Signal processing method, storage medium, integrated circuit, device and terminal equipment

Abstract

The embodiment of the invention relates to the technical field of communication, and discloses a signal processing method, a storage medium, an integrated circuit, a device and terminal equipment, and the method comprises the steps: carrying out the distance dimension FFT of a frame of to-be-processed signal, obtaining a to-be-processed signal, and dividing the to-be-processed signal into at least two subframes; velocity dimension FFT is carried out on the to-be-processed signal of each subframe to obtain distance-Doppler data of each subframe, and coherent processing and incoherent processing are carried out based on the distance-Doppler data of different subframes; and determining angle information of the target object according to a result of the coherent processing and a result of the non-coherent processing. According to the signal processing method provided by the embodiment of the invention, the angular resolution of the radar system can be greatly and stably improved without adding extra hardware, and the signal processing method also has good performance in a moving scene.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of communication technologies, and in particular, to a signal processing method, a storage medium, an integrated circuit, a device, and a terminal device. Background Art

[0002] A millimeter-wave radar can transmit modulated electromagnetic waves and receive signals reflected from surrounding targets. The received signals will be processed by a Fast Fourier Transform (FFT) and displayed as a dense point grid containing distance, velocity, and angle information for all processed FFT intervals, which is the Radar DataCube (RDC). As Figure 1 shown, after the RDC undergoes range-dimensional FFT (range-dimensional Fourier transform), velocity-dimensional FFT (Doppler-dimensional Fourier transform), and Constant False Alarm Rate (CFAR) detection, the distance information and velocity information of each target can be obtained. After angle estimation, a two-dimensional or three-dimensional point cloud distribution can be obtained, and tracking or positioning processing can be performed based on this point cloud distribution.

[0003] It can be understood that the richer the point cloud information, the more accurate the subsequent processing of tracking and positioning algorithms. In order to improve the quantity and quality of the point cloud, it is necessary to require the radar system to have higher resolution. Under the condition that the range resolution and velocity resolution are certain, the quality of the angle resolution is very crucial for improving the quantity and quality of the point cloud. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a signal processing method, a storage medium, an integrated circuit, a device, and a terminal device, which can significantly and stably improve the angle resolution of the radar system without adding additional hardware, and also have good performance in a mobile scenario.

[0005] To solve the above technical problems, an embodiment of the present application provides a signal processing method, including the following steps: performing range-dimensional FFT on a frame of signal to be processed to obtain the signal to be processed, and dividing the signal to be processed into at least two sub-frames; respectively performing velocity-dimensional FFT on the signals to be processed of each sub-frame to obtain range-Doppler data of each sub-frame, and performing coherent processing and non-coherent processing based on the range-Doppler data of different sub-frames; determining the angle information of the target object according to the results of the coherent processing and the non-coherent processing.

[0006] For a millimeter-wave radar, an embodiment of the present application further provides a signal processing method, which obtains a signal to be processed by performing range-dimensional FFT on an echo signal; performs multiple partial velocity-dimensional FFTs on the signal to be processed respectively to obtain a plurality of range-Doppler data; performs constant false alarm detection on the plurality of range-Doppler data to obtain corresponding multiple angle estimation data; performs velocity estimation based on the plurality of range-Doppler data to obtain range-velocity data; and performs target angle estimation based on the plurality of angle estimation data and the range-velocity data.

[0007] An embodiment of the present application further provides a computer-readable storage medium storing a computer program, which when executed by a processor can implement the signal processing method in the embodiment of the present application.

[0008] An embodiment of the present application further provides an integrated circuit, which may include: a signal transceiver channel, which can be used to transmit radio signals and receive echo signals formed by reflection of the radio signals by a target; a signal processing module, which is used to perform signal processing based on the above signal processing method. The signal processing module may include a sampling unit, a range-dimensional FFT unit, a velocity-dimensional FFT unit, a non-coherent processing unit, a coherent processing unit, and an execution unit: the sampling unit is used to sample the echo signal to obtain a sampled signal; the range-dimensional FFT unit is used to perform range-dimensional FFT on a frame of the sampled signal to obtain a signal to be processed and divide the signal to be processed into at least two sub-frames; the velocity-dimensional FFT unit is used to perform velocity-dimensional FFT on the signal to be processed of each sub-frame to obtain range-Doppler data of each sub-frame; the non-coherent processing unit is used to perform non-coherent processing based on the range-Doppler data of different sub-frames; the coherent processing unit is used to perform coherent processing based on the range-Doppler data of different sub-frames; the execution unit is used to determine the angle information of the target object according to the result of the coherent processing and the result of the non-coherent processing.

[0009] An embodiment of the present application further provides a radio device, including: a carrier; the integrated circuit as described above, disposed on the carrier; and an antenna, disposed on the carrier, for transmitting and receiving radio signals.

[0010] An embodiment of the present application further provides a terminal device, including: a device body; and the radio device as described above, disposed on the device body, where the radio device is used for target detection and / or communication.

[0011] The signal processing method, storage medium, integrated circuit, device, and terminal device provided by the embodiments of the present application, when estimating the angle of a target object, first perform range - dimension FFT on a frame of signal to be processed to obtain the signal to be processed, and divide the signal to be processed into at least two sub - frames. Then, perform velocity - dimension FFT on the signal to be processed in each sub - frame to obtain the range - Doppler data of each sub - frame. Subsequently, perform coherent processing and non - coherent processing based on the range - Doppler data of different sub - frames. Finally, determine the angle information of the target object according to the results of the coherent processing and the non - coherent processing. Considering the generally used technology in the industry to improve the angle resolution of radar systems, which is limited by factors such as radar size, computing power, and phase noise, the improvement of the angle resolution of radar systems is limited. However, the embodiments of the present application start from the perspective of signal processing. Based on the idea of sub - frame division, using the relative motion between the radar and the target object, the virtual aperture arrays formed by each sub - frame are spliced into a larger virtual aperture array after the entire frame is transmitted. Thus, without adding additional hardware, the angle resolution of the radar system can be improved without limit, and the whole process can be achieved through simple FFT processing. The effect of improving the angle resolution is very stable, and it has a good performance in mobile scenarios.

