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

Abstract

The present application discloses a radar data processing method, device, storage medium and electronic device. The method includes: determining a distance parameter and an angle interval parameter for detecting a long-distance object; determining a target distance unit number corresponding to the distance parameter when first radar data matching the target spatial area is obtained; performing a Doppler transmission demodulation operation on the first radar data according to the target distance unit number to obtain second radar data; determining a target angle unit number interval corresponding to the angle interval parameter, and determining the target radar data according to the target angle unit number interval and the second radar data. The present application solves the technical problems of low processing efficiency and poor processing accuracy of radar data in the prior art.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving, and more specifically, to a radar data processing method, device, storage medium and electronic device. Background Art

[0002] With the widespread application of millimeter-wave radar in the autonomous driving industry, the requirements for the maximum detection distance, ranging, speed measurement, and angle measurement performance are gradually increasing. MIMO (multiple-input multiple-output) virtual array technology improves spatial resolution by adding virtual channels. A MIMO radar with Nr receiving antennas and Nt transmitting antennas can form a virtual antenna array of Nr×Nt dimensions, greatly increasing the antenna aperture to achieve an improvement in target angular resolution. The application of DDMA (Doppler domain multiple access) waveform technology transmits radar signals simultaneously through Nt different transmitting antennas. Compared with traditional time division multiplexing multiple transmission and multiple reception technology (TDM-MIMO), a higher transmission gain can be obtained under the same time requirements. 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 speed of the target.

[0003] For long-range targets, the signal-to-noise ratio is often weak and difficult to detect. Since long-range targets are limited, the sensitivity to Doppler side lobes is often weak. Therefore, the main pain points for long-range targets are low detection probability and low measurement accuracy due to low signal-to-noise ratio, and processing all regional data results in a large amount of processed data and low processing efficiency. In other words, the prior art has the technical problems of low processing efficiency and poor processing accuracy of radar data. Summary of the invention

[0004] The embodiments of the present application provide a radar data processing method, device, storage medium and electronic device to at least solve the technical problems of low radar data processing efficiency and poor processing accuracy in the prior art.

[0005] According to one aspect of an embodiment of the present application, a radar data processing method is provided, including: determining a distance parameter and an angle interval parameter for detecting a long-range object; determining a target distance unit number corresponding to the distance parameter when first radar data matching a target spatial region is acquired, 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 matching the target spatial region received by the target radar object; performing a Doppler transmission demodulation operation on the first radar data according to the target distance unit number to obtain second radar data; determining a target angle unit number interval corresponding to the angle interval parameter, and determining target radar data according to the target angle unit number interval and the second radar data, wherein the target radar data is used to detect a target object in the target spatial region, and the target object is an object outside the target distance indicated by the distance parameter in the target spatial region.

[0006] According to another aspect of an embodiment of the present application, a radar data processing device is also provided, including: a first determination unit, determining a distance parameter and an angle interval parameter for detecting a long-range object; a second determination unit, determining a target distance unit serial number corresponding to the distance parameter when first radar data matching a target spatial region is acquired, 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 matching the target spatial region received by the target radar object; an acquisition unit, performing a Doppler transmission demodulation operation on the first radar data according to the target distance unit serial number to obtain second radar data; a third determination unit, determining a target angle unit serial number interval corresponding to the angle interval parameter, and determining the target radar data according to the target angle unit serial number interval and the second radar data, wherein the target radar data is used to detect a target object in the target spatial region, and the target object is an object outside the target distance indicated by the distance parameter in the target spatial region.

[0007] As an optional solution, the acquisition unit is further used to determine a first radar data subset and a second radar data subset from the first radar data according to the range unit number, wherein the range unit number of the data elements in the first radar data subset is greater 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 less than the target range unit number; obtain a Doppler unit number that matches the transmit phase offset parameter of the target radar object; perform a cyclic shift operation on the first radar data subset according to the cyclic shift parameter indicated by the Doppler unit number to obtain a first reference data subset; and splice multiple data matrices included in the first reference data subset according to a matrix splicing method indicated by a subarray dimension of a long-range virtual subarray to obtain the second radar data, wherein the subarray dimension of the long-range virtual subarray is determined by a simulation operation performed on the target radar.

[0008] As an optional solution, the above-mentioned radar data processing device also includes a fourth determination module, which is used to determine the target range unit number according to the ratio between the range parameter and the range resolution of the target radar object; and determine the Doppler unit number according to the product between the transmission phase offset parameter and the 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.

[0009] As an optional solution, the above-mentioned acquisition unit also includes a matrix processing module, which is used to perform a cyclic shift operation on the second radar data subset according to the cyclic shift parameter indicated by the Doppler unit sequence number to obtain a second reference data subset; according to the matrix splicing method indicated by the subarray dimension of the close-range virtual subarray, multiple data matrices included in the second reference data subset are spliced ​​to obtain second close-range radar data, wherein the subarray dimension of the close-range virtual subarray is determined by a simulation operation performed on the target radar, and the second close-range radar data is used to perform object detection on a reference object, and the reference object is an object within the target distance indicated by the distance parameter in the target space area.

[0010] As an optional scheme, the above-mentioned third determination unit includes a fifth determination module, which is used to arrange the second radar data according to the virtual array channel, and perform a fast Fourier transform operation on the arranged second radar data in the azimuth dimension according to the first number of points to obtain long-range three-dimensional radar data; according to the target angle unit sequence number interval, determine a long-range three-dimensional data subset from the long-range three-dimensional radar data, wherein the angle unit sequence numbers of the data elements included in the long-range three-dimensional data subset are within the target angle unit sequence number interval; and determine the long-range three-dimensional data subset as the target radar data.

