Radar data processing method and device, storage medium and electronic equipment

Abstract

The invention discloses a radar data processing method and device, a storage medium and electronic equipment. The method comprises the following steps: determining a distance parameter and a virtual subarray parameter which are used for detecting a short-distance object; determining a target distance unit serial number corresponding to the distance parameter under the condition that first radar data matched with the target space region is obtained; determining a first radar data subset matched with the close-range object from the first radar data according to the target distance unit serial number; according to a matrix splicing mode indicated by the virtual sub-array parameters, Doppler emission demodulation operation is executed on the first radar data subset to obtain second radar data, and the second radar data is used for detecting a close-range object in the target space area to obtain the target space area. The short-distance object is an object within the target distance indicated by the distance parameter in the target space area. The technical problems of low radar data processing efficiency and poor processing accuracy in the prior art are solved.

Description

Technical Field

[0001] This application relates to the field of autonomous driving, and more particularly, to a method, apparatus, storage medium, and electronic device for processing radar data. Background Art

[0002] With the wide application of millimeter-wave radar in the autonomous driving industry, the requirements for the farthest detection distance, ranging, speed measurement, and angle measurement performance are gradually increasing. The MIMO (Multiple-Input Multiple-Output) virtual array technology improves the spatial resolution by increasing the virtual channels. An MIMO radar with Nr receiving antennas and Nt transmitting antennas can form a virtual antenna array with an Nr×Nt dimension, greatly increasing the antenna aperture to improve the target angle resolution. The application of the DDMA (Doppler Domain Multiple Access) waveform technology, by simultaneously transmitting radar signals through Nt different transmitting antennas, can obtain a higher transmit gain under the same time requirement compared with the traditional time-division multiplexing multiple-input multiple-output technology (TDM-MIMO). However, the target echo signal of the DDMA waveform will have Nt energy components in the Doppler dimension, so it is necessary to determine the order of the transmitting antennas to obtain the true target speed.

[0003] Since the DDMA waveform transmitting channel will increase the Doppler sidelobe during receiving and demodulation, in an environment with strong near-range multi-targets and clutter, the false alarm probability of target detection and processing increases particularly significantly. That is to say, there are technical problems of inaccurate and low-efficiency radar data processing in the prior art. Summary of the Invention

[0004] Embodiments of this application provide a method, apparatus, storage medium, and electronic device for processing radar data, so as to at least solve the technical problem of poor accuracy in processing radar data in the prior art.

[0005] According to one aspect of the embodiments of the present application, a method for processing radar data is provided, including: determining a distance parameter and a virtual sub-array parameter for detecting a short-range object, where the distance parameter is used to indicate the distance interval corresponding to the short-range object, and the virtual sub-array parameter is used to indicate the element arrangement mode of the transmitting sub-array matched with the short-range object; when obtaining first radar data matched with a target space region, determining a target distance unit number corresponding to the distance parameter, where the first radar data is obtained by performing a fast Fourier transform operation on target echo data, and the target echo data is echo data received by a target radar object and matched with the target space region; determining a first radar data subset matched with the short-range object from the first radar data according to the target distance unit number; performing a Doppler transmit demodulation operation on the first radar data subset according to the matrix splicing mode indicated by the virtual sub-array parameter to obtain second radar data, where the second radar data is used to detect the short-range object in the target space region, and the short-range object is an object within the target distance indicated by the distance parameter in the target space region.

[0006] According to another aspect of the embodiments of the present application, a device for processing radar data is further provided, including: a first determination unit, configured to determine a distance parameter and a virtual sub-array parameter for detecting a short-range object, where the distance parameter is used to indicate the distance interval corresponding to the short-range object, and the virtual sub-array parameter is used to indicate the element arrangement mode of the transmitting sub-array matched with the short-range object; a second determination unit, configured to determine a target distance unit number corresponding to the distance parameter when obtaining first radar data matched with a target space region, where the first radar data is obtained by performing a fast Fourier transform operation on target echo data, and the target echo data is echo data received by a target radar object and matched with the target space region; a screening unit, configured to determine a first radar data subset matched with the short-range object from the first radar data according to the target distance unit number; a demodulation unit, configured to perform a Doppler transmit demodulation operation on the first radar data subset according to the matrix splicing mode indicated by the virtual sub-array parameter to obtain second radar data, where the second radar data is used to detect the short-range object in the target space region, and the short-range object is an object within the target distance indicated by the distance parameter in the target space region.

[0007] As an alternative solution, the above demodulation unit includes: an acquisition module for acquiring a Doppler unit serial number that matches the transmit phase offset parameter of the above target radar object; a cyclic shift module for performing a cyclic shift operation on the above first radar data subset according to the cyclic shift parameter indicated by the above Doppler unit serial number to obtain a first reference data subset; a determination module for determining a target matrix splicing method according to the element serial number and element position of the transmit array element indicated by the above virtual subarray parameter; a splicing module for splicing a plurality of data matrices included in the above first reference data subset according to the above target matrix splicing method to obtain the above second radar data, where the above virtual subarray parameter is determined by a simulation operation performed on the above target radar object.

[0008] As an alternative solution, the above radar data processing device further includes: a first determination module for determining the above target distance unit serial number according to the ratio between the above distance parameter and the distance resolution of the above target radar object; a second determination module for determining the above Doppler unit serial number according to the product of the above transmit phase offset parameter and a first signal quantity parameter, where the above first signal quantity parameter is used to indicate the number of modulation signals included in one frame of radar signal transmitted by the above target radar object.

[0009] As an alternative solution, the above radar data processing device further includes: a detection unit for acquiring the number of points in the azimuth dimension that matches the above virtual subarray parameter; performing a fast Fourier transform operation on the above second radar data in the azimuth dimension according to the number of points in the azimuth dimension and the arrangement method of the virtual array channels corresponding to the above virtual subarray parameter to obtain target radar data; performing an object detection operation according to the above target radar data.

[0010] As an alternative solution, the above screening unit is further used to: determine a second radar data subset that matches a far-distance object from the above first radar data according to the above target distance unit serial number, where the distance unit serial number of the data elements in the above first radar data subset is less than or equal to the above target distance unit serial number, and the distance unit serial number of the data elements in the above second radar data subset is greater than the above target distance unit serial number.

[0011] As an alternative solution, the above screening unit is further configured to: determine a target angular unit serial number range for detecting a far-distance object; perform a Doppler transmit demodulation operation on the second radar data subset according to the target distance unit serial number to obtain third radar data; perform a fast Fourier transform operation on the third radar data in the azimuth dimension according to the arrangement mode corresponding to the number of points in the azimuth dimension matched with the far-distance object and the virtual array channels corresponding to the far-distance virtual subarray parameters to obtain far-distance three-dimensional radar data; determine a far-distance three-dimensional data subset from the far-distance three-dimensional radar data according to the target angular unit serial number range, where the angular unit serial numbers of the data elements included in the far-distance three-dimensional data subset are within the target angular unit serial number range; and determine the far-distance three-dimensional data subset as the reference radar data for object detection of the far-distance object, where the far-distance object is an object outside the target distance indicated by the distance parameter in the target spatial region.

[0012] As an alternative solution, the processing of the above radar data further includes: a simulation unit, configured to, when determining the number of transmit array elements and receive array elements of the target radar object, obtain a plurality of candidate code pattern combinations, where the candidate code pattern combinations are used to indicate the number of array elements and the array element serial numbers of at least one object array element extracted from a plurality of transmit array elements; obtain first simulation results corresponding to the plurality of candidate code pattern combinations respectively, where the first simulation results include at least one of the following: the sidelobe height of at least one Doppler sidelobe, the position of at least one of the Doppler sidelobes; and determine at least one first code pattern combination from the plurality of candidate code pattern combinations according to the first simulation results corresponding to the plurality of candidate code pattern combinations respectively, where the virtual subarray parameters are used to indicate the first code pattern combination.

[0013] As an alternative solution, the simulation unit is configured to perform at least one of the following: when the sidelobe height of at least one Doppler sidelobe corresponding to the current candidate code pattern combination among the plurality of candidate code pattern combinations is less than or equal to a first threshold, determine the current candidate code pattern combination as the first code pattern combination; and when the distribution state of at least one Doppler sidelobe corresponding to the current candidate code pattern combination among the plurality of candidate code pattern combinations is less than or equal to a second threshold, determine the current candidate code pattern combination as the first code pattern combination.

[0014] As an alternative solution, the above simulation unit is further configured to: obtain at least one reference radar array information; according to the at least one reference radar array information, the distance parameter, and the angle interval parameter, obtain target simulation results respectively corresponding to the at least one reference radar array information, where the target simulation results include main-to-side lobe ratio parameters; according to the target simulation results, determine target radar array information from the at least one reference radar array information, where the target radar array information is used to indicate the array parameters of the target radar object.

[0015] As an alternative solution, the above simulation unit is further configured to: obtain the height estimation parameter of the above short-range object; according to the height estimation parameter and multiple candidate object distances, determine the elevation angles respectively corresponding to the multiple candidate object distances; when at least one reference radar array information is obtained, obtain at least one reference simulation result according to the reference radar array information and the multiple elevation angles, where the reference simulation results include at least one of the following: angle measurement error value, main-to-side lobe ratio change rate; determine the distance parameter according to the at least one reference simulation result that satisfies the first constraint condition.

[0016] According to another aspect of the embodiments of the present application, there is provided a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above method for processing radar data.

[0017] According to another aspect of the embodiments of the present application, there is further provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the above method for processing radar data through the computer program.

[0018] In the above embodiments of the present application, determine the distance parameter and the virtual sub-array parameter for detecting the short-range object; when the first radar data matching the target space region is obtained, determine the target distance unit number corresponding to the distance parameter; determine the first radar data subset matching the short-range object from the first radar data according to the target distance unit number; perform a Doppler transmit demodulation operation on the first radar data subset according to the matrix splicing method indicated by the virtual sub-array parameter to obtain the second radar data, where the second radar data is used to detect the short-range object in the target space region, and the short-range object is an object within the target distance indicated by the distance parameter in the target space region, and thus the short-range object can be further detected through the second radar data.