[0012] In some optional embodiments, the non - coherent processing includes: performing non - coherent accumulation on the range - Doppler data of different sub - frames, and performing constant false alarm detection based on the first data obtained from the non - coherent accumulation; according to the results of the constant false alarm detection, performing first - angle estimation on the range - Doppler data of each sub - frame respectively to obtain the result of the non - coherent processing; wherein, the result of the non - coherent processing is the first angle of the target object corresponding to each sub - frame. When performing non - coherent processing, constant false alarm detection is required, which can filter out unnecessary targets and false targets and improve the accuracy of subsequent angle estimation. The first - angle estimation can obtain a rough angle of the target object, preparing for the splitting and fine - angle estimation of the target object in the future.

[0013] In some optional embodiments, after obtaining the result of the non - coherent processing, the method further includes: arbitrarily selecting one sub - frame as the first sub - frame in each sub - frame, and taking the other sub - frames except the first sub - frame as the second sub - frames; respectively calculating the first difference between the first angle of the target object corresponding to each second sub - frame and the first angle of the target object corresponding to the first sub - frame; taking the second sub - frames whose absolute value of the first difference between the first sub - frame and the first difference is less than the first preset threshold as the retained sub - frames. If the fluctuation difference of the first angle between different sub - frames is very large, it indicates that the first angle estimated by some sub - frames is interfered and very inaccurate. Therefore, arbitrarily select one sub - frame as the first sub - frame, and based on the first sub - frame, select the sub - frames within the allowable fluctuation range to participate in the final angle estimation, which can further improve the accuracy of angle estimation.

[0014] In some alternative embodiments, after obtaining the result of the non-coherent processing, the method further includes: calculating a first average value of the first angles of the target object corresponding to each sub-frame; respectively calculating a second difference between the first angle of the target object corresponding to each sub-frame and the first average value; and using the sub-frames with the absolute value of the second difference less than a second preset threshold as the retained sub-frames. By calculating the average value, it can be more ensured that the determined retained sub-frames are more scientific and reasonable, thereby further improving the accuracy of angle estimation.

[0015] In some alternative embodiments, the coherent processing includes: performing coherent accumulation on the range-Doppler data of different sub-frames, and respectively performing velocity estimation on the range-Doppler data of each sub-frame based on the data obtained from the coherent accumulation to obtain the result of the coherent processing; wherein the result of the coherent processing is the velocity information of the target object corresponding to each sub-frame.

[0016] In some alternative embodiments, determining the angle information of the target object according to the result of the coherent processing and the result of the non-coherent processing includes: performing motion compensation on the target object according to the velocity information of the target object corresponding to the retained sub-frames; performing non-coherent accumulation on the range-Doppler data of the retained sub-frames, and performing a second angle estimation based on the second data obtained from the non-coherent accumulation to obtain the second angle of the target object. Using the velocity information of the target object obtained by the coherent processing to perform motion compensation on the target object and then perform angle estimation can splice the virtual aperture arrays formed by each sub-frame into a larger virtual aperture array after the entire frame transmission is completed, so as to distinguish target objects with very close distances and obtain accurate angle information of each target object.

[0017] In some alternative embodiments, after performing range-dimensional FFT on a frame of signal to be processed to obtain the signal to be processed, it further includes: determining the range information of the target object based on the signal to be processed; after obtaining the second angle of the target object, it further includes: obtaining point cloud data according to the range information, the velocity information and the second angle, and performing tracking and positioning on the target object based on the point cloud data.

[0018] In some alternative embodiments, dividing the signal to be processed into at least two sub-frames includes: dividing the signal to be processed into at least two consecutive sub-frames with equal lengths according to the frame length.

[0019] In some alternative embodiments, when dividing the signal to be processed into at least two sub - frames, the lengths of different sub - frames are allowed to be different, and partial overlap is allowed between two adjacent sub - frames. Allowing overlap when dividing sub - frames can ensure both the length of the sub - frames and the number of sub - frames, so that a larger and better - quality virtual aperture array can be obtained during subsequent processing.

[0020] In some alternative embodiments, the waveform of the signal to be processed is a continuous wave whose frequency changes linearly with time.

[0021] In some alternative embodiments, the continuous wave includes at least one of a frequency - modulated continuous wave (FMCW for short) and a stepped - frequency continuous wave (SFCW for short).

[0022] In some alternative embodiments, before obtaining the signal to be processed by performing distance - dimension FFT on the radar data cube, it further includes: acquiring an echo signal; mixing the echo signal to obtain an intermediate - frequency signal; performing analog - to - digital conversion on the intermediate - frequency signal to obtain a first discrete signal, and using the first discrete signal as the signal to be processed.

[0023] In some alternative embodiments, using the first discrete signal as the signal to be processed includes: performing at least one digital signal processing on the first discrete signal to obtain a second discrete signal; using the second discrete signal as the signal to be processed. Description of the Drawings

[0024] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings, and these exemplary illustrations do not limit the embodiments.