[0011] As an optional scheme, the above-mentioned fifth determination module is also used to obtain at least one angle boundary value in the angle interval parameter; determine the first reference value corresponding to each of the at least one angle boundary values ​​according to half of the product between the sine value of each of the at least one angle boundary value and the first point number; determine at least one angle unit boundary number according to the modulo result between at least one first reference value and the first point number; determine the target angle unit boundary number interval according to at least one angle unit boundary number.

[0012] As an optional solution, the above-mentioned matrix processing module includes an execution module for arranging the second short-range radar data according to the virtual array channel, and performing a fast Fourier transform operation on the arranged second short-range radar data in the azimuth dimension according to the second number of points to obtain short-range three-dimensional radar data; and performing an object detection operation based on the short-range three-dimensional radar data.

[0013] As an optional scheme, the above-mentioned first determination unit is also used to obtain a 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; 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 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; determine the distance parameter according to at least one reference simulation result that satisfies the first constraint condition.

[0014] As an optional solution, the first determination unit is further configured to determine a functional area for detecting the target object according to the type of the target radar object; and to determine an angle interval parameter according to the distance parameter and the functional area.

[0015] As an optional solution, the above-mentioned radar data processing device also includes a second acquisition module, which is used 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, the target simulation result corresponding to the at least one reference radar array information is obtained, wherein the target simulation result includes a main-sidelobe ratio parameter; according to the target simulation result, the target radar array information is determined from the at least one reference radar array information, wherein the target radar array information is used for the array parameters of the target radar object.

[0016] According to another aspect of the embodiment of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, the computer instructions are 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 radar data processing method.

[0017] According to another aspect of an embodiment of the present application, there is also provided an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the radar data processing method through the computer program.

[0018] In the above-mentioned embodiment of the present application, a distance parameter and an angle interval parameter for detecting a long-distance object are determined; when first radar data matching a target spatial region is obtained, a target distance unit number corresponding to the distance parameter is determined, 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 matching the target spatial region received by the target radar object; a Doppler transmission demodulation operation is performed on the first radar data according to the target distance unit number to obtain second radar data; a target angle unit number interval corresponding to the angle interval parameter is determined, and target radar data is determined from the second radar data according to the target angle unit number interval, wherein the target radar data is used to detect a target object in the target spatial region, and the target object is an object outside the target distance indicated by the distance parameter in the target spatial region.

[0019] Through the above-mentioned implementation mode of the present application, the distance parameter and the angle interval parameter for detecting the long-distance object are first determined, and the angle range of the long-distance starting point and the area of ​​interest is determined; further, when the first radar data matching the target spatial area is obtained, the target distance unit number corresponding to the distance parameter is determined, wherein 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 matching the target spatial area received by the target radar object; the Doppler transmission demodulation operation can be performed on the first radar data according to the target distance unit number to obtain the second radar data; the target angle unit number interval corresponding to the angle interval parameter is determined, and the target radar data is determined from the second radar data according to the target angle unit number interval, thereby solving the technical problems of low processing efficiency and poor processing accuracy of radar data in the prior art. BRIEF 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 of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

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

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

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

[0024] Figure 4is a schematic diagram of an optional radar array method according to an embodiment of the present application;

[0025] Figure 5 is a schematic diagram of an optional distance-pitch angle relationship according to an embodiment of the present application;

[0026] Figure 6 is a schematic diagram of an optional angle measurement error according to an embodiment of the present application;

[0027] Figure 7 is an optional main-sidelobe ratio influence schematic diagram according to an embodiment of the present application;

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

[0029] Fig. 9 is another optional main-sidelobe ratio influence schematic diagram according to an embodiment of the present application;

[0030] Fig.10 is another optional angle-dimensional spectrum schematic diagram according to an embodiment of the present application;

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

[0032] Fig.12 is a flowchart of another optional radar data processing method according to an embodiment of the present application;

[0033] Fig.13 is a flowchart of another optional radar data processing method according to an embodiment of the present application;

[0034] Fig.14 is a schematic diagram of a radar data processing device according to an embodiment of the present application;

[0035] Fig.15 It is a schematic diagram of the structure of an optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0037] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0038] According to one aspect of an embodiment of the present application, a method for processing radar data is provided. Optionally, the method for processing radar data can be applied to, but is not limited to, Figure 1 In the hardware environment shown. Optionally, the radar data processing method provided by the present application can be applied to a vehicle terminal. Figure 1 A side view of a vehicle terminal 101 is shown, and the vehicle terminal 101 can travel on a travel surface 113. The vehicle terminal 101 includes an onboard navigation system 103, a memory 102 storing a digitized 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.

[0039] In one embodiment, the space monitoring system 117 includes one or more space sensors and systems, which are used to monitor the visible area 105 in front of the vehicle terminal 101. The space monitoring system 117 also includes a space monitoring controller 118; the space sensors used to monitor the visible area 105 include a laser radar 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 sensor. The space monitoring controller 118 can determine the linear range, relative speed and trajectory of the vehicle terminal 101 based on the input from the space sensor, for example, determine the current speed of the vehicle and the relative speed compared to the front vehicle. The space sensor of the vehicle terminal space monitoring system 117 may include an object positioning sensing device, and the object positioning sensing device may include a range sensor, which can be used to locate the front object such as the front vehicle object.