[0019] Through the above embodiments of the present application, first, according to the distance parameter and the serial number of the target distance unit matching the distance parameter, a data subset corresponding to the near-range space (where the near-range object is located in the near-range space) is separated from the first radar data, that is, the first radar data subset, thereby reducing the data processing volume in the process of identifying the near-range object; further, in the process of performing Doppler transmit demodulation operation on the first radar data subset, based on the matrix splicing method corresponding to the virtual subarray, the Doppler transmit demodulation operation is performed on the first radar data subset, and then the Doppler dimension sidelobes can be suppressed through the virtual subarray determined by pre-simulation, thereby improving the measurement accuracy of the near-range object and solving the technical problem of poor processing accuracy of radar data in the prior art. Description of the Drawings

[0020] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments and descriptions thereof of the present application are used to explain the present application, and do not constitute an improper limitation to the present application. In the drawings:

[0021] Figure 1 is a schematic diagram of the application environment of an optional method for processing radar data according to an embodiment of the present application;

[0022] Figure 2 is a flowchart of an optional method for processing radar data according to an embodiment of the present application;

[0023] Figure 3 is a flowchart of another optional method for processing radar data according to an embodiment of the present application;

[0024] Figure 4 is a schematic diagram of an optional Doppler sidelobe distribution according to an embodiment of the present application;

[0025] Figure 5 is a schematic diagram of an optional Doppler sidelobe distribution according to an embodiment of the present application;

[0026] Figure 6 is a flowchart of yet another optional method for processing radar data according to an embodiment of the present application;

[0027] Figure 7 is a schematic diagram of an optional radar antenna layout according to an embodiment of the present application;

[0028] Figure 8 is a schematic diagram of an optional angle dimension spectrum according to an embodiment of the present application;

[0029] Figure 9 is a schematic diagram of the influence of an optional main-to-side lobe ratio according to an embodiment of the present application;

[0030] Figure 10 It is another optional angular dimension spectrum schematic diagram according to an embodiment of the present application;

[0031] Figure 11 It is a flowchart of another optional method for processing radar data according to an embodiment of the present application;

[0032] Figure 12 It is a schematic diagram of the relationship between an optional distance and elevation angle according to an embodiment of the present application;

[0033] Figure 13 It is a schematic diagram of an optional azimuth angle measurement error according to an embodiment of the present application;

[0034] Figure 14 It is another optional main-to-side lobe ratio influence schematic diagram according to an embodiment of the present application;

[0035] Figure 15 It is a flowchart of another optional method for processing radar data according to an embodiment of the present application;

[0036] Figure 16 It is a flowchart of another optional method for processing radar data according to an embodiment of the present application;

[0037] Figure 17 It is a schematic diagram of a device for processing radar data according to an embodiment of the present application;

[0038] Figure 18 It is a schematic diagram of the structure of an optional electronic device according to an embodiment of the present application. Detailed implementation manners

[0039] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0040] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of this application are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0041] According to one aspect of the embodiments of the present application, a method for processing radar data is provided. Optionally, the above-mentioned method for processing radar data can be but is not limited to being applied to a hardware environment as Figure 1 shown. Optionally, the above-mentioned method for processing radar data provided by the present application can be applied to a vehicle terminal. Figure 1 A side view of the vehicle terminal 101 is shown. The vehicle terminal 101 can travel on the traveling surface 113. The vehicle terminal 101 includes a memory 102 storing an on-board navigation system 103 and a digital road map 104, a space monitoring system 117, a vehicle controller 109, a GPS (Global Positioning System) sensor 110, an HMI (Human-Machine Interface) device 111, and also includes an autonomous controller 112 and a telematics controller 114.

[0042] In one embodiment, the space monitoring system 117 includes one or more space sensors and systems for monitoring the visible area 105 in front of the vehicle terminal 101. The space monitoring system 117 also includes a space monitoring controller 118 for monitoring the visible area 105. The space sensors for monitoring the visible area 105 include a lidar sensor 106, a radar sensor 107, a camera 108, etc. The space monitoring controller 118 can be used to generate data related to the visible area 105 based on the data input from the space sensors. The space monitoring controller 118 can determine the linear range, relative speed and trajectory of the vehicle terminal 101 according to the input from the space sensors. For example, it can determine the current speed of the vehicle itself and the relative speed compared to the vehicle in front. The space sensors of the vehicle terminal space monitoring system 117 can include object positioning sensing devices, and the object positioning sensing devices can include range sensors, and the range sensors can be used to locate objects in front, such as the vehicle object in front.

[0043] The camera 108 is advantageously mounted and positioned on the vehicle terminal 101 in a position that allows the capture of images of the visible area 105, where at least a portion of the visible area 105 includes a portion of the travel surface 113 that is in front of the vehicle terminal 101 and includes the trajectory of the vehicle terminal 101. The visible area 105 may also include the surrounding environment. Other cameras may also be employed, for example, including a second camera disposed on the rear portion or side portion of the vehicle terminal 101 to monitor the rear of the vehicle terminal 101 and one of the right or left sides of the vehicle terminal 101.

[0044] The autonomous controller 112 is configured to implement autonomous driving or advanced driver assistance system (ADAS) vehicle terminal functionality. Such functionality may include an on-vehicle terminal control system capable of providing a certain level of driving automation. Driving automation may include a series of dynamic driving and vehicle terminal operations. Driving automation may include a certain level of automatic control or intervention involving individual vehicle terminal functions (e.g., steering, acceleration, and / or braking).

[0045] In the present embodiment, the transmitting antenna in the radio frequency module included in the above-mentioned radar sensor 107 can be used to transmit radar signals, and the receiving antenna is used to receive echo signals. After obtaining the echo signals of the receiving antenna, the following steps can be performed:

[0046] S102, determine the distance parameter and virtual subarray parameter for detecting a near object, where the distance parameter is used to indicate the distance interval corresponding to the near object, and the virtual subarray parameter is used to indicate the element arrangement mode of the transmitting subarray matching the near object;

[0047] S104, when the first radar data matching the target space region is obtained, determine the target distance unit number corresponding to the distance parameter, where the first radar data is obtained by performing a fast Fourier transform operation on the target echo data, and the target echo data is the echo data received by the target radar object and matching the target space region;

[0048] S106, determine the first radar data subset matching the near object from the first radar data according to the target distance unit number;

[0049] S108, perform a Doppler transmit demodulation operation on the first radar data subset according to the matrix splicing method indicated by the virtual subarray parameter to obtain the second radar data, where the second radar data is used to detect the near object in the target space region, and the near object is an object within the target distance indicated by the distance parameter in the target space region.

[0050] The HMI device 111 provides human-machine interaction for the purpose of guiding the operation of the infotainment system, GPS (Global Positioning System) sensor 110, on-board navigation system 103, and the like, and includes a controller. The HMI device 111 monitors operator requests and provides the status, services, and maintenance information of the vehicle terminal system to the operator. The HMI device 111 communicates with multiple operator interface devices and / or controls the operation of multiple operator interface devices. The HMI device 111 can also communicate with one or more devices that monitor biometric data associated with the vehicle terminal operator. For simplicity of description, the HMI device 111 is depicted as a single device, but in embodiments of the systems described herein, it can be configured as multiple controllers and associated sensing devices.

[0051] Operator controls can be included in the passenger compartment of the vehicle terminal 101 and, by way of non-limiting example, can include a steering wheel, an accelerator pedal, a brake pedal, and an operator input device, which is an element of the HMI device 111. The operator controls enable the vehicle terminal operator to interact with the operating vehicle terminal 101 and direct the operation of the vehicle terminal 101 to provide passenger transportation.

[0052] The on-board navigation system 103 uses a digital road map 104 for the purpose of providing navigation support and information to the vehicle terminal operator. The autonomous controller 112 uses the digital road map 104 for the purpose of controlling autonomous vehicle terminal operation or ADAS vehicle terminal functions.

[0053] The vehicle terminal 101 can include a telematics controller 114, and the telematics controller 114 includes a wireless telematics communication system capable of performing external communication of the vehicle terminal (including communicating with a communication network 115 having wireless and wired communication capabilities). The wireless telematics communication system includes a non-on-board server 116 capable of short-range wireless communication with a mobile terminal.

[0054] As an alternative embodiment, as Figure 2 shown, the processing method of radar data can be executed by a radar sensor, and the specific steps include:

[0055] S202, determining a distance parameter and a virtual subarray parameter for detecting a near object, where the distance parameter is used to indicate the distance interval corresponding to the near object, and the virtual subarray parameter is used to indicate the arrangement mode of the elements of the transmitting subarray matched with the near object;

[0056] S204. When the first radar data matching the target space region is obtained, determine the target distance cell number corresponding to the distance parameter, where the first radar data is obtained by performing a fast Fourier transform operation on the target echo data, and the target echo data is the echo data received by the target radar object and matching the target space region;

[0057] S206. Determine a subset of the first radar data that matches the near-range object from the first radar data according to the target distance cell number;

[0058] S208. According to the matrix splicing method indicated by the virtual subarray parameter, perform a Doppler transmit demodulation operation on the subset of the first radar data to obtain second radar data, where the second radar data is used to detect the near-range object in the target space region, and the near-range object is an object within the target distance indicated by the distance parameter in the target space region.

[0059] It should be noted that in the above step S202, the above distance parameter may be a parameter used to indicate the spatial range where the above near-range object is located. For example, when the distance parameter is 100 m, it indicates that in this embodiment, an object within 100 m from the target radar is determined as a near-range object. Correspondingly, an object outside 100 m from the target radar can be determined as a far-range object.

[0060] The virtual subarray parameter in the above step S204 can be used to indicate the array element arrangement method of the transmit subarray that matches the near-range object. For example, when the target radar object includes 4 transmit antennas, the virtual subarray parameter "0, 1, 1, 1" can be used to indicate that when detecting a near-range object, it is indicated that object detection is performed through the virtual transmit array elements composed of the second, third, and fourth antennas. In the data processing process, it is reflected as using the radar data corresponding to the second, third, and fourth antennas for near-range object detection; another example is that when the virtual subarray parameter is "1, 0, 1, 1", it indicates that when detecting a near-range object, it is indicated that object detection is performed through the virtual transmit array elements composed of the first, third, and fourth antennas. In the data processing process, it is reflected as using the radar data corresponding to the first, third, and fourth antennas for near-range object detection.

[0061] It should be noted that the above distance parameter and virtual subarray parameter may be relevant parameters determined in advance based on simulation operations of the target radar object and meeting the requirements for near-range object detection. For example, the simulation target of the above distance parameter during the simulation process may be: the pitch angle error is less than or equal to the target threshold; the simulation target of the above virtual subarray parameter during the simulation process may be: the sidelobe height of at least one Doppler sidelobe meets the first condition, and the position distribution of at least one of the Doppler sidelobes meets the second condition.

[0062] Further, the above first radar data may be obtained by performing a fast Fourier transform operation on target echo data, and the above target echo data is echo data received by a target radar object and matching the target space region.

