequentially. The oscillator is connected to both the modulator and demodulator, outputting carrier waves for modulation and demodulation. The modulator may also be connected to an encoder to receive the baseband signal used for modulation.

[0272] A modulator can be used to modulate and amplify the carrier and baseband signals to obtain the transmitted signal, and then send the transmitted signal to the transmitting antenna.

[0273] Transmitting antennas (such as millimeter-wave antennas) are used to emit signals into the environment to detect targets in the environment, which may be target vehicles, other vehicles, or other moving objects.

[0274] A receiving antenna (e.g., a millimeter-wave antenna) is used to receive echo signals reflected from targets in the environment. Due to the isolation between the transmitting and receiving antennas, the receiving antenna also receives the transmission leakage signal directly transmitted from the transmitting antenna to the receiving antenna. The receiving antenna transmits the received signal to a demodulator. In this application, the receiving antenna may receive a first received signal or a second received signal, wherein the first received signal may include both the echo signal reflected from the target and the transmission leakage signal. The second received signal may include the transmission leakage signal.

[0275] The demodulator is used to perform frequency mixing (down-conversion) and low-noise amplification on the transmitted signal with a carrier wave pre-transmitted by the oscillator. The analog-to-digital converter is used to perform analog-to-digital conversion on the signal processed by the demodulator to obtain the time-domain data of the signal. In this application, the time-domain data of either the first received signal or the second received signal can be obtained.

[0276] The correlator is used to perform matched filtering on the time-domain data of the signal to obtain the target's range information. In this application, the range spectrum data of the first received signal can be obtained. The accumulator is used to coherently accumulate the target's range information to increase the amplitude of the range information.

[0277] The processor processes the target's distance information to obtain the target's velocity information. Based on the target's distance and velocity information, the processor can detect and determine the target's distance and velocity, thus completing the target localization.

[0278] The processor can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a network processor (NP), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program in this application. It can also be a digital signal processor (DSP), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. The processor typically performs logical and arithmetic operations based on program instructions stored in memory. The processor can fully or partially implement the functions of the first acquisition module 1410, the first determination module 1420, the processing module 1430, the second acquisition module 1440, and the second determination module 1450 in the embodiments of this application.

[0279] The memory can be a storage unit located inside the processor, such as registers or caches. The memory can also be a storage unit located outside the processor, such as read-only memory (ROM) or other types of static storage devices that can store static information and instructions, such as random access memory (RAM). The memory can implement the functions of the storage module 1460 in the embodiments of this application.

[0280] Optionally, the monolithic microwave integrated circuit may also include devices such as power amplifiers, low-noise amplifiers, and variable-gain amplifiers. Those skilled in the art should understand that all signal processing devices capable of implementing this application are within the scope of protection of this application.

[0281] This application provides a vehicle, which includes the signal processing device of this application.

[0282] This application provides a program or a computer program product including program instructions, which, when executed by a processor, will cause the processor to implement the method flow in any of the above method embodiments.

[0283] The program instructions mentioned above can be stored, in whole or in part, on a storage medium packaged with the processor, or in part or in whole on a memory not packaged with the processor.

[0284] Embodiments of this application provide a non-volatile computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the above-described method.

[0285] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), electrically programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital video disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing.

[0286] The computer-readable program instructions or code described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network mismatch card or network interface in each computing / processing device receives computer-readable program instructions from the network and forwards them to computer-readable storage media stored in the respective computing / processing device.

[0287] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as "C" or similar languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information from computer-readable program instructions. These electronic circuits can execute computer-readable program instructions to implement various aspects of this application.

[0288] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0289] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved.

[0290] It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, can be implemented using hardware (such as circuits or ASICs (Application Specific Integrated Circuits)) that performs the corresponding function or action, or using a combination of hardware and software, such as firmware.

[0291] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings, disclosure, and appended claims in carrying out the claimed invention. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0292] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A signal processing method, characterized by, The method includes: Acquire a first received signal, and process the first received signal to obtain two-dimensional spectral data of distance and velocity; Based on the distance and velocity two-dimensional spectral data, the first time-domain data is determined; The first time-domain data is filtered using a mismatch filter to obtain first distance spectrum data. The parameters of the mismatch filter are determined based on the time-domain data of the second received signal or the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal. The second received signal is a transmission leakage signal. Based on the first distance spectrum data, first distance detection data is obtained; The second detection data is determined based on the first distance detection data and the first detection data obtained from the first received signal; The method further includes: Based on the time-domain data of the second received signal, determine the maximum amplitude of the range-dimensional sidelobe in the second received signal; Based on the maximum amplitude of the range dimension sidelobe in the second received signal, the desired filtered data of the second received signal is determined, wherein the amplitude of the range dimension sidelobe of the desired filtered data is lower than the maximum amplitude of the range dimension sidelobe in the second received signal. The parameters of the mismatch filter are determined based on the time-domain data of the second received signal and the desired filtering data of the second received signal.