[0040] The camera 108 is advantageously mounted and positioned on the vehicle terminal 101 in a position that allows capturing an image of the visible area 105, wherein at least a portion of the visible area 105 includes a portion of the travel surface 113 in front of the vehicle terminal 101 and including the trajectory of the vehicle terminal 101. The visible area 105 may also include the surrounding environment. Other cameras may also be used, for example, including a second camera disposed on the rear 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.

[0041] The autonomous controller 112 is configured to implement autonomous driving or advanced driver assistance system (ADAS) vehicle terminal functionality. Such functionality may include a vehicle terminal onboard control system capable of providing a certain level of driving automation. Driving automation may include a range of dynamic driving and vehicle terminal operations. Driving automation may include a certain level of automatic control or intervention involving a single vehicle terminal function (e.g., steering, acceleration, and / or braking).

[0042] In this implementation, the radar data processing process is applied to the above scenario, as follows:

[0043] S102, determining a distance parameter and an angle interval parameter for detecting a distant object;

[0044] S104, when first radar data matching the target spatial region is acquired, 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 matching the target spatial region received by the target radar object;

[0045] S106, performing a Doppler transmission demodulation operation on the first radar data according to the target range unit sequence number to obtain second radar data;

[0046] S108, determine the target angle unit serial number interval corresponding to the angle interval parameter, and determine the target radar data based on the target angle unit serial number interval and the second radar data, wherein the target radar data is used to detect the target object in the target space area, and the target object is an object outside the target distance indicated by the distance parameter in the target space area.

[0047] 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, onboard navigation system 103 and the like, and includes a controller. The HMI device 111 monitors operator requests and provides the operator with status, service and maintenance information of the vehicle terminal system. The HMI device 111 communicates with multiple operator interface devices and / or controls the operation of multiple operator interface devices. The HMI device 111 may 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 the embodiments of the system described herein, it may be configured as multiple controllers and associated sensing devices.

[0048] Operator controls may be included in the passenger compartment of the vehicle terminal 101, and may include, by way of non-limiting example, 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 a vehicle terminal operator to interact with the operating vehicle terminal 101 and direct the operation of the vehicle terminal 101 to provide passenger transportation.

[0049] The onboard navigation system 103 uses the digitized road map 104 for the purpose of providing navigation support and information to the vehicle terminal operator. The autonomous controller 112 uses the digitized road map 104 for the purpose of controlling the autonomous vehicle terminal operation or ADAS vehicle terminal functions.

[0050] The vehicle terminal 101 may include a telematics controller 114, which includes a wireless telematics communication system capable of communicating outside the vehicle terminal (including communicating with a communication network 115 having wireless and wired communication capabilities). The wireless telematics communication system includes an off-board server 116 capable of short-range wireless communication with a mobile terminal.

[0051] As an optional implementation, Figure 2 As shown, the radar data processing method can be performed by the radar sensor alone or together with other electronic devices, and the specific steps include:

[0052] S202, determining a distance parameter and an angle interval parameter for detecting a distant object;

[0053] S204, when first radar data matching the target spatial region is acquired, 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 matching the target spatial region received by the target radar object;

[0054] S206, performing a Doppler transmission demodulation operation on the first radar data according to the target range unit sequence number to obtain second radar data;

[0055] S208, determine the target angle unit serial number interval corresponding to the angle interval parameter, and determine the target radar data based on the target angle unit serial number interval and the second radar data, wherein the target radar data is used to detect the target object in the target space area, and the target object is an object outside the target distance indicated by the distance parameter in the target space area.

[0056] In the above step S202, the distance parameter and the angle interval parameter for detecting the long-distance object are determined; in an optional embodiment, the above distance parameter can be used to define the starting distance for long-distance target detection, and the above distance parameter can be determined according to the performance requirements of the radar system, such as the farthest detection distance, target detection probability and other indicators. The above angle interval parameter can be the angle interval of the area of ​​interest. For example, the area 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 radar is installed on both sides of the vehicle and is mainly used for blind spot monitoring (BSD), lane change assistance (LCA) and other functions. The area of ​​interest of the side radar may be concentrated in a certain angle range on the side of the vehicle, such as 0 degrees to 30 degrees or -30 degrees to 0 degrees in the left and right 90-degree fields of view. This is only an example.

[0057] Further in the above step S204, when the first radar data matching the target spatial area is obtained, the target distance unit number corresponding to the distance parameter is determined, wherein 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 spatial area.

[0058] Optionally, obtaining the first radar data matching the target spatial region may be performed, for example, by the following process: for example, the number of radar antenna parameters receiving array elements is 8, the number of transmitting antennas is 4, one processing cycle is one frame, and the number of chirps in one frame is M. D =512, the number of fast time sampling points for each chirp M R=512. After performing distance dimension FFT and Doppler dimension FFT on the 8 receiving channels of the original echo data, the distance unit range of the RD (range, Doppler) FFT data is [0,511], the Doppler unit range is [0,511], and the RDFFT data dimension is 512×512×8, corresponding to the first radar data; the echo data can be specifically the signal data emitted and captured by the radar to the target object at the target distance, and the target echo data size is 512×512×8. The target radar object can be installed in vehicles, roads, etc., and can have different functions.