[0063] Specifically, the above first radar data may be RDFFT data, that is, data obtained after performing range - dimension FFT (Fast Fourier Transform) and Doppler - dimension FFT processing on echo data. The data size of the above echo data is the number of sampling points * sampling bits * number of receiving channels. Range - dimension FFT is used to analyze range information, while Doppler - dimension FFT is used to analyze velocity information, and the data dimension is the number of sampling points * sampling bits * number of receiving channels.

[0064] Specifically, obtaining the first radar data matching the target space region may be, for example, through the following process: For example, the number of receiving array elements of the radar antenna parameters is 8, the number of transmitting antennas is 4, one processing period is one frame, and the number of chirps M D in one frame = 512, and the number of fast - time sampling points M R for each chirp = 512. After performing range - dimension FFT and Doppler - dimension FFT on the 8 receiving channels of the original echo data respectively, the range cell range of the RD (range, Doppler) FFT data is [0, 511], the Doppler cell range is [0, 511], and the dimension of the RD (range, Doppler) FFT data is 512×512×8, corresponding to the above first radar data; the above echo data may specifically be signal data transmitted and captured by the radar for a target object at a target range, and the size of the above target echo data is 512×512×8.

[0065] Further, after obtaining the above first radar data, the first radar data subset matching the near - range object may be further determined from the first radar data through the above steps S204 and S206.

[0066] Optionally, in the above S204, determining the target range cell number corresponding to the range parameter includes: determining the target range cell number according to the ratio between the range parameter and the range resolution of the target radar object.

[0067] Specifically, continuing with the above - mentioned embodiment as an example, determining the target range cell number corresponding to the range parameter may be, for example: setting the far - range starting range to 100 meters, that is, the range parameter is 100, indicating that in this embodiment, an object within 100 m from the radar is determined as a near - range object, and an object outside 100 m from the radar is a far - range object. Determining the system range resolution Δ r to be 0.5 m, and the velocity resolution Δ dis 0.45 meters per second. Taking a common front radar as an example, the angular range θ of interest at a long distance is set pro ∈[-20° to 20°]. The formula for calculating the corresponding distance cell number from the range resolution is:

[0068] R far_idx = R far / Δ r , and then R far_idx = 200.

[0069] Among them, R far is the distance parameter used to distinguish between near-range objects and far-range objects, and the above-mentioned Δ r is the range resolution of the target radar.

[0070] Furthermore, based on the above-mentioned target distance cell number R far_idx process the first radar data to obtain a first radar data subset, including: determining from the first radar data a first radar data subset that matches the near-range object and a second radar data subset that matches the far-range object according to the target distance cell number. Among them, the distance cell numbers of the data elements in the first radar data subset are less than or equal to the target distance cell number, and the distance cell numbers of the data elements in the second radar data subset are greater than the target distance cell number.

[0071] Specifically, in the case where the target distance cell number R far_idx = 200 determined by the above-mentioned implementation manner, the RDFFT data with a distance cell number greater than 200 among the data elements in the above-mentioned first radar data can be determined as the second radar data subset; the RDFFT data with a distance cell number less than or equal to 200 among the data elements in the above-mentioned first radar data can be determined as the first radar data subset.

[0072] It can be understood that in this implementation manner, during the process of detecting objects in a specific area (near range), the data subset associated with the near-range objects can be separated from the original RDFFT data through the above-mentioned steps S204 and S206, thereby reducing the data processing volume and improving the object detection efficiency.

[0073] Furthermore, after determining the above-mentioned first radar data subset, the first radar data subset can be further demodulated based on the virtual subarray parameters to detect the near-range objects.

[0074] In an optional implementation manner, performing a Doppler transmit demodulation operation on the first radar data subset according to the matrix splicing method indicated by the virtual subarray parameters to obtain the second radar data includes:

[0075] S1. Obtain the Doppler cell number that matches the transmit phase offset parameter of the target radar object;

[0076] S2. Perform a cyclic shift operation on the first radar data subset according to the cyclic shift parameter indicated by the Doppler cell number to obtain a first reference data subset;

[0077] S3. Determine the target matrix splicing method according to the element number and element position of the transmit array element indicated by the virtual subarray parameter;

[0078] S4. Splice the multiple data matrices included in the first reference data subset according to the target matrix splicing method to obtain second radar data, where the virtual subarray parameter is determined for the simulation operation performed on the target radar object.

[0079] It can be understood that in this embodiment, during the demodulation of the first radar data subset, it is necessary to first obtain the Doppler cell number that matches the transmit phase offset parameter of the target radar object, and perform a cyclic shift operation on the first radar data subset based on the Doppler cell number to obtain a first reference data subset.

[0080] Optionally, the obtaining of the Doppler cell number that matches the transmit phase offset parameter of the target radar object includes: determining the Doppler cell number according to the product of the transmit phase offset parameter and the first signal quantity parameter, where the first signal quantity parameter is used to indicate the number of modulation signals included in one frame of radar signal transmitted by the target radar object.

[0081] The following continues to illustrate the method for obtaining the Doppler cell number by taking the target radar object in the above embodiment as an example:

[0082] In the case where the transmit phase offsets Δ of the second to fourth channels relative to the first channel in the 4 transmit antennas of the DDMA waveform are 84.375°, 140.625°, and 267.1875° respectively. Calculate the transmit phase offset Δ according to the following formula θ Calculate the corresponding Doppler cell number: θ

[0083]

[0084] where, Δ θ is the transmit phase offset of the nth channel relative to the first channel in the DDMA waveform transmit antenna. One processing period is one frame, and the number of chirps in one frame is M D , which is the above-mentioned first signal quantity parameter. Furthermore, the Δ of the second to fourth channels relative to the first channel in the transmit antenna can be obtained θ_idx are 120, 200, and 380 respectively. ​

[0085] Further, in steps S3 - S4, according to the cyclic translation parameters indicated by the Doppler unit numbers, a cyclic translation operation is performed on the first radar data subset to obtain a first reference data subset; based on the element numbers and element positions of the transmitting elements indicated by the virtual sub - array parameters, the target matrix splicing method is determined; and then based on...

[0086] Specifically, for the near - range processing, the transmitting sub - arrays used select the 2nd to 4th transmitting elements, that is, Nt' = 3. Thus, the size of the formed virtual data sub - array is 8 * 3 (i.e., the number of receiving elements * the number of transmitting elements) = 24; the RDFFT data corresponding to the second transmitting antenna in the original transmitting array is cyclically translated 120 units along the Doppler dimension. That is, the data with Doppler dimension unit numbers [0:511] in the original RDFFT data becomes [120:511, 0:119]. The data corresponding to the third and fourth transmitting antennas are cyclically translated 200 and 380 units respectively and then sequentially spliced with the receiving antenna N_r dimension, forming a demodulated data matrix with dimensions of 200×512×24, which corresponds to the above - mentioned second radar data.

[0087] Through the above - mentioned implementation manner of the present application, the Doppler unit numbers matching the transmitting phase offset parameters of the target radar object are obtained; according to the cyclic translation parameters indicated by the Doppler unit numbers, a cyclic translation operation is performed on the first radar data subset to obtain a first reference data subset; according to the element numbers and element positions of the transmitting elements indicated by the virtual sub - array parameters, the target matrix splicing method is determined; according to the target matrix splicing method, multiple data matrices included in the first reference data subset are spliced to obtain the second radar data, and the data in the near - range is specifically optimized.

[0088] In the above - mentioned implementation manner, on the one hand, the first radar data subset matching the near - range target is determined from the first radar data through the distance parameter, and then the computing resources are concentrated to process the signals within a specific distance and Doppler range, avoiding redundant operations on the signals in the entire space, and reducing the computational complexity and data processing time.

[0089] On the other hand, in the above - mentioned implementation manner, the virtual sub - array parameters can be determined by pre - simulation results, and the optimization goal during the simulation process can be the virtual sub - array parameters whose selected Doppler sidelobe heights and distributions meet specific conditions. Then, during the demodulation process based on the above - mentioned virtual sub - array parameters, for the first radar data subset (near - range target), by reducing the number of transmitting antennas participating in the demodulation, the formation of Doppler sidelobes is reduced, the amount of calculation is reduced, thereby accelerating the data processing speed and improving the processing efficiency.

[0090] Further, after splicing a plurality of data matrices included in the first reference data subset according to the target matrix splicing method to obtain the second radar data, the following steps are further included:

[0091] S1, obtaining the number of points in the azimuth dimension that matches the virtual subarray parameters;

[0092] S2, performing a fast Fourier transform operation on the second radar data in the azimuth dimension according to the number of points in the azimuth dimension and the arrangement method corresponding to the virtual array channels of the virtual subarray parameters to obtain the target radar data;

[0093] S3, performing an object detection operation according to the target radar data.

[0094] It should be noted that in this embodiment, after obtaining the second radar data, it is also necessary to further perform a fast Fourier transform operation on the second radar data in the azimuth dimension to obtain the target radar data for performing object detection.

[0095] In this embodiment, there can be a certain matching relationship between the number of FFT points in the azimuth dimension (i.e., the above-mentioned number of points in the azimuth dimension) and the radar array elements. It should be noted that since the number of FFT points in the azimuth dimension directly affects the angle resolution of the radar system, and at the same time, the selection of the number of FFT points in the azimuth dimension is also restricted by the radar hardware, including processing power and storage capacity. Too many FFT points may lead to excessive computational complexity and affect the real-time performance of the system. Based on this, although the efficiency of the FFT algorithm is usually the highest when the number of points is a power of 2. Therefore, although theoretically the number of FFT points can be perfectly matched with the number of array elements, in actual design, usually a power of 2 close to the number of array elements is selected as the number of FFT points to balance the angle resolution and computational efficiency.

[0096] In addition, since when performing FFT in the azimuth dimension, the signals received by the radar array elements will be combined to form a composite signal, and then an FFT transform is performed on this composite signal. The selection of the number of FFT points in the azimuth dimension will affect the signal processing effect, including the sidelobe level and the shape of beamforming. In this embodiment, the above-mentioned number of points in the azimuth dimension that matches the virtual subarray parameters can also be obtained by pre-simulating and calculating the target radar based on the height and distribution state of the sidelobe level as the optimization target.

[0097] In a specific embodiment, the second radar data can be arranged according to virtual array channels, and a fast Fourier transform operation is performed on the arranged second radar data in the azimuth dimension according to the number of points in the azimuth dimension to obtain target radar data. For example, in the above embodiment, when the dimension of the demodulated data matrix is 200×512×24, the demodulated data of the near-range transmission is further arranged according to the virtual array channels, and the number of FFT points in the azimuth dimension M_A = 48, and the size of the RDA three-dimensional data matrix Ω formed is 200×512×48. And Ω' = Ω, that is, subsequent object detection operations are directly performed according to the target radar data.