2. The signal processing method of claim 1, wherein, The method further includes: Based on the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal, obtain the distance spectrum data with the maximum amplitude in the first received signal; The parameters of the mismatch filter are determined based on the distance spectrum data of the maximum amplitude in the first received signal.

3. The signal processing method of claim 2, wherein, Based on the distance spectrum data with the maximum amplitude in the first received signal, the parameters of the mismatch filter are determined, including: Based on the range spectrum data with the maximum amplitude in the first received signal, determine the maximum amplitude of the range dimension sidelobe in the first received signal; Based on the maximum amplitude of the range dimension sidelobe in the first received signal, the desired filtered data of the maximum amplitude signal in the first received signal is determined, wherein the amplitude of the range dimension sidelobe of the desired filtered data is lower than the maximum amplitude of the range dimension sidelobe in the first received signal. The parameters of the mismatch filter are determined based on the distance spectrum data of the maximum amplitude in the first received signal and the expected filtering data of the maximum amplitude signal in the first received signal.

4. The signal processing method of claim 1, wherein, Based on the aforementioned two-dimensional spectral data of distance and velocity, the first time-domain data is determined, including: Construct the inversion matrix based on the transmitted signal; Based on the aforementioned two-dimensional distance and velocity spectrum data, determine the second distance spectrum data; The first time-domain data is determined based on the second distance spectrum data and the inversion matrix.

5. The signal processing method according to claim 4, characterized in that, Based on the aforementioned two-dimensional distance and velocity spectral data, second distance spectral data is determined, including: Based on the distance and velocity two-dimensional spectral data, the range dimension sidelobe amplitude of the signal in the first received signal is determined; Signals whose sidelobe amplitude is greater than or equal to the amplitude threshold in the distance dimension are identified as target signals. The second range spectrum data is determined based on the range spectrum data of the Doppler unit where the target signal is located in the two-dimensional range and velocity spectrum data.

6. The signal processing method according to claim 1, characterized in that, The method further includes: Based on the distance and velocity two-dimensional spectrum data of the first received signal, determine the Doppler cell where the maximum amplitude signal in the first received signal is located; From the range and velocity two-dimensional spectrum data of the first received signal, extract the range and velocity two-dimensional spectrum data of the Doppler unit where the maximum amplitude signal in the first received signal is located, and use it as the range and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal.

7. The signal processing method according to any one of claims 1-6, characterized in that, The first detection data includes distance detection and / or speed detection data. Based on the first distance detection data and the first detection data obtained from the first received signal, the second detection data is determined, including: Replace the distance detection data in the first detection data with the first distance detection data to obtain the second detection data, or... The second detection data is obtained by performing an OR operation on the first distance detection data and the first detection data.

8. A signal processing apparatus, characterized in that, The device includes: The first acquisition module is used to acquire a first received signal and process the first received signal to obtain two-dimensional spectrum data of distance and velocity. The first determining module is used to determine the first time-domain data based on the distance and velocity two-dimensional spectrum data; The processing module is used to filter the first time-domain data using a mismatch filter to obtain first distance spectrum data, wherein the parameters of the mismatch filter are determined based on the time-domain data of the second received signal or the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal, and the second received signal is a transmission leakage signal; The second acquisition module is used to obtain first distance detection data based on the first distance spectrum data; The second determining module is used to determine the second detection data based on the first distance detection data and the first detection data obtained from the first received signal; The device further includes: The third determining module is used to determine the maximum amplitude of the range-dimensional sidelobe in the second received signal based on the time-domain data of the second received signal. The fourth determining module is used to determine the desired filtered data of the second received signal based on the maximum amplitude of the range dimension sidelobe in the second received signal, wherein the amplitude of the range dimension sidelobe of the desired filtered data is lower than the maximum amplitude of the range dimension sidelobe in the second received signal. The fifth determining module is used to determine the parameters of the mismatch filter based on the time-domain data of the second received signal and the expected filtering data of the second received signal.

9. The signal processing apparatus according to claim 8, characterized in that, The device further includes: The third acquisition module is used to acquire the distance spectrum data with the maximum amplitude in the first received signal based on the two-dimensional distance and velocity spectrum data with the maximum amplitude in the first received signal. The sixth determining module is used to determine the parameters of the mismatch filter based on the distance spectrum data of the maximum amplitude in the first received signal.

10. The signal processing apparatus according to claim 8, characterized in that, The device includes: The seventh determining module is used to determine the Doppler unit where the maximum amplitude signal in the first received signal is located based on the two-dimensional spectrum data of distance and velocity of the first received signal; The eighth determining module is used to extract the distance and velocity two-dimensional spectrum data of the Doppler unit where the maximum amplitude signal in the first received signal is located from the distance and velocity two-dimensional spectrum data of the first received signal, and use it as the distance and velocity two-dimensional spectrum data of the maximum amplitude in the first received signal.

11. A signal processing apparatus, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the method of any one of claims 1-7 when executing the instructions.

12. A non-volatile computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1-7.

13. A vehicle, characterized in that, The vehicle includes the device as described in any one of claims 8-11.

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