[0059] Determining the target distance unit number corresponding to the distance parameter can be done by, for example, setting the long-range starting distance to 100 meters. Determining the system distance resolution Δ r is 0.5m, velocity resolution Δ d is 0.45 m / s. Taking the common front radar as an example, the angle range of interest at long distance is set to θ pro ∈[-20°~20°]. The formula for calculating the corresponding distance unit number from the distance resolution is:

[0060] R far_idx =R far / Δ r , where R far That is, the distance parameter is used to indicate the critical distance value for distinguishing long-distance and short-distance. The specific value corresponds to the long-distance starting distance of 100 meters, and then R is obtained. far_idx =200.

[0061] Optionally, in the above step S206, a Doppler transmit demodulation operation is performed on the first radar data according to the target range unit sequence number to obtain second radar data;

[0062] As an optional implementation, for example, the transmission phase offsets Δ of the second to fourth channels relative to the first channel in the four transmitting antennas of the DDMA waveform are θ They are 84.375°, 140.625°, and 267.1875° respectively. The following formula is used to calculate the transmission phase offset Δ θ Calculate the corresponding Doppler unit number:

[0063]

[0064] Therefore, the Δ of the second to fourth channels relative to the first channel in the transmitting antenna can be obtained. θ_idxThey are 120, 200, and 380 respectively. In this embodiment, for RDFFT data with a range unit number greater than or equal to 200, all transmitting antennas are used to participate in demodulation, that is, the RDFFT data is sequentially cyclically shifted [0, 120, 200, 380] in the Doppler dimension and then spliced ​​to form demodulated data, whose dimension is 312×512×32, corresponding to the above-mentioned second radar data.

[0065] Optionally, in the above step S208, determining the target angle unit sequence number interval corresponding to the angle interval parameter may be: arranging the demodulated data of the long-distance transmission according to the virtual array channel, and performing the azimuth dimension FFT point number M A =64, thus forming an RDA (range, Doppler, angle) 3D data matrix Ω of size 312×512×64.

[0066] Further, according to the set area range of the angle of interest, the formula Where ceil(·) means rounding up, mod(x,A) means taking x modulo A, and calculating the range of the long-distance angle dimension processing unit number θ pro_idx ∈[0:11,53:63].

[0067] The target radar data is determined according to the target angle unit sequence number interval and the second radar data obtained by demodulating the received signal. The size of the RDA3-dimensional data Ω' used for long-range target detection is 312×512×23. The above target radar data is the detection point data obtained by performing CA-CFAR on the detection matrix Ω'. The above target object is a long-range object, that is, the distance relative to the radar is greater than 100m.

[0068] The above process is described below in a specific implementation manner:

[0069] S1, according to the radar system performance requirements, complete the radar antenna and waveform design, and the transmission channel transmits DDMA waveforms with different phase changes. Including the number of MIMO antenna receiving array elements Nr and the number of transmitting antennas Nt. The phase offset Δ corresponding to the transmitting antenna under the DDMA system θ The number of chirps in the processing cycle M D and the number of fast time sampling points M for each chirp R . Determine the system distance resolution Δ r , velocity resolution Δ d .

[0070] For example, the design parameters of radar antenna include the number of receiving array elements = 8, the number of transmitting antennas = 4, and the dimension of the virtual array = 8*4 = 32. The transmission phase offsets of the second to fourth channels relative to the first channel of the four transmitting antennas of the DDMA waveform are 84.375°, 140.625°, and 267.1875°, respectively. One processing cycle is one frame, the number of chirps in one frame = 512, and the number of fast time sampling points of each chirp = 512. The system distance resolution is 0.5 meters, and the velocity resolution is 0.45 meters per second.

[0071] S2, determine the signal processing long-distance starting position R far For example, set the long-range starting distance to 100 meters, take the common front radar as an example, and set the angle range of interest for the long-range θ pro ∈[-20°~20°].

[0072] S3, down-convert the radar echo data, and obtain the original echo data after completing the digital-to-analog conversion. The original echo data enters the signal processing link for target detection processing. The specific steps are as follows Figure 3 As shown:

[0073] S302, performing distance and Doppler dimension FFT on the original echo data to obtain RDFFT data; specifically, performing distance dimension FFT on the fast time sampling points of the original echo data, and then performing Doppler FFT in the chirp dimension to obtain range Doppler FFT (RDFFT) data.

[0074] S304, performing distance judgment on the RDFFT data; S304-2, completing transmit Doppler dimension demodulation according to the long-range virtual sub-array;

[0075] Specifically, the following formula can be used to calculate the transmission phase offset Δ θ Calculate the corresponding Doppler unit number:

[0076] Calculate R based on distance accuracy far The corresponding distance dimension unit number R far__idx The formula is as follows: far_idx =R far / Δ r .

[0077] By R far_idx Determine the distance range of the RDFFT data involved in the processing, and calculate the RDFFT data of different distance ranges according to Δ θ_idx Doppler dimension demodulation is performed on different transmitting sub-arrays to obtain demodulated data. In this embodiment, RDFFT data of a long range is demodulated.

[0078] S306, after completing the angle dimension FFT, the RDA 3-dimensional data matrix Ω is obtained;

[0079] Specifically, after performing range-dimensional FFT and Doppler-dimensional FFT on the eight receiving channels of the original echo data, the range unit range of the RDFFT data is [0,511], and the Doppler unit range is [0,511], that is, the RDFFT data dimension is 512×512×8.