[0098] In an alternative manner, the above-mentioned performing object detection operations according to the target radar data may include estimating parameter values such as the point trace distance, speed, and angle of the near-range object.

[0099] Specifically, through the above-mentioned target radar data, target point trace distance, speed, and angle unit information R t , D t , A t can be obtained.

[0100] Further, the target distance, speed, and angle estimation values can be calculated by the following formulas:

[0101] Target estimated distance = R t × Δ r ; Target estimated speed = D t × Δ d ;

[0102] Thus, the output of the target point trace information is completed.

[0103] Among them, indicates the modulo result between obtaining the angle unit information A t and , M A is the number of FFT points in the azimuth dimension corresponding to the near-range object = 48.

[0104] Through the above embodiments of the present application, according to the number of points in the azimuth dimension and the virtual subarray parameters determined by pre-simulation, a fast Fourier transform is performed on the second radar data in the azimuth dimension, and then a virtual subarray formed by using some transmitting array elements is used for near-range target detection, reducing the Doppler dimension transmission demodulation operation amount, reducing the Doppler dimension sidelobe formed after demodulation, and thus also reducing the false alarm probability of near-range target detection.

[0105] The following Figure 3 describes the complete process of a method for processing radar data of a near-range object.

[0106] S302, perform range and Doppler dimension FFT on the original echo data to obtain RDFFT data; specifically, it can be to perform range dimension FFT on the fast time sampling points of the original echo data first, and then perform Doppler FFT in the chirp dimension to obtain range Doppler FFT (RDFFT) data.

[0107] S304, perform range judgment on the RDFFT data; S304-1, complete transmit Doppler dimension demodulation according to the near-range virtual subarray;

[0108] Specifically, the following formula can be used to calculate the transmit phase offset Δ θ Calculate the corresponding Doppler cell number:

[0109] Calculate R according to the range accuracy far The corresponding range dimension cell number R far__idx The formula for R is as follows: R far_idx = R far / Δ r .

[0110] From R far_idx Judge the range of the RDFFT data participating in the processing, and perform Doppler dimension demodulation of different transmit subarrays on the RDFFT data in different range ranges according to Δ θ_idx to obtain demodulated data. In this embodiment, the RDFFT data in the far-range is demodulated.

[0111] S306, after completing the angle dimension FFT, obtain the RDA3-dimensional data matrix Ω;

[0112] Specifically, after performing range dimension FFT and Doppler dimension FFT on the 8 receiving channels of the original echo data respectively, the range cell range of the RDFFT data is [0, 511], and the Doppler cell range is [0, 511], that is, the RDFFT data dimension is 512×512×8.

[0113] Further calculate the Δ of the second to fourth channels relative to the first channel in the transmit antenna according to the formula in S304 θ_idx which are 120, 200, and 380 respectively.

[0114] Calculate R according to the formula in S304 far_idx = 200.

[0115] For the RDFFT data with the range cell number less than or equal to 200, use the second, third, and fourth transmit antennas to participate in the demodulation. That is, the RDFFT data is cyclically shifted [0, 120, 200, 380] in sequence in the Doppler dimension and then spliced to form demodulated data, and its dimension is 312×512×24.

[0116] S308, perform distance judgment on the RDA 3D data matrix Ω; S308-1, perform target detection on the near-distance data matrix Ω'; S310, target detection and track output;

[0117] The data after near-distance transmission demodulation is arranged according to the virtual array channels, and the number of azimuth FFT points M A = 48, thus forming the RDA 3D data matrix Ω with a size of 312×512×48.

[0118] During the near-distance object detection process, the matrix to be detected Ω' = the RDA 3D data matrix Ω, so CA-CFAR can be performed to obtain target track information. Specifically, when obtaining the target track distance, speed, and angle unit information R t 、D t 、A t In the case of, the target distance, speed, and angle estimated values can be calculated by the following formula:

[0119] Target estimated distance = R t ×Δ r ; Target estimated speed = D t ×Δ d ;

[0120] Thus, the output of target track information is completed.

[0121] Through the above implementation manner of the present application, first, according to the distance parameter and the target distance unit serial number matching the distance parameter, the data subset corresponding to the near-distance space (the near-distance object is located in the near-distance space) is separated from the first radar data, that is, the first radar data subset, thereby reducing the data processing amount in the process of near-distance object recognition; further, in the process of performing Doppler transmission demodulation operation on the first radar data subset, based on the matrix splicing method corresponding to the virtual subarray, the Doppler transmission demodulation operation is performed on the first radar data subset, and then the Doppler dimension sidelobe can be suppressed through the virtual subarray determined by pre-simulation, thereby improving the measurement accuracy of the near-distance object and solving the technical problem of poor processing accuracy of radar data in the prior art.

[0122] It can be understood that after obtaining the first radar data, object detection of the far-distance object can also be realized according to the second radar data subset corresponding to the far-distance object. The following describes a method for detecting a far-distance object:

[0123] In an optional implementation manner, after determining the second radar data subset matching the near-distance object from the first radar data according to the target distance unit serial number, it further includes:

[0124] S1. Determine the target angle unit serial number range for detecting a far - distance object;

[0125] S2. Perform Doppler transmit demodulation operation on the second radar data subset according to the target distance unit serial number to obtain the third radar data;

[0126] S3. Perform a fast Fourier transform operation on the third radar data in the azimuth dimension according to the number of points in the azimuth dimension matching the far - distance object and the arrangement method corresponding to the virtual array channels of the far - distance virtual sub - array parameters to obtain the far - distance three - dimensional radar data;

[0127] S4. Determine a far - distance three - dimensional data subset from the far - distance three - dimensional radar data according to the target angle unit serial number range, where the angle unit serial numbers of the data elements included in the far - distance three - dimensional data subset are within the target angle unit serial number range;

[0128] S5. Determine the far - distance three - dimensional data subset as the reference radar data for object detection of the far - distance object, where the far - distance object is an object outside the target distance indicated by the distance parameter in the target space region.

[0129] In the above step S1, the target angle unit serial number range for detecting a far - distance object can be determined first, where the target angle unit serial number range can be determined according to the angle range parameter. It should be noted that the above angle range parameter can be the angle range of the region of interest. For example, the region of interest of the forward radar usually includes a large angle range in front of the vehicle, such as - 20 degrees to 20 degrees in a 180 - degree field of view. The side - mounted radars are installed on both sides of the vehicle and are mainly used for functions such as blind spot detection (BSD) and lane change assist (LCA). The region of interest of the side - mounted radars may be concentrated within a certain angle range on the side of the vehicle, such as 0 degrees to 30 degrees or - 30 degrees to 0 degrees in a 90 - degree field of view on each side. This is only an example here.

[0130] Optionally, in the above steps S2 and S3, performing a Doppler transmit demodulation operation on the second radar data subset matching the far - distance object according to the target distance unit serial number to obtain the third radar data can be achieved in the following way:

[0131] Specifically, when the transmit phase offsets Δ of the second to fourth channels relative to the first channel among the 4 transmit antennas of the DDMA waveform are 84.375°, 140.625°, and 267.1875° respectively, calculate the transmit phase offset Δ using the following formula θ Calculate the corresponding Doppler unit serial number: θ Calculate the corresponding Doppler unit serial number:

[0132]

[0133] Therefore, the relative Δ between the second to fourth channels and the first channel in the transmitting antenna can be obtained. θ_idx They are 120, 200, and 380 respectively. In this embodiment, for the RDFFT data with the distance unit number greater than or equal to 200, all transmitting antennas are used for demodulation. That is, the RDFFT data is cyclically shifted by [0, 120, 200, 380] in sequence in the Doppler dimension and then spliced to form demodulated data, whose dimension is 312×512×32, which corresponds to the above-mentioned third radar data.

[0134] Next, the data after far-distance transmitting demodulation is arranged according to the virtual array channels, and the number of FFT points M A in the azimuth dimension is 64, so that the size of the RDA three-dimensional data matrix Ω is 312×512×64.

[0135] Optionally, the target angle unit number interval in the above step S4 can be obtained in the following way: According to the set range of the region of interest angle for the far-distance target, through the formula calculate the target angle unit number interval θ pro_idx ∈[0:11, 53:63].

[0136] Furthermore, based on the above target angle unit number interval, a far-distance three-dimensional data subset is selected from the far-distance three-dimensional radar data. Specifically, the target radar data is determined according to the target angle unit number interval and the third radar data obtained by demodulating the received signal. The size of the RDA three-dimensional data Ω' for far-distance target detection is 312×512×23. The above target radar data is the detection point data obtained by performing CA-CFAR on the matrix Ω' to be detected. The above target object is a far-distance object, that is, the distance is greater than 100 m relative to the radar.

[0137] Through the above embodiments of the present application, first, the distance parameter and the angle interval parameter for detecting a far-distance object are determined, that is, the far-distance starting point and the angle range of the region of interest are determined; furthermore, according to the angle range representing the region of interest, by selecting the angle range of the region of interest, only the angle units associated with the target object are processed, avoiding redundant operations on the full-field angle data, significantly improving the processing efficiency, and solving the technical problems of low processing efficiency and poor processing accuracy of radar data in the prior art during the detection of far-distance objects.

[0138] The following describes the simulation operation process related to the above target radar object. It can be understood that the above simulation operation can be used to determine, including but not limited to, the above distance parameter and virtual subarray parameter.

[0139] In an optional embodiment, before the above determining the distance parameter and the virtual subarray parameter for detecting a near-distance object, it further includes:

[0140] S1. When the number of transmitting array elements and receiving array elements of a target radar object is determined, obtain a plurality of candidate code pattern combinations, where a candidate code pattern combination is used to indicate the number of array elements and the array element serial numbers of at least one object array element extracted from a plurality of transmitting array elements;

[0141] S2. Obtain first simulation results respectively corresponding to the plurality of candidate code pattern combinations, where the first simulation results include at least one of the following: the sidelobe height of at least one Doppler sidelobe, the position of at least one Doppler sidelobe;

[0142] S3. Determine at least one first code pattern combination from the plurality of candidate code pattern combinations according to the first simulation results respectively corresponding to the plurality of candidate code pattern combinations, where virtual sub-array parameters are used to indicate the first code pattern combination.