[0025] Figure 1 is a typical signal - processing flowchart of a millimeter - wave radar;

[0026] Figure 2 is a schematic diagram of multiple targets relative to a vehicle during the vehicle's driving;

[0027] Figure 3 is a flowchart of the signal - processing method provided in an embodiment of the present application;

[0028] Figure 4 is a schematic diagram of the sub - frame division result provided in an embodiment of the present application;

[0029] Figure 5 is another schematic diagram of the sub - frame division result provided in an embodiment of the present application;

[0030] Figure 6 It is a flowchart of non - coherent processing based on range - Doppler data of different sub - frames provided in an embodiment of the present application;

[0031] Figure 7 It is a flowchart of screening at least two divided sub - frames to determine the retained sub - frames provided in an embodiment of the present application;

[0032] Figure 8 It is another flowchart of screening at least two divided sub - frames to determine the retained sub - frames provided in an embodiment of the present application;

[0033] Figure 9 It is a schematic diagram of virtual aperture array splicing provided in an embodiment of the present application;

[0034] Figure 10 It is a schematic diagram of a signal processing method provided in another embodiment of the present application;

[0035] Figure 11 It is a schematic diagram of forming a frame of data processing by dividing sub - frames in an embodiment of the present application;

[0036] Figure 12 It is a schematic diagram of rough angle estimation for different channels in an embodiment of the present application;

[0037] Figure 13 It is a schematic diagram of the structure of an integrated circuit provided in an embodiment of the present application;

[0038] Figure 14 It is a schematic diagram of the structure of a signal processing module provided in an embodiment of the present application. Detailed implementation manners

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will elaborate on each embodiment of the present application with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in each embodiment of the present application, many technical details are provided to help readers better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in the present application can still be implemented. The division of the following embodiments is for convenience of description and should not constitute any limitation on the specific implementation manner of the present application. The embodiments can be combined and cross - referenced with each other on the premise of no contradiction.

[0040] Millimeter-wave radar can be applied to various vehicles such as cars, ships, and airplanes. In-vehicle millimeter-wave radar is an essential device in technologies such as autonomous driving and assisted driving. During the driving process of a vehicle, the in-vehicle millimeter-wave radar emits modulated electromagnetic waves and receives signals reflected from surrounding targets. After a series of signal processing, the distance information and speed information of each target are obtained. Through angle estimation, a two-dimensional or three-dimensional point cloud distribution can be obtained, and tracking or positioning processing can be performed based on this point cloud distribution. As Figure 2 shown, there are multiple such targets, including false targets such as vehicle exhaust and soot, and the distances between some targets are very close, and their angles relative to the vehicle are difficult to distinguish, which results in low angle resolution of in-vehicle radar under traditional signal processing methods.

[0041] Currently, common technologies for improving the angle resolution of radar systems include Multiple Input Multiple Output (MIMO) technology, sparse array technology, synthetic aperture radar technology, super-resolution algorithm technology, etc.

[0042] MIMO technology encodes on the transmitting side and decodes on the receiving side to form a larger virtual aperture array to obtain better angle resolution performance. MIMO technology includes Time Division Multiplexing (TDM), Frequency Division Multiplexing (FDM), Code Division Multiplexing (CDM), and Doppler Division Multiplexing (DDM), etc. However, due to problems such as radar size and phase noise, the performance improvement of MIMO technology in expanding the radar aperture and thus improving the angle resolution is very limited, and the cost is relatively high.

[0043] Sparse array technology changes the array distribution from uniform to non-uniform to obtain a larger virtual aperture array and achieve higher angle resolution. However, sparse array technology also brings some additional problems, such as excessive sidelobes and grating lobes.

[0044] Synthetic aperture radar technology realizes a larger virtual aperture array based on the relative motion between the radar and the target in the broadside direction of the radar to obtain higher angle resolution. However, synthetic aperture radar technology is only applicable to static scenes and performs poorly in mobile scenes.

[0045] Super-resolution algorithm techniques include subspace algorithms (such as MUSIC algorithm) and projection algorithms (maximum likelihood algorithm), etc. These algorithms are computationally complex, time-consuming, and not robust enough in mobile scenarios.

[0046] To solve the problems that the method for improving the angular resolution of radar is restricted by factors such as radar size, computing power, and phase noise, the improvement of the angular resolution of the radar system is limited and not robust, it performs poorly in mobile scenarios, and has poor universality, etc. An embodiment of the present application proposes a signal processing method, which can be specifically applied to a terminal or a processor. This embodiment and each of the following embodiments are described by taking the processor as an example. The implementation details of the signal processing method of this embodiment are specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution.

[0047] The specific process of the signal processing method of this embodiment can be as Figure 3 shown, including:

[0048] Step 101, perform range-dimensional FFT on a frame of signal to be processed to obtain the signal to be processed, and divide the signal to be processed into at least two sub-frames.

[0049] In specific implementation, after the processor samples the echo signal to obtain the signal to be processed in the form of a radar data cube, perform range-dimensional FFT on a frame of signal to be processed to obtain the signal to be processed, and divide the signal to be processed into at least two sub-frames. Each sub-frame corresponds to a virtual aperture.

[0050] In some examples, the processor can divide the signal to be processed into at least two consecutive sub-frames with equal length according to the frame length. As Figure 4 shown, the processor divides the signal to be processed into 4 consecutive sub-frames with equal length, and the two adjacent sub-frames are connected end to end to further improve the robustness of the radar system.

[0051] In some examples, when the processor divides the signal to be processed into at least two sub-frames, the lengths of different sub-frames are allowed to be different, and partial overlap is allowed between two adjacent sub-frames. As Figure 4 shown, the processor divides the signal to be processed into 4 sub-frames, and there is partial overlap between two adjacent sub-frames. Allowing overlap when dividing sub-frames can ensure both the length of the sub-frames and the number of sub-frames. A larger and better-quality virtual aperture array can be obtained during subsequent processing to further improve the angular resolution.

[0052] In some examples, the waveform of the signal to be processed is a continuous wave whose frequency changes linearly with time, and the continuous wave includes at least one of FMCW wave and SFCW wave.

[0053] In some examples, before the processor performs range - dimension FFT on a frame of signal to obtain the signal to be processed, it further includes: acquiring an echo signal; mixing the echo signal to obtain an intermediate - frequency signal; performing analog - to - digital conversion on the intermediate - frequency signal to obtain a first discrete signal (i.e., a digital signal), and using the first discrete signal as the signal to be detected. That is, angle estimation is performed at the ADC threshold.