[0080] Further, according to the formula in S304, the second channel to the fourth channel in the transmitting antenna are calculated relative to the first channel Δ θ_idx They are 120, 200 and 380 respectively.

[0081] R is calculated according to the formula in S304 far_idx =200.

[0082] For RDFFT data with range unit numbers greater than or equal to 200, all transmitting antennas are used to participate in demodulation, that is, the RDFFT data is cyclically shifted [0, 120, 200, 380] in the Doppler dimension and then concatenated to form demodulated data with a dimension of 312×512×32.

[0083] S308, perform distance judgment on the RDA 3D data matrix Ω; S308-2, perform target detection on the long-distance data matrix Ω'; S310, target detection and point trace output;

[0084] The demodulated data of the long-distance transmission is arranged according to the virtual array channel, and the azimuth dimension FFT point number M is performed. A =64, thus forming an RDA 3D data matrix Ω of size 312×512×64.

[0085] By formula Calculate the long-distance angle dimension processing unit number range θ pro_idx ∈[0:11,53:63]. The size of the RDA3D data Ω' for long-range object detection is 312×512×23.

[0086] Assume that the target point information is obtained by performing CA-CFAR on the matrix Ω' to be detected, for example, the target is detected at the distance unit number = 250, the Doppler unit number = 300, and the angle unit number = 10. The target estimated distance = 125 meters, the target estimated speed = 60 meters / second, and the target estimated angle = 1.57 degrees are calculated and determined, and the specific calculation method is not specifically limited.

[0087] Through the above implementation of the present application, the distance parameter and angle interval parameter for detecting the long-distance object are first determined, the angle range of the long-distance starting point and the area of ​​interest is determined, and the reduction of the signal-to-noise ratio caused by the traditional full-field-of-view processing is avoided, thereby improving the accuracy of long-distance weak target detection; further, when the first radar data matching the target spatial area is obtained, the target distance unit number corresponding to the distance parameter is determined, wherein 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 spatial area, and the target echo data can be obtained according to the target The expected distribution of the target is determined, and the angle interval parameters and the transmission demodulation strategy are adjusted; the Doppler transmission demodulation operation is performed on the first radar data according to the target distance unit number to obtain the second radar data; the target angle unit number interval corresponding to the angle interval parameter is determined, and the target radar data is determined from the second radar data according to the target angle unit number interval. By selecting the angle range of the area of ​​interest, only the angle units associated with the target object are processed, thereby avoiding redundant calculations on the full field of view 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.

[0088] In an optional implementation, performing a Doppler transmit demodulation operation on the first radar data according to the target range unit sequence number to obtain the second radar data includes:

[0089] S1, determining a first radar data subset and a second radar data subset from the first radar data according to the range unit sequence number, wherein the range unit sequence number of the data elements in the first radar data subset is greater than or equal to the target range unit sequence number, and the range unit sequence number of the data elements in the second radar data subset is less than the target range unit sequence number;

[0090] S2, obtaining the Doppler unit number that matches the transmission phase offset parameter of the target radar object;

[0091] S3, 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;

[0092] S4, splicing a plurality of data matrices included in the first reference data subset according to a matrix splicing method indicated by a subarray dimension of a long-range virtual subarray to obtain second radar data, wherein the subarray dimension of the long-range virtual subarray is determined by a simulation operation performed on the target radar.

[0093] In the above step S1, the first radar data subset and the second radar data subset are determined from the first radar data according to the range unit number; for example, the long-range starting distance is set to 100m, and the corresponding target range unit number calculated by the range resolution is 200, then the range unit number of the data elements in the above first radar data subset is the RDFFT data with a range unit number greater than or equal to 200; the range unit number of the data elements in the above second radar data subset is the RDFFT data with a range unit number less than 200.

[0094] In the above step S2, the Doppler unit number matching the transmission phase offset parameter of the target radar object is obtained. As an optional implementation, for example, the transmission phase offset Δ of the second channel to the fourth channel relative to the first channel in the four transmitting antennas of the DDMA waveform is θ They are 84.375°, 140.625°, and 267.1875° respectively. The following formula is used to calculate the transmission phase offset Δ θ Calculate the corresponding Doppler unit number:

[0095]

[0096] Therefore, the Δ of the second to fourth channels relative to the first channel in the transmitting antenna can be obtained. θ_idx They are 120, 200, and 380 respectively, which are the cyclic translation parameters.

[0097] Further in steps S3-S4, a cyclic shift operation is performed on the first radar data subset according to the cyclic shift parameter indicated by the Doppler unit number to obtain a first reference data subset; and a plurality of data matrices included in the first reference data subset are spliced ​​according to the matrix splicing method indicated by the subarray dimension of the long-range virtual subarray to obtain a second radar data.

[0098] Optionally, for RDFFT data with a range unit number greater than or equal to 200, all transmitting antennas are used to participate in demodulation, that is, the RDFFT data is cyclically shifted in the Doppler dimension in sequence [0, 120, 200, 380], so that the echo signals of different transmitting antennas are aligned and then spliced ​​to form demodulated data. The above subarray dimension can be the virtual antenna array dimension formed by the transmitting and receiving antennas corresponding to the optimal array design selected after simulating different antenna placement positions and numbers, and the above splicing method can be specifically sequential splicing. The echo signals of different transmitting antennas corresponding to the above second radar data are aligned and spliced ​​to form demodulated data, and its dimension is 312×512×32, that is, there are 4*8=32 channels under the array design mode of 4 transmits and 8 receives.