[0143] In the above step S1, when the number of transmitting array elements and receiving array elements of a target radar object is determined, obtain a plurality of candidate code pattern combinations, where a candidate code pattern combination is used to indicate the number of array elements and the array element serial numbers of at least one object array element extracted from a plurality of transmitting array elements. The number of the above-mentioned transmitting array elements and receiving array elements can be the number of antennas determined in advance according to requirements. The above-mentioned candidate code pattern combinations provide a variety of different waveform design options, and these waveforms can be pulse sequences of different lengths and different structures. By selecting different code pattern combinations, the time, frequency, and phase parameters of radar signals can be adjusted to adapt to different detection environments and target characteristics. Different array element combinations can provide different angular resolutions and range resolutions, thereby improving the accuracy of target recognition and tracking.

[0144] Further, in the above steps S2 - S3, obtain first simulation results respectively corresponding to the plurality of candidate code pattern combinations, where the first simulation results include at least one of the following: the sidelobe height of at least one Doppler sidelobe, the position of at least one Doppler sidelobe; determine at least one first code pattern combination from the plurality of candidate code pattern combinations according to the first simulation results respectively corresponding to the plurality of candidate code pattern combinations.

[0145] In an optional implementation manner, the above determining at least one first code pattern combination from the plurality of candidate code pattern combinations according to the first simulation results respectively corresponding to the plurality of candidate code pattern combinations includes at least one of the following:

[0146] When the sidelobe height of at least one Doppler sidelobe corresponding to the current candidate code pattern combination among the plurality of candidate code pattern combinations is less than or equal to a first threshold, determine the current candidate code pattern combination as the first code pattern combination;

[0147] When the distribution state of at least one Doppler sidelobe corresponding to the current candidate code pattern combination among the multiple candidate code pattern combinations is less than or equal to the second threshold, the current candidate code pattern combination is determined as the first code pattern combination.

[0148] In method 1, for example, a radar system has 4 transmitting array elements and 4 receiving array elements. Design multiple candidate code combinations, and measure the Doppler sidelobe height corresponding to each combination. Set a threshold, such as -20dB as the first threshold for the sidelobe height. Assuming that among the candidate code combinations A, B, C, and D, only combination C has all sidelobe heights that do not exceed -20dB, then combination C will be determined as the first code combination. It can be understood that the sidelobe height of the Doppler sidelobe directly affects the interference level of the radar signal. A lower sidelobe height can reduce clutter and interference and improve the signal-to-noise ratio of the signal.

[0149] In the second method, for example, a threshold is set such as the sidelobe width does not exceed 10 FFT bins; if all sidelobe distribution states of a candidate code pattern combination meet the condition (the sidelobe width does not exceed 10 FFT bins), the candidate code pattern combination is determined as the first code pattern combination. It can be understood that the distribution state of the Doppler sidelobe affects the angular resolution of the radar. Optimizing the sidelobe distribution can improve the radar's ability to resolve the target angle, thereby more accurately locating the target.

[0150] In addition, in this embodiment, the preferred first code pattern combination can also be determined by combining the above-mentioned embodiment 1 and embodiment 2. For example, when the weight coefficients of the linear and planar array antenna directional layout optimization design are respectively 0.45 and 0.9, not only the sidelobe level and cross-polarization gain are reduced, but also the gain drop in the main radiation direction can be ensured not to be too great. This method effectively improves the sidelobe height and distribution state of the Doppler sidelobe by optimizing the array layout, thereby improving the performance of the radar system.

[0151] In an optional implementation, the process of selecting the number of FFT points in the azimuth dimension may be: Figure 7 The design of 4-transmit and 4-receive array is shown, and the specific antenna position is shown in the coordinate system in the figure. The MIMO POS has 4*4=16 channels. The positions of the transmitting and receiving channels are shown in the figure. The number of FFT points in the azimuth dimension can be the width of the mimo pos, which is the point with the largest horizontal coordinate minus the point with the smallest horizontal coordinate. This width is a concept of aperture, which determines the angle measurement accuracy and angle resolution of the radar. The larger the aperture, the better these two are. It should be noted that the number of fft points must be larger than the aperture, otherwise it is equivalent to the number of fft points being smaller than the number of sampling points, resulting in the fft angle measurement not being able to play the role of this large aperture. It can be set to 2 to the power of n or 3*(2 to the power of n) while meeting the above conditions.

[0152] The following will describe a specific design method of virtual sub - arrays in combination with Figure 4 and Figure 5 A specific design method of virtual sub - arrays will be described.

[0153] As Figure 4 shown, Figure 4 The figure shows the Doppler sidelobe distribution of an antenna design method. The horizontal axis is dopIdx (Doppler index), and the vertical axis is peaKVal (peak value). For example, the result of simulating the Doppler sidelobe distribution by extracting one channel is as Figure 5 shown. A distribution that meets the conditions can be selected. For example, it is determined that the overall Doppler spectrum is more stable as the distribution that meets the conditions, that is, it is determined that Figure 5 the Doppler sidelobe distribution corresponding to the third channel extracted from the first one in the second row in the figure has the best effect, which is the selected antenna design method in the case of short distance.

[0154] The following will describe the method for determining the parameters of virtual sub - arrays involved before the process of short - distance object detection in combination with Figure 6 A method for determining the parameters of virtual sub - arrays involved before the short - distance object detection process will be described.

[0155] The above process will be fully described with a flowchart Figure 6 First, in S602, a code pattern combination that meets the system requirements is designed, including requirements such as the maximum detection range, angular resolution, Doppler resolution, and false alarm rate.

[0156] In S604, each group of code patterns is traversed, including:

[0157] Execute S604 - 1 to calculate the combination of extracting N from M codewords. Specifically, each group of code patterns that meets the system requirements is traversed, and the combination of extracting N codewords from each code pattern is calculated. Here, N is the number of channels staggered in the elevation layer of the transmitting antenna, which affects the phase shift and sidelobe distribution of the transmitting antenna. For example, if the number of transmitting antennas is M (assuming M = 4, N = 3), then all possible combinations of extracting 3 codewords from the complete code pattern need to be calculated, and each combination represents a possible transmission mode;

[0158] In S604 - 2, the Doppler sidelobe position and size are calculated. Specifically, according to the demodulation rule, the Doppler sidelobe position and size of each extracted combination are calculated. Among them, the demodulation rule is to use the transmitting channel 1 as the transmitting channels 1 - M respectively, perform phase shift, and obtain the Doppler sidelobe;

[0159] Specifically, the sidelobe position can be mapped to the Doppler domain by calculating the phase difference after phase shift, and the sidelobe size reflects the energy distribution after demodulation.

[0160] S604-3, the maximum value of all sidelobes <= threshold 1, and the position difference of all sidelobes <= threshold 2; specifically, determine whether the maximum value of the Doppler sidelobe position difference and the sidelobe height meet the thresholds. Generally, it is desired that the Doppler sidelobes are low enough and the sidelobe positions are relatively concentrated to reduce interference with target detection. Evaluate the relative height of the Doppler sidelobes. Compared with the main lobe energy, the lower the sidelobe energy, the smaller its negative impact on target detection performance.

[0161] As an alternative implementation, assume a Barker code sequence with a length of 7 and the codewords: +1, +1, +1, -1, +1, -1, -1. Combinations of N codewords need to be extracted from it. For example, when N = 3, the following combinations can be obtained: Combination 1: +1, +1, +1; Combination 2: +1, +1, -1; Combination 3: +1, -1, +1... Calculate each extracted combination according to the demodulation rule. For example, demodulation is achieved by calculating the dot product of the received signal and the local codeword. If the received signal is +1, -1, +1, for example, the process of calculating its dot product with the above Combination 1 is (+1)×(+1)+(-1)×(+1)+(+1)×(+1) = +1 - 1 + 1 = +1.

[0162] Further calculate the position and size of the Doppler sidelobes, including but not limited to determining the position and size of the sidelobes by calculating the autocorrelation function of the codewords, and no specific limitation is made here.

[0163] Set the maximum value of the sidelobe position difference and the threshold value of the sidelobe energy to evaluate whether the performance of each code pattern combination meets the requirements. For example, a threshold can be set, requiring that the position difference of the farthest sidelobe does not exceed 100 units, and the relative height of all sidelobes does not exceed -20 dB of the main lobe height.

[0164] Execute S604-4 when meeting the requirements, record the current code pattern and the extraction position; otherwise, do not record; finally, obtain S606, the final code pattern.

[0165] The following describes the radar array design method involved before detecting a far - distance object. In an alternative implementation, before determining the distance parameter and virtual sub - array parameter for detecting a near - distance object, it further includes:

[0166] S1, obtain at least one reference radar array information;

[0167] S2, according to at least one reference radar array information, distance parameter, and angle interval parameter, obtain the target simulation results corresponding to at least one reference radar array information respectively, where the target simulation results include the main - to - sidelobe ratio parameter;

[0168] S3. Determine the target radar array information from at least one reference radar array information according to the target simulation result, where the target radar array information is used to indicate the array parameters of the target radar object.

[0169] In the above step S1, obtaining at least one reference radar array information can be determined according to design requirements, such as detection range, angle coverage, performance indicators (angle resolution, angle measurement accuracy, etc.) and the type of detected target, etc. The above radar array information includes but is not limited to information such as the number of receiving antennas, the number of transmitting antennas, antenna array pattern, DDMA waveform parameters, processing period, etc.

[0170] In the above step S2, according to at least one reference radar array information, distance parameter and angle interval parameter, obtain the target simulation results corresponding to at least one reference radar array information respectively.

[0171] In Figure 7 the shown radar antenna layout of 4 transmitters and 4 receivers, determine that the minimum number of channels used is 14, perform simulations on any combination to obtain the angle - dimension spectrum as Figure 8 shown, calculate the main - to - sidelobe ratio within the selected FOV, the schematic diagram is as Figure 9 shown, and further select the optimal sub - array as Figure 10 the sub - array corresponding to the thick - line mark in , that is, the one with the highest main - to - sidelobe ratio.

[0172] Further in the above step S3, according to the target simulation result, determine the target radar array information from at least one reference radar array information.

[0173] As an alternative implementation, for example, there are array combinations A, B, and C. Among them, array combination A contains sub - arrays a1, a2, and a3. Sub - array a1 uses a specific antenna layout. When detecting distant targets, the radiation energy in the main lobe direction is relatively strong, but there is also a certain energy distribution in the sidelobes; the antenna layouts of sub - arrays a2 and a3 are different and have their own radiation characteristics; array combination B consists of sub - arrays b1, b2, and b3. Sub - array b1 adopts another antenna arrangement method, and the energy concentration in the main lobe in the direction of distant targets is relatively high, and the sidelobe energy is relatively low; the designs of sub - arrays b2 and b3 are also aimed at optimizing the signal reception of distant targets, but are different from the characteristics of sub - array b1; array combination C contains sub - arrays c1, c2, and c3. The antenna layout of sub - array c1 focuses on improving the signal gain within a specific angle range, and its main - to - sidelobe ratio shows certain characteristics; sub - arrays c2 and c3 work together in the whole array combination to meet the requirements of distant target detection.