[0054] In some examples, when the processor uses the first discrete signal as the signal to be detected, it may include: performing at least one digital signal processing on the first discrete signal to obtain a second discrete signal; using the second discrete signal as the signal to be detected. That is, in this embodiment, the second discrete signal obtained after digital signal processing can be used as the signal to be detected, that is, angle estimation is performed at the DSP threshold.

[0055] Step 102: Perform velocity - dimension FFT on the signals to be processed in each sub - frame respectively to obtain range - Doppler data for each sub - frame, and perform coherent processing and non - coherent processing based on the range - Doppler data of different sub - frames.

[0056] In a specific implementation, after the processor divides the signal to be processed into at least two sub - frames, it can perform velocity - dimension FFT (also known as Doppler - dimension FFT) on the signals to be processed in each sub - frame respectively to obtain range - Doppler data for each sub - frame, and perform coherent processing and / or non - coherent processing based on the range - Doppler data of different sub - frames.

[0057] In some examples, performing coherent processing based on the range - Doppler data of different sub - frames is specifically performing coherent integration based on the range - Doppler data of different sub - frames, and performing non - coherent processing based on the range - Doppler data of different sub - frames is specifically performing non - coherent integration based on the range - Doppler data of different sub - frames.

[0058] In some examples, when the processor performs non - coherent processing based on the range - Doppler data of different sub - frames, it can be implemented through the steps as shown in Figure 6 and specifically includes:

[0059] Step 201: Perform non - coherent integration on the range - Doppler data of different sub - frames, and perform constant false alarm rate (CFAR) detection based on the first data obtained from the non - coherent integration.

[0060] In a specific implementation, after the processor obtains the range - Doppler data for each sub - frame, it can perform non - coherent integration on the range - Doppler data of different sub - frames, and perform CFAR detection based on the first data obtained from the non - coherent integration. When performing non - coherent processing, CFAR detection is required, which can filter out unwanted targets and false targets, and improve the accuracy of subsequent angle estimation.

[0061] Step 202: According to the results of constant false alarm rate (CFAR) detection, perform first-angle estimation on the range-Doppler data of each sub-frame respectively to obtain the result of non-coherent processing.

[0062] In a specific implementation, the processor performs CFAR detection based on the first data obtained by non-coherent accumulation. After obtaining the results of CFAR detection, it can perform first-angle estimation on the range-Doppler data of each sub-frame respectively to obtain the result of non-coherent processing. The result of non-coherent processing is specifically the first angle of the target object corresponding to each sub-frame. The first-angle estimation can obtain a rough angle of the target object, that is, regarding several target objects with similar ranges as a whole, preparing for the subsequent splitting and fine-angle estimation of the target object. For example, data extraction is performed based on the data such as the range cells and Doppler cells corresponding to the targets detected by CFAR detection to serve as the basic data for subsequent first-angle estimation, thereby obtaining the rough angle information of the target object.

[0063] In some examples, after the processor obtains the result of non-coherent processing, it can Figure 7 screen at least two sub-frames divided through the steps shown as follows to determine the retained sub-frames, which specifically include:

[0064] Step 301: Arbitrarily select a sub-frame as the first sub-frame in each sub-frame, and regard the other sub-frames except the first sub-frame as the second sub-frames.

[0065] In a specific implementation, the processor needs to ensure that the first angles corresponding to each estimated sub-frame are scientific and reasonable. Therefore, after obtaining the result of non-coherent processing, it is necessary to screen at least two divided sub-frames. First, arbitrarily select a sub-frame as the first sub-frame (i.e., the screening basis) in each sub-frame, and regard the other sub-frames except the first sub-frame as the second sub-frames (i.e., the objects to be screened).

[0066] In an example, the processor divides the signal to be processed into 8 consecutive sub-frames. After obtaining the result of non-coherent processing, it selects the 5th sub-frame as the first sub-frame, then the 1st, 2nd, 3rd, 4th, 6th, 7th, and 8th sub-frames will automatically become 7 second sub-frames. Or, the processor divides the first FFT data into 8 consecutive sub-frames. After obtaining the result of non-coherent processing, it first selects the 1st to 4th sub-frames as the first sub-frames, and regards the 5th to 8th sub-frames as the second sub-frames to perform preprocessing operations to obtain the screening threshold; then based on this screening threshold, it selects a sub-frame that meets the screening threshold as the first sub-frame, and the rest are used as the second sub-frames, and then performs subsequent related operations such as those described in the embodiments of the present application.

[0067] Step 302: Calculate the first difference between the first angle of the target object corresponding to each second sub-frame and the first angle of the target object corresponding to the first sub-frame respectively.

[0068] Step 303: Use the second sub-frames for which the absolute value of the first difference between the first sub-frame and the first difference is less than the first preset threshold as the retained sub-frames.

[0069] In a specific implementation, after the processor determines the first sub-frame and the second sub-frames, it can calculate the first difference between the first angle of the target object corresponding to each second sub-frame and the first angle of the target object corresponding to the first sub-frame respectively, calculate the absolute value of each first difference, and sequentially determine whether the absolute value of each first difference is less than the first preset threshold. The processor uses the first sub-frame and the second sub-frames for which the absolute value of the first difference is less than the first preset threshold as the retained sub-frames. Among them, the first preset threshold can be set by those skilled in the art according to actual needs. Considering that if the fluctuation difference of the first angle between different sub-frames is very large, it indicates that the first angle estimated by some sub-frames is interfered and very inaccurate. Therefore, any sub-frame is selected as the first sub-frame, and the sub-frames within the allowable fluctuation range are selected based on the first sub-frame to participate in the final angle estimation, which can further improve the accuracy of angle estimation.

[0070] In an example, the processor divides the signal to be processed into 8 consecutive sub-frames, selects the 5th sub-frame as the first sub-frame, and the absolute values of the first differences between the first angles of the target objects corresponding to the 1st, 2nd, 3rd, 4th, 6th, 7th, and 8th sub-frames and the first angle of the target object corresponding to the 5th sub-frame are respectively: 0.4, 0.6, 1.2, 1.6, 0.3, 0.5, 0.4 (the unit is degree). When the first preset threshold is 1, the processor determines the 1st, 2nd, 5th, 6th, 7th, and 8th sub-frames as the retained sub-frames.