[0099] Through the above implementation of the present application, the first radar data subset and the second radar data subset are determined from the first radar data according to the distance unit number; the Doppler unit number matching the transmission phase offset parameter of the target radar object is obtained; according to the cyclic shift parameter indicated by the Doppler unit number, the first radar data subset is subjected to a cyclic shift operation to obtain the first reference data subset; according to the matrix splicing method indicated by the subarray dimension of the long-range virtual subarray, the multiple data matrices included in the first reference data subset are spliced ​​to obtain the second radar data, and the data within different distance ranges are optimized in a targeted manner. For the first radar data subset (long-range target), by focusing on a specific Doppler unit number, redundant processing of full-spectrum data is avoided, and the use of computing resources is further optimized.

[0100] In an optional implementation, determining a target distance unit sequence number corresponding to the distance parameter includes:

[0101] S1, determining the target range unit number according to the ratio between the range parameter and the range resolution of the target radar object;

[0102] Get the Doppler unit number that matches the transmit phase offset parameters of the target radar object, including:

[0103] S2, determining a Doppler unit number according to a product of a transmission 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.

[0104] In the above step S1, the target range unit number is determined according to the ratio between the range parameter and the range resolution of the target radar object; alternatively, the target range unit number can be determined according to the formula R far_idx =R far / Δ r Determine, where the long-distance starting distance is R far Corresponding to the above distance parameter, Δ r The system distance resolution is designed according to system requirements.

[0105] In the above step S2, the Doppler unit number is determined according to the product between the transmit phase offset parameter and the first signal quantity parameter; alternatively, the Doppler unit number can be determined according to the formula Determine, where Δ θ is the transmission phase offset of the nth channel relative to the first channel in the DDMA waveform transmitting antenna. One processing cycle is one frame, and the number of chirps in one frame is M. D , which is the first signal quantity parameter mentioned above.

[0106] Through the above implementation method recorded in this application, the target distance unit number is determined according to the ratio between the distance parameter and the distance resolution of the target radar object, ensuring that the target is more accurately mapped in the distance dimension in the radar signal processing. This precise positioning helps to improve the accuracy of target detection and tracking; the Doppler unit number is determined according to the product between the transmission phase offset parameter and the first signal quantity parameter. After determining the target distance unit number and the Doppler unit number, the radar system can concentrate computing resources to process signals within a specific distance and Doppler range, avoiding redundant operations on the full-space signal and reducing computational complexity and data processing time.

[0107] In an optional implementation, after determining the first radar data subset and the second radar data subset from the first radar data according to the range unit sequence number, the method further includes:

[0108] S1, performing a cyclic shift operation on the second radar data subset according to the cyclic shift parameter indicated by the Doppler unit sequence number to obtain a second reference data subset;

[0109] S2, according to the matrix splicing method indicated by the subarray dimension of the close-range virtual subarray, splicing multiple data matrices included in the second reference data subset to obtain second close-range radar data, wherein the subarray dimension of the close-range virtual subarray is determined by the simulation operation performed on the target radar, and the second close-range radar data is used to perform object detection on a reference object, and the reference object is an object within the target distance indicated by the distance parameter in the target space area.

[0110] In the above steps S1-S2, a cyclic shift operation is performed on the second radar data subset according to the cyclic shift parameter indicated by the Doppler unit number to obtain a second reference data subset; and a plurality of data matrices included in the second reference data subset are spliced ​​according to the matrix splicing method indicated by the subarray dimension of the close-range virtual subarray to obtain the second close-range radar data.

[0111] Specifically, the long-range starting distance is set to 100m, and the corresponding distance unit number is calculated as 200 according to the distance resolution. The second to fourth channels in the transmitting antenna are Δ θ_idxFor example, the RDFFT data of the second transmitting antenna in the original transmitting array needs to be cyclically shifted by 120 units along the Doppler dimension. That is, the data of the original RDFFT data Doppler dimension unit number [0:511] is changed to [120:511,0:119]. The data corresponding to the third and fourth transmitting antennas are cyclically shifted by 200 and 380 units respectively to align the echo signals of different transmitting antennas, and then the dimensions of the receiving antenna Nr are sequentially extended to obtain the above-mentioned second short-range radar data, forming a demodulated data matrix with a dimension of 200 (distance dimension) × 512 (Doppler dimension) × 24 (angle dimension). Since the number of transmitting antennas can be reduced within the short range, for example, the first transmitting antenna is reduced, that is, the array design of 3 transmitting and 8 receiving has 3*8=24 channels; in this embodiment, for example, one channel corresponds to one angle for data processing, and the number of angle dimensions corresponding to 24 channels is 24.

[0112] Since the distance dimension refers to the number of distance units covered by the processed data, different distance unit numbers can be used to represent different straight-line distances between the target and the radar. In the case of close range, since the target is relatively close, the radar system does not need to detect beyond the set distance. Therefore, according to the long-range starting value, the distance unit number 200 is determined as the boundary distance through calculation. In the case of close range, the distance unit numbers 1-200 (i.e., the distance unit numbers corresponding to within 100m) are covered, totaling 200 distance units. In the case of long range, the distance unit numbers 201 to 512 (i.e., the distance unit numbers corresponding to beyond 100m) are covered, totaling 312 distance units. It can be understood that the subarray dimension of the above-mentioned close-range virtual subarray can be formed by reducing the number of channels staggered by N pitch layers on the basis of the number of transmitting antennas initially designed, and can be the dimension corresponding to the array design with the best effect selected through simulation, such as reducing the subarray dimension formed by the first transmitting antenna. In this embodiment, the above-mentioned reference object can be a target detection point within 100m.