[0174] For sub-array a1 in the array configuration combination A, its main lobe radiation energy EA and sidelobe radiation energy Ea1 are obtained through simulation or theoretical calculation. Then the main-to-sidelobe ratio Ra1 = EA / Ea1. Calculate the main-to-sidelobe ratio of each sub-array in the same way.

[0175] For example, in array configuration combination A, Ra2 is the maximum value among them; in array configuration combination B, Rb1 is the maximum value among them; in array configuration combination C, Rc3 is the maximum value among them. Further compare Ra2, Rb1, and Rc3. If Rb2 is the largest, then array configuration combination B is selected as the optimal main array, and its signal reception and processing capabilities are the best. It should also be noted that when calculating the main-to-sidelobe ratio, various factors need to be considered, such as the performance of the antenna, the height distribution of the target, the requirements of the far-distance FOV, the signal-to-noise ratio, etc.

[0176] The following is a detailed description in combination with the flowchart Figure 11 Specifically explain the above simulation process:

[0177] S1102, perform array design that meets the system requirements;

[0178] Traverse each group of arrays and execute S1104 to evaluate the distance segmentation; S1106 to evaluate the far-distance FOV; S1108 to evaluate the optimal sub-array.

[0179] Specifically, in S1104, the evaluation of the distance segmentation includes: S1104-1, confirm the target distribution height; S1104-2, calculate the elevation angle distribution of the target at different distances; S1104-3, simulate the influence of the elevation angle on the azimuth angle measurement at different distances; S1104-4, screen the distances where the azimuth angle measurement error and the change of the main-to-sidelobe ratio are within a reasonable range; that is, evaluate this item according to the target height distribution range and the influence of the elevation channel on the azimuth angle measurement.

[0180] S1106, the evaluation of the far-distance FOV includes: S1106-1, confirm the functional area according to the radar type; S1106-2, confirm the far-distance FOV in combination with the distance segmentation value; that is, calculate the FOV according to the radar functional area and the far-distance distance segment.

[0181] S1108. Evaluating the optimal subarray includes: S1108-1, traversing all array arrangements that meet the system requirements; S1108-2, setting the minimum number of virtual channels used; S1108-3, screening subarrays for each array arrangement according to the minimum number of channels used; S1108-4, the subarray meets the high main-to-sidelobe ratio requirement in the far main FOV; if the requirement is met, execute S1108-5, record the number of channels used and the main-to-sidelobe ratio of the current subarray; S1108-6, obtain the jointly optimal subarray of the number of channels and the main-to-sidelobe ratio; S1108-7, record the current array arrangement and the optimal subarray; that is, consider the signal-to-noise ratio to set the minimum number of MIMO channels used, and screen the subarrays that meet the requirements according to the high main-to-sidelobe ratio requirement of the far main FOV subarray.

[0182] S1110. Traverse all combinations of array arrangements + subarrays, and screen the combination with the highest main-to-sidelobe ratio of the subarray.

[0183] S1112. Final array arrangement.

[0184] In an alternative embodiment, before the above-mentioned determination of the distance parameter and the virtual subarray parameter for detecting a near-distance object, it further includes:

[0185] S1. Obtain the height estimation parameter of the near-distance object.

[0186] S2. Determine the pitch angle corresponding to each of the multiple candidate object distances according to the height estimation parameter and the multiple candidate object distances.

[0187] S3. When at least one reference radar array arrangement information is obtained, obtain at least one reference simulation result according to the reference radar array arrangement information and the multiple pitch angles, where the reference simulation result includes at least one of the following: angle measurement error value, main-to-sidelobe ratio change rate.

[0188] S4. Determine the distance parameter according to at least one reference simulation result that meets the first constraint condition.

[0189] In the above steps S1 - S2, obtain the height estimation parameter of the target object; determine the pitch angle corresponding to each of the multiple candidate object distances according to the height estimation parameter and the multiple candidate object distances.

[0190] Optionally, as Figure 12 shown, it is a schematic diagram of the pitch angles of target objects with heights of -1m and 15m at different distances. It can be seen that there are inflection points where the pitch angles gradually tend to be flat (0°) near different distance critical points respectively. That is, it can be determined that for target objects with different heights, there are corresponding distance critical points respectively, that is, the far-distance start values corresponding to target objects with different heights can be determined respectively.

[0191] In the above step S3, when at least one reference radar array information is obtained, at least one reference simulation result is obtained according to the reference radar array information and multiple elevation angles; as in Figure 13 , Figure 14 in which the angle measurement error influence analysis and the main side lobe ratio influence analysis are carried out for a target at a height of 15m, Figure 13 in the coordinate system, the horizontal axis X represents the distance, the vertical axis z represents the azimuth angle measurement state, and the parameter y represents the azimuth angle degree, Figure 14 in the coordinate system, the horizontal axis X represents the distance, the vertical axis z represents the main side lobe ratio, and the parameter y represents the azimuth angle degree. From Figure 13 it can be seen that after a distance of 270m, the error influence tends to be stable, and 270m can be used as the distance judgment critical value; from Figure 14 it can be seen that after a distance of 90m, the error influence tends to be stable, and 90m can be used as the distance judgment critical value.

[0192] In the above step S4, according to at least one reference simulation result that meets the first constraint condition, the distance parameter is determined. The first constraint condition can be to determine the weight value matching the angle measurement error value and the main side lobe ratio change rate according to different design requirements, that is, the distance parameter value can be jointly determined according to the above influencing factors. For example, comprehensively judging the two conditions to determine that 270m is the distance critical value, and within 270m is the near-distance range. Or it can be determined that the main side lobe ratio influence is the main factor, and 90m is determined as the critical value.

[0193] By obtaining the height estimation parameter of the target object; determining the elevation angle corresponding to each of the multiple candidate object distances according to the height estimation parameter and the multiple candidate object distances; when at least one reference radar array information is obtained, obtaining at least one reference simulation result according to the reference radar array information and the multiple elevation angles; determining the distance parameter according to at least one reference simulation result that meets the first constraint condition; by accurately and reasonably determining the starting distance of the far-distance object, the accuracy of radar data processing for far-distance objects is improved.

[0194] The following uses the process Figure 15 to illustrate the overall solution:

[0195] S1502, complete the antenna and DDMA waveform design according to the radar system performance requirements;

[0196] S1504, determine the starting position of the far distance, the size of the near-distance virtual subarray and the far-distance angle range;

[0197] S1506, perform signal processing on the original echo data to complete target detection.

[0198] Furthermore, in the case of needing to detect far-distance objects and near-distance objects simultaneously, a complete implementation method is asFigure 16 As shown:

[0199] Before performing range and Doppler FFT, the radar antenna and waveform design can be completed according to the performance requirements of the radar system, and the transmitting channels respectively transmit DDMA waveforms with different phase changes. It includes the number of receiving elements Nr of the MIMO antenna and the number of transmitting antennas Nt. The phase offset Δ corresponding to the transmitting antenna in the DDMA system θ . The number of chirps M within the processing period D and the number of fast-time sampling points M for each chirp R . Determine the system range resolution Δ r , and the velocity resolution Δ d .

[0200] For example: Design the radar antenna parameters, the number of receiving elements = 8, the number of transmitting antennas = 4, and the formed virtual array dimension = 8 * 4 = 32. The transmitting phase offsets Δ of the second to fourth channels relative to the first channel among the 4 transmitting antennas of the DDMA waveform θ are 84.375°, 140.625°, and 267.1875° respectively. One processing period is one frame, the number of chirps in one frame = 512, and the number of fast-time sampling points for each chirp = 512. The system range resolution is 0.5 meters, and the velocity resolution is 0.45 meters per second.

[0201] Next, through the simulation processing method in the above embodiments, determine the far-range starting position R of the signal processing far . Evaluate and calculate the size Nt' of the near-range transmitting subarray that meets the system requirements, and select the angle range θ of interest for far-range target detection processing in combination with the functional requirements pro , and form a spatial subdomain.

[0202] For example: Set the far-range starting distance to 100 meters, and select the 2nd to 4th transmitting elements for the near-range processing transmitting subarray, that is, Nt' = 3. Thus, the formed virtual subarray size is 8 * 3 = 24; taking a common front radar as an example, set the angle range θ of interest for far range pro ∈[-20° to 20°].[[]END]]

[0203] S1602, perform range and Doppler dimension FFT on the original echo data to obtain RDFFT data;

[0204] In the above steps, the radar echo data is down-converted, and the original echo data is obtained after completing digital-to-analog conversion. The original echo data enters the signal processing link for target detection processing.

[0205] Specifically, after performing FFT in the range dimension on the fast-time sampling points of the original echo data, Doppler FFT in the chirp dimension is then performed to obtain range-Doppler FFT (RDFFT) data.

[0206] In addition, the transmission phase offset Δ can be calculated using the following formula θ Calculate the corresponding Doppler cell number:

[0207]

[0208] Calculate R according to the range accuracy far The corresponding range dimension cell number R far__idx The formula is as follows:

[0209] R far_idx = R far / Δ r .

[0210] Based on R far_idx judge the range of the RDFFT data participating in the processing, and perform Doppler dimension demodulation of different transmit subarrays on the RDFFT data of different ranges according to Δ θ_idx to obtain demodulated data.

[0211] Next, execute S1604 to perform range judgment on the RDFFT data;

[0212] In the case of short range, execute S1604-1 to complete transmit Doppler dimension demodulation according to the short-range virtual subarray;

[0213] In the case of long range, execute S1604-2 to complete transmit Doppler dimension demodulation according to the long-range virtual subarray;

[0214] Specifically, assume that the size of the received original echo data is 512×512×8; the specific steps for target detection processing of this data are as follows:

[0215] After performing range dimension FFT and Doppler dimension FFT on the 8 receiving channels of the original echo data respectively, the range cell range of the RDFFT data is [0, 511], and the Doppler cell range is [0, 511], that is, the RDFFT data dimension is 512×512×8.

[0216] Calculate the transmission phase offset Δ according to the following formula θ Calculate the corresponding Doppler cell number:

[0217]

[0218] Therefore, the Δ of the second to fourth channels relative to the first channel in the transmit antenna can be obtained θ_idx are 120, 200, and 380 respectively.

[0219] The formula for calculating the corresponding range cell number from the range resolution is as follows:

[0220] R far_idx = R far / Δ r , and then R far_idx = 200.