[0071] In some examples, after the processor obtains the result of non-coherent processing, it can Figure 8 screen at least two divided sub-frames through the steps shown as follows to determine the retained sub-frames, specifically including:

[0072] Step 401: Calculate the first average value of the first angles of the target objects corresponding to each sub-frame.

[0073] In a specific implementation, after the processor obtains the result of non-coherent processing, it can calculate the first average value of the first angles of the target objects corresponding to each sub-frame.

[0074] In one example, the processor divides the signal to be processed into 8 consecutive sub - frames. The first angles of the target objects corresponding to each sub - frame are 31.2, 32.1, 30.9, 31.5, 31.8, 32.2, 33.1, 31.7 (in degrees), and the first average value of the first angles of the target objects corresponding to each sub - frame calculated is 31.8 (rounded to one decimal place).

[0075] Step 402: Calculate the second differences between the first angles of the target objects corresponding to each sub - frame and the first average value respectively.

[0076] Step 403: Take the sub - frames whose absolute values of the second differences are less than the second preset threshold as the retained sub - frames.

[0077] In a specific implementation, after the processor calculates the first average value of the first angles of the target objects corresponding to each sub - frame, it can calculate the second differences between the first angles of the target objects corresponding to each sub - frame and the first average value respectively, and take the sub - frames whose absolute values of the second differences are less than the second preset threshold as the retained sub - frames. Among them, the second preset threshold can be set by those skilled in the art according to actual needs. By calculating the average value, it can ensure that the determined retained sub - frames are more scientific and reasonable, thereby further improving the accuracy of angle estimation.

[0078] In one example, the processor divides the signal to be processed into 8 consecutive sub - frames. The absolute values of the second differences between the first angles of the target objects corresponding to each sub - frame and the first average value are 0.6, 0.3, 0.9, 0.3, 0, 0.4, 1.3, 0.1 respectively. When the first preset threshold is 1, the processor determines the 1st, 2nd, 3rd, 4th, 5th, 6th, and 8th sub - frames as the retained sub - frames.

[0079] In some examples, the processor performs coherent accumulation on the range - Doppler data of different sub - frames, and based on the data obtained from the coherent accumulation, performs velocity estimation on the range - Doppler data of each sub - frame respectively to obtain the result of coherent processing. The result of coherent processing is the velocity information of the target object corresponding to each sub - frame.

[0080] Step 103: Determine the angle information of the target object according to the result of coherent processing and the result of non - coherent processing.

[0081] In some examples, the result of non-coherent processing is the first angle of the target object corresponding to each sub-frame, and the result of coherent processing is the velocity information of the target object corresponding to each sub-frame. When the processor determines the angle information of the target object based on the results of coherent processing and non-coherent processing, it first performs motion compensation on the target object according to the velocity information of the target object corresponding to the retained sub-frame, then performs non-coherent accumulation on the range-Doppler data of the retained sub-frame, and performs a second angle estimation based on the second data obtained from the non-coherent accumulation to obtain the second angle of the target object. By using the velocity information of the target object obtained through coherent processing to perform motion compensation on the target object and then performing accurate angle estimation, the virtual aperture arrays formed by each sub-frame can be stitched together into a larger virtual aperture array after the entire frame transmission is completed, so as to distinguish target objects with very close distances and obtain accurate angle information of each target object.

[0082] As Figure 9 shown, the vehicle (vehicle-mounted millimeter-wave radar) moves in the Figure 9 given direction. During the transmission of a frame of signal, the relative position of the target object with respect to the vehicle remains basically unchanged. The processor divides the signal to be processed into 4 consecutive sub-frames, and each sub-frame corresponds to a small virtual aperture array. When the velocity information of the vehicle is determined, the processor can fuse the 4 small virtual aperture arrays into a large virtual aperture array. Since the aperture of the virtual aperture array corresponding to each sub-frame is relatively small, it is impossible to distinguish between target object 1 and target object 2, and the two can only be regarded as a whole. Therefore, when performing angle estimation with the virtual aperture array corresponding to each sub-frame, only a rough first angle can be obtained. After the entire frame transmission is completed and the large virtual aperture array is formed, the processor can then distinguish the two targets, that is, the second angles of the fine target object 1 and target object 2 can be obtained, thus achieving an improvement in angle resolution.

[0083] In one example, after the processor performs range-dimensional FFT on a frame of signal to be processed to obtain the signal to be processed, it can also determine the range information of the target object based on the signal to be processed. After the processor obtains the second angle of the target object, it can also obtain point cloud data according to the range information, velocity information, and second angle of the target object, etc., and perform operations such as tracking and positioning on the target object based on the point cloud data.

[0084] In this embodiment, when estimating the angle of a target object, first perform range-dimensional FFT on a frame of signal to be processed to obtain the signal to be processed, and divide the signal to be processed into at least two sub-frames. Then, perform velocity-dimensional FFT on the signal to be processed in each sub-frame to obtain the range-Doppler data of each sub-frame. Subsequently, perform coherent processing and non-coherent processing based on the range-Doppler data of different sub-frames. Finally, determine the angle information of the target object according to the results of the coherent processing and the non-coherent processing. Considering the general technology in the industry to improve the angle resolution of radar systems, which is limited by factors such as radar size, computing power, and phase noise, the improvement of the radar system's angle resolution is limited. However, the embodiment of this application starts from the perspective of signal processing. Based on the idea of sub-frame division, using the relative motion between the radar and the target object, the virtual aperture arrays formed by each sub-frame are spliced into a larger virtual aperture array after the entire frame is transmitted. Thus, without adding additional hardware, the angle resolution of the radar system can be improved without limit, and the whole process can be achieved through simple FFT processing. The improvement effect of the angle resolution is very stable and has a good performance in mobile scenarios.