[0113] In an optional implementation, determining a target angle unit serial number interval corresponding to the angle interval parameter, and determining target radar data according to the target angle unit serial number interval and the second radar data, includes:

[0114] S1, arranging the second radar data according to the virtual array channels, and performing a fast Fourier transform operation on the arranged second radar data in the azimuth dimension according to the first number of points to obtain long-range three-dimensional radar data;

[0115] S2, 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 within the target angle unit sequence number interval;

[0116] S3, determining the long-range three-dimensional data subset as target radar data.

[0117] In the above step S1, the second radar data is arranged according to the virtual array channels, and a fast Fourier transform operation is performed on the arranged second radar data in the azimuth dimension according to the first number of points to obtain long-range three-dimensional radar data;

[0118] As an optional implementation, for example, for RDFFT data with a range unit number greater than or equal to 200, all transmitting antennas are used to participate in demodulation, that is, the RDFFT data is sequentially cyclically shifted [0, 120, 200, 380] in the Doppler dimension and then spliced ​​to form demodulated data, whose dimension is 312×512×32, and further according to the first point number (specifically, the azimuth dimension FFT point number) to obtain the long-range three-dimensional radar data, specifically, the long-range transmission demodulated data is arranged according to the virtual array channel, and the azimuth dimension FFT point number M is performed. A =64, thus forming an RDA 3D data matrix Ω of size 312×512×64. The specific number of azimuth dimension FFT points needs to be determined according to the design position of the antenna and actual needs. This is only an example.

[0119] In a way like Figure 4 The following is an example of how to select the number of FFT points in the azimuth dimension for a 4-transmit 4-receive array design: The specific positions of the transmitting antenna and the receiving antenna are as follows: Figure 4 As shown in the coordinate system, the MIMO POS has 4*4=16 channels, and the positions of the channels are as follows: Figure 4 The position of the marker point in the MIMO POS coordinate system, the number of FFT points in the azimuth dimension can be the width of the mimo pos, 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. 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.

[0120] Further in steps S2-S3, a long-range three-dimensional data subset is determined from the long-range three-dimensional radar data according to the target angle unit sequence number interval; and the long-range three-dimensional data subset is determined as the target radar data.

[0121] Optionally, the target angle unit number interval can be obtained according to the angle range of interest, for example, setting the long-range angle range of interest θ pro ∈[-20°~20°], and the above steps set the number of FFT points in the azimuth dimension M A=64, and then the range of the long-range angle dimension processing unit serial numbers is calculated to be 1 / n of the original processing range. Taking 1 / 3 as an example, the size of the RDA3-dimensional data Ω' used for long-range target detection is 312×512×23 (approximately 1 / 3 of 64), which is the above-mentioned target radar data. It can be understood that due to the reduction in the number of angle-restricted channels, the range of the long-range angle dimension processing unit serial numbers corresponds, that is, each channel corresponds to an angle dimension serial number, which reduces the number of processes and improves the processing efficiency.

[0122] In an optional implementation, when determining the target angle unit serial number interval corresponding to the angle interval parameter, and determining the target radar data according to the target angle unit serial number interval and the second radar data, it also includes:

[0123] S1, obtaining at least one angle boundary value in the angle interval parameter;

[0124] S2, determining a first reference value corresponding to each of the at least one angle boundary value according to half of the product between the sine value of each of the at least one angle boundary value and the first point number;

[0125] S3, determining at least one angle unit boundary number according to a modulo result between at least one first reference value and the first point number;

[0126] S4, determining a target angle unit sequence number interval according to at least one angle unit boundary sequence number.

[0127] Optionally, the target angle unit number interval can be expressed as:

[0128] Calculated, where ceil(·) means rounding up. mod(x,A) means taking x modulo A. The above angle interval parameters can be determined according to the function of the radar and the installation location of the radar. For example, it is divided into corner radar and front radar. The angle range corresponding to the corner radar is relatively large and can generally be plus or minus 90 degrees, and the angle range corresponding to the front radar is plus or minus 60 degrees. No specific limitation is made here.

[0129] The above steps S1-S4 are described with a complete implementation method: for example, the angle range θ of interest at a long distance is set. pro ∈[-20°~20°], corresponding to the above angle interval parameters, the boundary value and the middle value of the range can be determined as the angle boundary value, that is, the sequence boundary values ​​corresponding to [-20°~0°] and [0°~20°] are determined, and the number of FFT points M in the azimuth dimension is set according to the above steps. A =64 (i.e. the first point number), and then calculate the long-distance angle dimension processing unit number range θ pro_idx ∈[0:11,53:63].

[0130] Therefore, the size of the RDA3-dimensional data Ω' used for long-range target detection is 312×512×23, which is the above-mentioned target radar data. It can be understood that due to the reduction in the number of angle-restricted channels, the long-range angle-dimension processing unit number range corresponds, that is, each channel corresponds to an angle-dimension number, which reduces the number of processes and improves the processing efficiency.

[0131] In an optional implementation, after obtaining the second short-range radar data, the method further includes:

[0132] S1, arranging the second short-range radar data according to the virtual array channels, and performing a fast Fourier transform operation on the arranged second short-range radar data in the azimuth dimension according to the second number of points to obtain short-range three-dimensional radar data;

[0133] S2, performing object detection operation based on the close-range 3D radar data.