[0221] For the data with a range cell number less than 200, the Doppler transmit demodulation operation is as follows:

[0222] The RDFFT data corresponding to the second transmit antenna in the original transmit array is circularly shifted by 120 cells along the Doppler dimension. That is, the data with Doppler dimension cell numbers [0:511] in the original RDFFT data becomes [120:511, 0:119]. The data corresponding to the third and fourth transmit antennas are circularly shifted by 200 and 380 cells respectively, and then concatenated in sequence with the receive antenna in the Nr dimension to form a demodulated data matrix with dimensions 200×512×24.

[0223] For the RDFFT data with a range cell number greater than or equal to 200, all transmit antennas are used for demodulation. That is, the RDFFT data is circularly shifted by [0, 120, 200, 380] in sequence along the Doppler dimension and then concatenated to form demodulated data with dimensions 312×512×32.

[0224] Furthermore, the data after near-range transmit demodulation is arranged according to the virtual array channels, and the number of FFT points M A = 48 in the azimuth dimension, forming an RDA 3D data matrix Ω with a size of 200×512×48. And Ω' = Ω.

[0225] The data after far-range transmit demodulation is arranged according to the virtual array channels, and the number of FFT points M A = 64 in the azimuth dimension, thus forming an RDA 3D data matrix Ω with a size of 312×512×64.

[0226] S1606, after completing the angle dimension FFT, obtain the RDA 3D data matrix Ω;

[0227] S1608, perform range judgment on the RDA 3D data matrix Ω;

[0228] In the near-range case, execute S1608-1 to perform target detection on the near-range data matrix Ω';

[0229] In the far-range case, execute S1608-2 to perform target detection on the far-range data matrix Ω';

[0230] Finally, execute S1610 for target detection and tracklet output;

[0231] In the above steps, from the angle range θ of concern pro calculate the angle cell number θ corresponding to the azimuth - dimension FFT pro_idx The formula is as follows:

[0232]

[0233] where ceil(·) represents rounding up, and mod(x,A) represents taking the modulus of x with respect to A.

[0234] Therefore, different angle ranges can be selected according to different distance information to obtain the corresponding spatial sub - domain RDA 3 - D data matrix Ω'.

[0235] Specifically, the far - range 3 - D data subset can be screened out from the far - range 3 - D radar data based on the above target angle cell number interval. Specifically, the target radar data is determined according to the target angle cell number interval and the demodulated received signal. The size of the RDA 3 - D data Ω' for far - range target detection is 312×512×23, and the above - mentioned target radar data is the detection point data obtained by performing CA - CFAR on the matrix Ω' to be detected.

[0236] For the near - range object, the data after near - range transmission and demodulation is arranged according to the virtual array channels, and the number of points M A of the azimuth - dimension FFT performed is 48, thus forming an RDA 3 - D data matrix Ω with a size of 312×512×48. During the near - range object detection process, the matrix Ω' to be detected = the RDA 3 - D data matrix Ω.

[0237] S3 - 5, perform target detection on the RDA 3 - D data matrix Ω' to obtain the target point - track distance, speed, and angle cell information R t , D t , A t . The target distance, speed, and angle estimated values can be calculated by the following formulas:

[0238] Target estimated distance = R t ×Δ r ; Target estimated speed = D t ×Δ d ;

[0239] Thus, the output of the target point - track information is completed.

[0240] Through the above embodiments of the present application, for near-range target detection, virtual sub-arrays formed by using some transmitting array elements are used to reduce the Doppler dimension emission demodulation operation amount, reduce the Doppler dimension sidelobes formed after demodulation, and thus also reduce the false alarm probability of near-range target detection; for far-range target detection, it is carried out in the subspace formed in the angle dimension, reducing the operation amount and storage space during detection, and rationally using the signal-to-noise ratio improvement brought by antenna coherent accumulation.

[0241] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0242] According to another aspect of the embodiments of the present application, there is also provided a radar data processing device for implementing the above radar data processing method. As Figure 17 shown, the device includes:

[0243] A first determination unit 1702, configured to determine a distance parameter and a virtual sub-array parameter for detecting a near-range object, where the distance parameter is used to indicate a distance interval corresponding to the near-range object, and the virtual sub-array parameter is used to indicate an element arrangement mode of a transmitting sub-array matching the near-range object;

[0244] A second determination unit 1704, configured to determine a target distance unit serial number corresponding to the distance parameter when first radar data matching a target space region is obtained, where the first radar data is obtained by performing a fast Fourier transform operation on target echo data, and the target echo data is echo data received by a target radar object and matching the target space region;

[0245] A screening unit 1706, configured to determine a first radar data subset matching the near-range object from the first radar data according to the target distance unit serial number;

[0246] A demodulation unit 1708, configured to perform a Doppler emission demodulation operation on the first radar data subset according to the matrix splicing mode indicated by the virtual sub-array parameter to obtain second radar data, where the second radar data is used to detect a near-range object in the target space region, and the near-range object is an object within the target distance indicated by the distance parameter in the target space region.

[0247] As an alternative solution, the above demodulation unit 1708 includes: an acquisition module, configured to acquire a Doppler unit serial number that matches the transmit phase offset parameter of the above target radar object; a cyclic shift module, configured to perform a cyclic shift operation on the above first radar data subset according to the cyclic shift parameter indicated by the above Doppler unit serial number to obtain a first reference data subset; a determination module, configured to determine a target matrix splicing method according to the element serial number and element position of the transmit array element indicated by the above virtual subarray parameter; a splicing module, configured to splice a plurality of data matrices included in the above first reference data subset according to the above target matrix splicing method to obtain the above second radar data, where the above virtual subarray parameter is determined by a simulation operation performed on the above target radar object.

[0248] As an alternative solution, the above radar data processing device further includes: a first determination module, configured to determine the above target distance unit serial number according to the ratio between the above distance parameter and the distance resolution of the above target radar object; a second determination module, configured to determine the above Doppler unit serial number according to the product of the above transmit phase offset parameter and a first signal quantity parameter, where the above first signal quantity parameter is used to indicate the number of modulation signals included in one frame of radar signal transmitted by the above target radar object.

[0249] As an alternative solution, the above radar data processing device further includes: a detection unit, configured to acquire the number of points in the azimuth dimension that matches the above virtual subarray parameter; perform a fast Fourier transform operation on the above second radar data in the azimuth dimension according to the number of points in the azimuth dimension and the arrangement method of the virtual array channels corresponding to the above virtual subarray parameter to obtain target radar data; perform an object detection operation according to the above target radar data.

[0250] As an alternative solution, the above screening unit 1706 is further configured to: determine a second radar data subset that matches a long-distance object from the above first radar data according to the above target distance unit serial number, where the distance unit serial number of the data elements in the above first radar data subset is less than or equal to the above target distance unit serial number, and the distance unit serial number of the data elements in the above second radar data subset is greater than the above target distance unit serial number.

[0251] As an alternative solution, the above-mentioned screening unit 1706 is further configured to: determine a target angle unit serial number range for detecting a far-distance object; perform a Doppler transmit demodulation operation on the second radar data subset according to the target distance unit serial number to obtain third radar data; perform a fast Fourier transform operation on the third radar data in the azimuth dimension according to the number of points in the azimuth dimension matching the far-distance object and the arrangement mode corresponding to the virtual array channels of the far-distance virtual subarray parameters to obtain far-distance three-dimensional radar data; determine a far-distance three-dimensional data subset from the far-distance three-dimensional radar data according to the target angle unit serial number range, where the angle unit serial numbers of the data elements included in the far-distance three-dimensional data subset are within the target angle unit serial number range; and determine the far-distance three-dimensional data subset as the reference radar data for object detection of the far-distance object, where the far-distance object is an object outside the target distance indicated by the distance parameter in the target space region.

[0252] As an alternative solution, the processing of the above-mentioned radar data further includes: a simulation unit, configured to obtain a plurality of candidate code pattern combinations when determining the number of transmit array elements and receive array elements of the target radar object, where the candidate code pattern combinations are used to indicate the number of array elements and the array element serial numbers of at least one object array element extracted from a plurality of transmit array elements; obtain first simulation results corresponding to the plurality of candidate code pattern combinations respectively, where the first simulation results include at least one of the following: the sidelobe height of at least one Doppler sidelobe, the position of at least one of the Doppler sidelobes; and determine at least one first code pattern combination from the plurality of candidate code pattern combinations according to the first simulation results corresponding to the plurality of candidate code pattern combinations respectively, where the virtual subarray parameters are used to indicate the first code pattern combination.

[0253] As an alternative solution, the simulation unit is configured to perform at least one of the following: when the sidelobe height of at least one of the Doppler sidelobes corresponding to the current candidate code pattern combination among the plurality of candidate code pattern combinations is less than or equal to a first threshold, determine the current candidate code pattern combination as the first code pattern combination; when the distribution state of at least one of the Doppler sidelobes corresponding to the current candidate code pattern combination among the plurality of candidate code pattern combinations is less than or equal to a second threshold, determine the current candidate code pattern combination as the first code pattern combination.

[0254] As an alternative solution, the above simulation unit is further configured to: obtain at least one reference radar deployment information; according to the at least one reference radar deployment information, the distance parameter, and the angle interval parameter, obtain target simulation results respectively corresponding to the at least one reference radar deployment information, where the target simulation results include main-to-side lobe ratio parameters; according to the target simulation results, determine target radar deployment information from the at least one reference radar deployment information, where the target radar deployment information is used to indicate the deployment parameters of the target radar object.

[0255] As an alternative solution, the above simulation unit is further configured to: obtain the height estimation parameter of the near object; according to the height estimation parameter and multiple candidate object distances, determine the elevation angles respectively corresponding to the multiple candidate object distances; when at least one reference radar deployment information is obtained, obtain at least one reference simulation result according to the reference radar deployment information and the multiple elevation angles, where the reference simulation results include at least one of the following: angle measurement error value, main-to-side lobe ratio change rate; according to the at least one reference simulation result that satisfies the first constraint condition, determine the distance parameter.

[0256] For specific embodiments, reference may be made to the examples shown in the above radar data processing method, and details are not described herein again.

[0257] Among them, the memory 1802 can be used to store software programs and modules, such as the program instructions / modules corresponding to the radar data processing method and device in the embodiments of the present invention. The processor 1804 executes various functional applications and data processing by running the software programs and modules stored in the memory 1802, that is, implements the above radar data processing method. The memory 1802 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 1802 may further include a memory remotely disposed relative to the processor 1804, and these remote memories may be connected to the terminal through a network. Examples of the above network include but are not limited to the Internet, enterprise intranet, local area network, mobile communication network, and combinations thereof. Among them, the memory 1802 may specifically but not limitedly be used to store file information such as target files. As an example, as Figure 18 shown, the memory 1802 may include but is not limited to the first determination unit 1702, the second determination unit 1704, the screening unit 1706, and the demodulation unit 1708 in the above radar data processing device. In addition, it may further include but is not limited to other module units in the above radar data processing device, which are not described in detail in this example.