[0085] Figure 10 It is a schematic diagram of the signal processing method provided in another embodiment of this application. As Figure 10 shown, a signal processing method is applied to improve millimeter-wave radar. The method may include the following:

[0086] After performing operations such as ADC on the echo signal, that is, after collecting the data of the entire frame (i.e., Radar data cube), continue with velocity-dimensional Fourier transform processing (Range FFT) to obtain a frame of Range FFT result data, and use this frame of Range FFT result data as the signal data to be processed for subsequent processing. That is, this frame of Range FFT result data can be divided into four sub-frames.

[0087] Perform the velocity dimension Fourier transform processing (Partial Doppler FFT) for each sub-frame respectively, and perform non-coherent combination on the range-doppler FFT results of multiple (partial or all of them can be selected) sub-frames, as well as constant false alarm rate detection (CFAR detection), etc. Coarse angle estimation is performed on the range-doppler FFT results and CFAR results of each sub-frame respectively, and the values of the coarse angle estimation can be screened to further improve the accuracy of angle estimation. For example, for the coarse angle estimation results located in the same range-doppler cell, if the value fluctuation range between different sub-frames is greater than the preset range, it can be filtered out, and the sub-frame data with angle fluctuation within the preset range can be selected for subsequent fine angle estimation.

[0088] Similarly, coherent processing (fine velocity estimation) can also be synchronously performed on the range-doppler FFT results of the above multiple sub-frames to obtain relatively fine target velocity estimation data. At the same time, based on this relatively fine target velocity estimation data, combined with the above coarse angle estimation results (or the screened coarse angle estimation results), subsequent fine angle estimation operations can be performed to achieve the purpose of improving the angle resolution of the millimeter-wave radar.

[0089] Finally, subsequent positioning, tracking, imaging, etc. operations can be performed based on the result data of the above fine angle estimation (such as the point cloud containing range-velocity-angle).

[0090] It should be noted that there can be partial overlap or adjacent arrangement between the data of adjacent sub-frames. At the same time, one frame of data can be divided into four, six, eight or other numbers of sub-frames. As Figure 11 shown, for the scenario containing four sub-frames, each sub-frame contains eight data elements (such as range bins). If there are six overlapping data elements between adjacent sub-frames, that is, one frame of data before sub-frame division contains 14 data elements. After performing Doppler FFT respectively, a data array containing 32 range-doppler cells can be formed.

[0091] In an alternative embodiment, as Figure 12As shown, if the number of virtual channels is N, for any virtual channel, after constant false alarm detection is completed, for any target (R, V), a vector S = {S0, S1... Si}, 0 < i ≤ N, can be obtained by extracting its 2D-FFT data in different channels. R0 represents the index of the range dimension, and V0 represents the index of the velocity dimension. At this time, this vector data can be used to roughly estimate the angle of the target (R, V) by means such as FFT, DBF, MUSIC, CS, etc.

[0092] For example, when using DBF for rough angle estimation, for any array, the positions of each array element are (X0, X1... X N-1 ), and its response in the direction of angle θ is:

[0093]

[0094] Then, DBF is to use each direction θ0, θ1... θ M-1 for matched filtering, that is:

[0095] P(θ) = |S × W(θ)| 2

[0096] Subsequently, after obtaining P(θ) in each direction, the angle direction of the target can be obtained based on this data spectrum. Among them, λ can be the wavelength corresponding to the center frequency point of the echo signal.

[0097] In summary, for FMCW millimeter waves, in combination with the technical content of this application, during the process of signal processing of echo information, after range FFT (Rang FFT), based on the Rang FFT data, one frame of Rang FFT data can be divided into two, three, or four sub-frames, that is, one frame of data can be divided into at least two sub-frames, which can be specifically set according to actual needs. For each sub-frame, velocity dimension FFT, also known as Doppler dimension Fourier transform (Doppler FFT), that is, perform Figure 10 the partial Fourier transform (Partial Doppler FFT) shown, and then perform subsequent processing based on the Doppler FFT data of each sub-frame to perform two different angle estimations.

[0098] For example, non-coherent processing can be first performed based on the Doppler FFT data of each sub-frame to obtain a first (coarse) angle estimate. Specifically, constant false alarm detection and angle estimation can be performed on the Doppler FFT data of each sub-frame to obtain the first angle estimate value corresponding to each sub-frame. Then, coherent combining processing is performed on the Doppler FFT data of all sub-frames to obtain a refined target velocity estimate value. Finally, after filtering (Angle filtering) the above-mentioned first angle estimate value based on the refined target velocity estimate value, a second (fine) angle estimate with higher resolution is obtained. Specifically, by targeting the same range-Doppler cell, the estimated targets with angle fluctuations within the threshold range between different sub-frames can be determined as the same real target, thereby effectively improving the resolution of the target angle on the premise that the range and velocity resolutions remain unchanged.

[0099] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, they are all within the protection scope of this patent; adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of its algorithm and process are all within the protection scope of this patent.

[0100] Another embodiment of this application relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0101] That is, those skilled in the art can understand that all or part of the steps in implementing the above method embodiments can be completed by a program instructing relevant hardware. The program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of this application (such as interference detection methods and / or constant false alarm detection methods, etc.). The aforementioned storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0102] Another embodiment of this application relates to an integrated circuit. The details of the integrated circuit of this embodiment are specifically described below. The following content is only implementation details provided for convenient understanding and is not necessary for implementing this solution. The schematic diagram of the integrated circuit of this embodiment can be as Figure 13As shown, the integrated circuit may include a signal transceiver channel 501, a signal processing module 502, etc. The signal transceiver channel 501 may be used to transmit radio signals and receive echo signals formed by the reflection of the radio signals by the target. The signal processing module 502 may be used to perform signal processing based on the signal processing method as described above. In some examples, the signal processing module 502 is as Figure 14 shown and may include a sampling unit 5021, a range-dimension FFT unit 5022, a velocity-dimension FFT unit 5023, a non-coherent processing unit 5024, a coherent processing unit 5025, an execution unit 5026, etc. Among them, the sampling unit 5021 may be used to sample the echo signal to obtain a sampled signal. The range-dimension FFT unit 5022 may be used to perform range-dimension FFT on a frame of sampled signals to obtain a signal to be processed and divide the signal to be processed into at least two sub-frames. The velocity-dimension FFT unit 5023 may be used to perform velocity-dimension FFT on the signals to be processed in each sub-frame to obtain range-Doppler data for each sub-frame. The non-coherent processing unit 5024 may be used to perform non-coherent processing based on the range-Doppler data of different sub-frames. The coherent processing unit 5025 may be used to perform coherent processing based on the range-Doppler data of different sub-frames. The execution unit 5026 may be used to determine the angle information of the target object according to the results of the coherent processing and the non-coherent processing.