[0258] Optionally, the above-mentioned transmission device 1806 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wired network and a wireless network. In one example, the transmission device 1806 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices and routers through a network cable, so as to communicate with the Internet or a local area network. In one example, the transmission device 1806 is a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0259] In addition, the above-mentioned electronic device further includes: a display 1808, and a connection bus 1810, which is used to connect each module component in the above-mentioned electronic device.

[0260] According to one aspect of the present application, a computer program product is provided. The computer program product includes computer programs / instructions, and the computer programs / instructions contain program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit, various functions provided by the embodiments of the present application are executed.

[0261] The serial numbers of the embodiments of the present application above are only for description and do not represent the advantages or disadvantages of the embodiments.

[0262] It should be noted that the computer system of the electronic device is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0263] In particular, according to the embodiments of the present application, the processes described in each method flowchart can be implemented as computer software programs. For example, the embodiments of the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit, various functions defined in the system of the present application are executed.

[0264] According to one aspect of the present application, a computer-readable storage medium is provided. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above various optional implementation manners.

[0265] Optionally, in this embodiment, the above-mentioned computer-readable storage medium can be set to store a computer program for executing the following steps:

[0266] S1. Determine a distance parameter and a virtual subarray parameter for detecting a short-range object, where the distance parameter is used to indicate the distance range corresponding to the short-range object, and the virtual subarray parameter is used to indicate the arrangement mode of the array elements of the transmitting subarray matched with the short-range object;

[0267] S2. When first radar data matching a target space region is obtained, determine a target distance cell number corresponding to the distance parameter, where the first radar data is obtained by performing a fast Fourier transform operation on target echo data, and the target echo data is echo data received by a target radar object and matching the target space region;

[0268] S3. Determine a first radar data subset matching the short-range object from the first radar data according to the target distance cell number;

[0269] S4. Perform a Doppler transmit demodulation operation on the first radar data subset according to the matrix splicing mode indicated by the virtual subarray parameter to obtain second radar data, where the second radar data is used to detect a short-range object in the target space region, and the short-range object is an object within the target distance indicated by the distance parameter in the target space region.

[0270] Optionally, in this embodiment, those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by a program instructing relevant hardware of an electronic device. The program can be stored in a computer-readable storage medium, and the storage medium can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0271] The serial numbers of the embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0272] If the integrated unit in the above embodiments is implemented in the form of a software function unit and sold or used as an independent product, it can be stored in the above computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing one or more computer devices (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application.

[0273] In the above embodiments of the present application, the descriptions of the various embodiments each have their own focuses. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0274] In several embodiments provided by the present application, it should be understood that the disclosed user equipment can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of units or modules can be in an electrical or other form.

[0275] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0276] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0277] The above is only the preferred embodiment of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A method for processing radar data, characterized in that: include: Determining a distance parameter and a virtual subarray parameter for detecting a close object, wherein the distance parameter is used to indicate a distance interval corresponding to the close object, and the virtual subarray parameter is used to indicate an array element arrangement mode of a transmitting subarray matching the close object; In the case of acquiring first radar data matching the target spatial region, determining a target distance unit sequence number corresponding to the distance parameter, wherein the first radar data is obtained by performing a fast Fourier transform operation on target echo data, and the target echo data is echo data received by the target radar object and matching the target spatial region; determining, from the first radar data, a first radar data subset matching the close-range object according to the target range unit sequence number; A Doppler transmit demodulation operation is performed on the first radar data subset according to the matrix splicing mode indicated by the virtual subarray parameters to obtain second radar data, wherein the second radar data is used to detect close objects in the target space area, and the close objects are objects within the target distance indicated by the distance parameters in the target space area.

2. The method according to claim 1, characterized in that The performing a Doppler transmit demodulation operation on the first radar data subset according to the matrix splicing mode indicated by the virtual subarray parameter to obtain second radar data includes: Obtaining a Doppler unit number that matches a transmit phase offset parameter of the target radar object; Performing a cyclic shift operation on the first radar data subset according to the cyclic shift parameter indicated by the Doppler unit sequence number to obtain a first reference data subset; Determining a target matrix splicing method according to the array element sequence number and array element position of the transmitting array element indicated by the virtual sub-array parameter; The plurality of data matrices included in the first reference data subset are spliced ​​according to the target matrix splicing method to obtain the second radar data, wherein the virtual subarray parameters are determined by a simulation operation performed on the target radar object.

3. The method according to claim 2, characterized in that The determining of the target distance unit sequence number corresponding to the distance parameter comprises: Determining the target range unit number according to a ratio between the range parameter and the range resolution of the target radar object; The obtaining of the Doppler unit sequence number matching the transmission phase offset parameter of the target radar object comprises: The Doppler unit number is determined according to the product of the transmit phase offset parameter and a first signal quantity parameter, wherein the first signal quantity parameter is used to indicate the number of modulated signals included in a frame of radar signals transmitted by the target radar object.

4. The method according to claim 2, characterized in that: After the plurality of data matrices included in the first reference data subset are spliced ​​according to the target matrix splicing method to obtain the second radar data, the method further includes: Obtaining the number of azimuth dimension points matching the virtual subarray parameters; According to the number of azimuth dimension points and the arrangement of virtual array channels corresponding to the virtual subarray parameters, a fast Fourier transform operation is performed on the second radar data in the azimuth dimension to obtain target radar data; An object detection operation is performed based on the target radar data.

5. The method according to claim 2, characterized in that: When determining a first radar data subset matching the close-range object from the first radar data according to the target distance unit sequence number, the method further includes: A second radar data subset matching the long-range object is determined from the first radar data according to the target range unit number, wherein the range unit number of the data elements in the first radar data subset is less than or equal to the target range unit number, and the range unit number of the data elements in the second radar data subset is greater than the target range unit number.

6. The method according to claim 5, characterized in that After determining a second radar data subset matching the close-range object from the first radar data according to the target range unit sequence number, the method further includes: Determining a target angle unit sequence number interval for detecting a distant object; Performing a Doppler transmit demodulation operation on the second radar data subset according to the target range unit sequence number to obtain third radar data; According to the number of azimuth dimension points matching the long-range object and the arrangement of virtual array channels corresponding to the long-range virtual subarray parameters, a fast Fourier transform operation is performed on the third radar data in the azimuth dimension to obtain long-range three-dimensional radar data; Determining a long-range 3D data subset from the long-range 3D radar data according to the target angle unit sequence number interval, wherein the angle unit sequence numbers of the data elements included in the long-range 3D data subset are located in the target angle unit sequence number interval; The long-range three-dimensional data subset is determined as reference radar data for object detection of the long-range object, wherein the long-range object is an object outside the target distance indicated by the distance parameter in the target space region.

7. The method according to claim 1, characterized in that Before determining the distance parameter and the virtual sub-array parameter for detecting the close-range object, the method further includes: When the number of transmitting array elements and receiving array elements of the target radar object is determined, a plurality of candidate code pattern combinations are obtained, wherein the candidate code pattern combinations are used to indicate the number of array elements and array element sequence numbers of at least one object array element extracted from the plurality of transmitting array elements; Acquire first simulation results corresponding to each of the plurality of candidate code pattern combinations, wherein the first simulation results include at least one of the following: a sidelobe height of at least one Doppler sidelobe, and a position of at least one Doppler sidelobe; At least one first code pattern combination is determined from the plurality of candidate code pattern combinations according to first simulation results corresponding to each of the plurality of candidate code pattern combinations, wherein the virtual subarray parameter is used to indicate the first code pattern combination.

8. The method according to claim 7, characterized in that The step of determining at least one first code pattern combination from the plurality of candidate code pattern combinations according to the first simulation results respectively corresponding to the plurality of candidate code pattern combinations comprises at least one of the following: When the side lobe height of at least one Doppler side lobe corresponding to the current candidate code pattern combination among the multiple candidate code pattern combinations is less than or equal to the first threshold, determining the current candidate code pattern combination as the first code pattern combination; When the distribution state of at least one Doppler sidelobe corresponding to a current candidate code pattern combination among the multiple candidate code pattern combinations is less than or equal to a second threshold, the current candidate code pattern combination is determined as the first code pattern combination.

9. The method according to claim 1, characterized in that: Before determining the distance parameter and the virtual sub-array parameter for detecting the close-range object, the method further includes: Acquiring at least one reference radar array information; According to at least one of the reference radar array information, the distance parameter and the angle interval parameter, obtaining a target simulation result corresponding to at least one of the reference radar array information, wherein the target simulation result includes a main-sidelobe ratio parameter; According to the target simulation result, target radar array information is determined from at least one of the reference radar array information, wherein the target radar array information is used to indicate array parameters of the target radar object.

10. The method according to claim 1, characterized in that Before determining the distance parameter and the virtual sub-array parameter for detecting the close-range object, the method further includes: Obtaining a height estimation parameter of the close object; Determining, according to the height estimation parameter and a plurality of candidate object distances, a pitch angle corresponding to each of the plurality of candidate object distances; In the case of obtaining at least one reference radar array information, obtaining at least one reference simulation result according to the reference radar array information and the plurality of pitch angles, wherein the reference simulation result includes at least one of the following: an angle measurement error value, a main-sidelobe ratio change rate; and determining the distance parameter according to the at least one reference simulation result satisfying the first constraint condition.

11. A radar data processing device, characterized in that: include: A first determining unit, configured to determine a distance parameter and a virtual subarray parameter for detecting a close object, wherein the distance parameter is used to indicate a distance interval corresponding to the close object, and the virtual subarray parameter is used to indicate an array element arrangement mode of a transmitting subarray matching the close object; The second determining unit is used to determine the target distance unit number corresponding to the distance parameter when the first radar data matching the target space area is acquired, wherein: The first radar data is obtained by performing a fast Fourier transform operation on the target echo data. The target echo data is the echo data received by the target radar object and matching the target spatial area; a screening unit, configured to determine, from the first radar data, a first radar data subset matching the close-range object according to the target range unit sequence number; A demodulation unit, configured to determine the matrix splicing mode indicated by the virtual sub-array parameters, Perform a Doppler transmit demodulation operation on the first radar data subset to obtain second radar data, wherein the second radar data is used to detect close-range objects in the target space area, and the close-range objects are objects within the target distance indicated by the distance parameter in the target space area.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method described in any one of claims 1 to 10 when executed by an electronic device.

13. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 10 through the computer program.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

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