[0103] It is worth mentioning that each module involved in this embodiment is a logical module. In practical applications, a logical unit may be a physical unit, a part of a physical unit, or implemented as a combination of multiple physical units. In addition, in order to highlight the innovative part of this application, units that are not closely related to solving the technical problems proposed in this application are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0104] In some alternative embodiments, the above integrated circuit may be a millimeter-wave radar chip or a lidar chip (such as an FMCW lidar chip), etc., for obtaining information such as the distance, angle, velocity, shape, size, surface roughness, and dielectric properties of the target. Optionally, the integrated circuit may be an Antenna-In-Package (abbreviation: AiP) chip structure, an Antenna-On-Package (abbreviation: AoP) chip structure, or an Antenna-On-Chip (abbreviation: AoC) chip structure, etc.

[0105] In an optional embodiment, different integrated circuits (such as chips) can be combined with each other to form a cascade structure. For the sake of simplicity, it will not be elaborated here, but it should be understood that all the technologies that those skilled in the art should be aware of based on the content recorded in this application should be included within the scope recorded in this application.

[0106] Another embodiment of this application relates to a radio device, which includes a carrier, the integrated circuit as described above disposed on the carrier, and an antenna disposed on the carrier for receiving and transmitting radio signals. The antenna can be integrated with the integrated circuit into an integrated device and disposed on the carrier (that is, at this time, the antenna can be the antenna provided in the AiP or AoC structure), and the integrated circuit can also be two discrete components from the antenna, and a system-on-chip (SoC) structure is formed through connection. Among them, the carrier can be a printed circuit board (PCB), such as a development board, a data acquisition board, or the main board of a device, etc., and the first transmission line can be a PCB trace.

[0107] In some optional embodiments, this application also provides a terminal device, which may include a device body and the radio device described in any of the above embodiments disposed on the device body; wherein, the radio device can be used to implement functions such as target detection and / or wireless communication.

[0108] Specifically, based on the above embodiments, in some optional embodiments of this application, the radio device can be disposed outside the device body or inside the device body, and in other optional embodiments of this application, part of the radio device can be disposed inside the device body and part can be disposed outside the device body. The embodiments of this application do not limit this, and it can be determined according to the specific situation.

[0109] In some alternative embodiments, the above-mentioned device body can be components and products applied in fields such as smart cities, smart homes, transportation, smart home appliances, consumer electronics, security monitoring, industrial automation, in-cabin detection (such as smart cockpits), medical devices, and healthcare. For example, the device body can be a smart transportation device (such as a car, bicycle, motorcycle, ship, subway, train, etc.), a security device (such as a camera), a liquid level / flow rate detection device, a smart wearable device (such as a bracelet, glasses, etc.), a smart home appliance (such as a floor cleaning robot, door lock, TV, air conditioner, smart light, etc.), various communication devices (such as a mobile phone, tablet computer, etc.), as well as a gate, smart traffic lights, smart signs, traffic cameras, and various industrial robotic arms (or robots), and can also be various instruments for detecting vital sign parameters and various devices equipped with such instruments, such as in-car vital sign detection in a car, indoor personnel monitoring, smart medical devices, consumer electronic devices, etc.

[0110] The radio device can be the radio device described in any embodiment of the present application. The structure and working principle of the radio device have been described in detail in the above embodiments and will not be elaborated here one by one.

[0111] It should be noted that the radio device can achieve functions such as target detection and / or communication by transmitting and receiving radio signals, so as to provide detection target information and / or communication information to the device body, thereby assisting or even controlling the operation of the device body.

[0112] For example, when the above-mentioned device body is applied to an Advanced Driving Assistance System (ADAS), the radio device as an in-vehicle sensor (such as a millimeter-wave radar, lidar, etc.) can assist the ADAS system to achieve application scenarios such as adaptive cruise control, Autonomous Emergency Braking (AEB), Blind Spot Detection (BSD), Lane Change Assist (LCA), Rear Cross Traffic Alert (RCTA), parking assistance, warning of rear vehicles, anti-collision, pedestrian detection, etc., and can also be applied to application scenarios such as anti-collision when opening the door of a car.

[0113] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0114] The above-described embodiments merely represent the preferred embodiments of the present application and the technical principles applied. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. Those skilled in the art can make various obvious changes, readjustments, and substitutions without departing from the protection scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments. Without departing from the concept of the present application, it can also include more other equivalent embodiments, and the protection scope of the present application is determined by the scope of the appended claims.

Claims

1. A signal processing method, characterized in that, Applied to improve millimeter-wave radar, the method includes: Performing range-dimensional FFT on the echo signal to obtain a signal to be processed; Performing multiple partial velocity-dimensional FFTs on the signal to be processed respectively to obtain multiple range-Doppler data; Performing constant false alarm detection on the multiple range-Doppler data to obtain corresponding multiple angle estimation data; Performing velocity estimation based on the multiple range-Doppler data to obtain range-velocity data; and Performing target angle estimation based on the multiple angle estimation data and the range-velocity data.

2. The signal processing method according to claim 1, wherein When performing signal processing based on one frame of the signal to be processed, the method further includes: Dividing one frame of the signal to be processed into at least two sub-frames; and Performing the partial velocity-dimensional FFT once based on one sub-frame.

3. The signal processing method according to claim 2, wherein There is partial overlap between the data of adjacent sub-frames.

4. A signal processing method, characterized in that, Including: Performing range-dimensional FFT on one frame of the signal to be processed to obtain the signal to be processed, and dividing the signal to be processed into at least two sub-frames; Performing velocity-dimensional FFT on the signal to be processed of each sub-frame respectively to obtain the range-Doppler data of each sub-frame, and performing coherent processing and non-coherent processing based on the range-Doppler data of different sub-frames; Determining the angle information of the target object according to the result of the coherent processing and the result of the non-coherent processing.

5. The signal processing method according to claim 4, wherein The non-coherent processing includes: Performing non-coherent accumulation on the range-Doppler data of different sub-frames, and performing constant false alarm detection based on the first data obtained from the non-coherent accumulation; According to the result of the constant false alarm detection, performing first angle estimation on the range-Doppler data of each sub-frame respectively to obtain the result of the non-coherent processing; wherein, the result of the non-coherent processing is the first angle of the target object corresponding to each sub-frame.

6. The signal processing method according to claim 5, wherein After obtaining the result of the non-coherent processing, the method further includes: Arbitrarily selecting one sub-frame from each sub-frame as the first sub-frame, and taking the other sub-frames except the first sub-frame as the second sub-frames; Calculating the first difference between the first angle of the target object corresponding to each second sub-frame and the first angle of the target object corresponding to the first sub-frame respectively; Taking the first sub-frame and the second sub-frames whose absolute value of the first difference is less than the first preset threshold as the reserved sub-frames.

7. The signal processing method according to claim 5, characterized in that, After obtaining the result of the non-coherent processing, the method further includes: Calculating the first average value of the first angles of the target object corresponding to each sub-frame; Calculating the second difference between the first angle of the target object corresponding to each sub-frame and the first average value respectively; Taking the sub-frames whose absolute value of the second difference is less than the second preset threshold as the reserved sub-frames.

8. The signal processing method according to claim 6 or 7, characterized in that The coherent processing includes: Performing coherent accumulation on the range-Doppler data of different sub-frames, and based on the data obtained from the coherent accumulation, performing velocity estimation on the range-Doppler data of each sub-frame respectively to obtain the result of the coherent processing; wherein, the result of the coherent processing is the velocity information of the target object corresponding to each sub-frame.

9. The signal processing method according to claim 8, wherein The determining the angle information of the target object according to the result of the coherent processing and the result of the non-coherent processing includes: Perform motion compensation on the target object according to the speed information of the target object corresponding to the reserved subframe; Perform non-coherent accumulation on the range-Doppler data of the reserved subframe, and perform a second angle estimation based on the second data obtained from the non-coherent accumulation to obtain the second angle of the target object.

10. The signal processing method according to claim 9, wherein After obtaining the processed signal by performing range dimension FFT on a frame of the signal to be processed, it further includes: Determine the range information of the target object based on the processed signal; After obtaining the second angle of the target object, it further includes: Obtain point cloud data according to the range information, the speed information, and the second angle, and perform tracking and positioning on the target object based on the point cloud data.

11. The signal processing method according to any one of claims 4 to 7, characterized in that The dividing the signal to be processed into at least two subframes includes: Divide the signal to be processed into at least two consecutive subframes with equal lengths according to the frame length.

12. The signal processing method according to any one of claims 4 to 7, characterized in that When dividing the signal to be processed into at least two subframes, the lengths of different subframes are allowed to be different, and partial overlap is allowed between two adjacent subframes.

13. The signal processing method according to any one of claims 4 to 7, characterized in that The waveform of the signal to be processed is a continuous wave whose frequency changes linearly with time.

14. The signal processing method according to claim 12, wherein the continuous wave includes at least one of frequency-modulated continuous wave (FMCW) and stepped-frequency continuous wave (SFCW).

15. The signal processing method according to any one of claims 4 to 7, characterized in that Before obtaining the processed signal by performing range dimension FFT on a frame of the signal to be processed, it further includes: Acquire an echo signal; Mix the echo signal to obtain an intermediate-frequency signal; Perform analog-to-digital conversion on the intermediate-frequency signal to obtain a first discrete signal, and use the first discrete signal as the signal to be processed.

16. The signal processing method according to claim 15, wherein, The using the first discrete signal as the signal to be processed includes: Perform at least one digital signal processing on the first discrete signal to obtain a second discrete signal; Use the second discrete signal as the signal to be processed.

17. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the signal processing method according to any one of claims 1 to 16.

18. An integrated circuit, characterized in that, It includes: A signal transceiver channel for transmitting a radio signal and receiving an echo signal formed by reflection of the radio signal by a target; A signal processing module for performing signal processing based on the method according to any one of claims 1 to 16.

19. The integrated circuit according to claim 18, wherein The signal processing module includes: A sampling unit for sampling the echo signal to obtain a sampled signal; A range dimension FFT unit for performing range dimension FFT on a frame of the sampled signal to obtain a processed signal and dividing the processed signal into at least two subframes; A velocity dimension FFT unit for performing velocity dimension FFT on the processed signal of each subframe to obtain the range-Doppler data of each subframe; A non-coherent processing unit for performing non-coherent processing based on the range-Doppler data of different subframes; A coherent processing unit for performing coherent processing based on the range-Doppler data of different subframes; An execution unit for determining the angle information of the target object according to the results of the coherent processing and the non-coherent processing.

20. A radio device, characterized in that, It includes: A carrier; The integrated circuit according to any one of claims 18 to 19 is disposed on the carrier; An antenna, disposed on the carrier, for receiving and transmitting radio signals.

21. A terminal device, characterized in that, Comprising: The device body; The radio device as described in claim 20 disposed on the device body, the radio device being used for target detection and / or communication.

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