[0134] In the above step S1, the second short-range radar data is arranged according to the virtual array channels, and the fast Fourier transform operation is performed on the arranged second short-range radar data in the azimuth dimension according to the second number of points to obtain short-range three-dimensional radar data. The above second number of points is the number of azimuth dimension FFT points corresponding to the antenna array design in the short-range case.

[0135] As an optional implementation, the dimension of the demodulated data matrix is ​​200×512×24, and the demodulated data is further transmitted at close range and arranged according to the virtual array channels, and the azimuth FFT point number M is performed. A =48, forming an RDA 3D data matrix Ω of size 200×512×48. And Ω'=Ω.

[0136] In the above step S2, an object detection operation is performed according to the short-range 3D radar data. For example, taking a target at a distance of 20 meters, a speed of 10 meters per second, and an angle of 10 degrees relative to the radar coordinate system as an example: after performing a CA-CFAR hypothesis test on the detection matrix Ω', the target point distance unit R is obtained. t =40, Doppler unit D t =22, angle unit A t =4, the target point information to be detected is obtained by the following formula: Target estimated distance = R t ×Δ r =20 (meters); target estimated speed = D t ×Δ d =9.9 (meters per second); This completes the output of target point information.

[0137] In an optional implementation, determining a distance parameter for detecting a distant object includes:

[0138] S1, obtain the height estimation parameters of the target object;

[0139] S2, determining a pitch angle corresponding to each of the plurality of candidate object distances according to the height estimation parameter and the plurality of candidate object distances;

[0140] S3, 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 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;

[0141] S4: Determine a distance parameter according to at least one reference simulation result that satisfies the first constraint condition.

[0142] In the above steps S1-S2, a height estimation parameter of the target object is obtained; and a pitch angle corresponding to each of the plurality of candidate object distances is determined according to the height estimation parameter and the plurality of candidate object distances;

[0143] Alternatively, if Figure 5 As shown in the figure, it is a schematic diagram of the pitch angle of the target object at a height of -1m (lower line) and 10m (upper line) at different distances. It can be seen that the pitch angle gradually tends to be flat (0°) near the critical points of different distances, that is, it can be determined that for target objects at different heights, there are respectively matching distance critical points, that is, the long-distance starting values ​​corresponding to target objects at different heights can be determined respectively.

[0144] 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 pitch angles; Figure 6 , Figure 7 The 15m height target was used to conduct the angle measurement error impact analysis and the main-sidelobe ratio impact analysis. Figure 6 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. Figure 7 In the coordinate system, the horizontal axis x represents the distance, the vertical axis z represents the main lobe to side lobe ratio, and the parameter y represents the azimuth angle. Figure 6 It can be seen that the error influence tends to be stable after the distance of 270m, and 270m can be used as the critical value for distance judgment; Figure 7 It can be seen that the error influence tends to be stable after the distance of 90m, and 90m can be used as the critical value for distance judgment.

[0145] In the above step S4, the distance parameter is determined according to at least one reference simulation result that satisfies the first constraint condition. The first constraint condition can be a weight value that matches the angle measurement error value and the main-sidelobe ratio change rate determined according to different design requirements, that is, the distance parameter value can be determined jointly according to the above influencing factors. For example, the two conditions are combined to determine that 270m is the distance critical value, and within 270m is the close range. Or it can be determined that the main-sidelobe ratio is the main factor, and 90m is determined as the critical value.

[0146] By acquiring a height estimation parameter of a target object; determining the pitch angles corresponding to the respective distances of the multiple candidate objects according to the height estimation parameter and the distances of the multiple candidate objects; acquiring at least one reference simulation result according to the reference radar array information and the multiple pitch angles when at least one reference radar array information is acquired; determining a distance parameter according to at least one reference simulation result satisfying a first constraint condition; and by accurately and reasonably determining the distance of the long-distance starting point, the accuracy of long-distance processing is improved.

[0147] In an optional implementation, determining an angle interval parameter for detecting a distant object includes:

[0148] S1, determining a functional area for detecting the target object according to the type of the target radar object;

[0149] S2, determining the angle interval parameter according to the distance parameter and the functional area.

[0150] In the above step S1, the functional area for detecting the target object is determined according to the type of the target radar object; the types of the above target radar objects include but are not limited to corner radars and front radars. The angle range corresponding to the corner radar is relatively large and can generally be plus or minus 90 degrees, and the angle range corresponding to the front radar is plus or minus 60 degrees, etc., and no specific limitation is made here.

[0151] Further in step S2, the angle interval parameter is determined according to the distance parameter and the functional area. Specifically, for example, the forward-looking radar may need to cover a wide angle range of -30 degrees to +30 degrees in the first area to capture all close targets; while in the second area, it may only need to focus on a narrow angle range of -10 degrees to +10 degrees. The first area may be a closer location area than the second area, for example, the first area is in the range of 100-200, and the second area is in the range of 200-300. This is only an example.

[0152] Through the above-mentioned implementation methods recorded in the present application, the functional area for detecting the target object is determined according to the type of the target radar object; the angle interval parameter is determined according to the distance parameter and the functional area; it can help the radar system optimize resource allocation, such as energy and processing power, to ensure sufficient detection capability in key areas, improve the angle estimation accuracy of the target, and thus enhance the target recognition capability.

[0153] In an optional implementation, after determining the distance parameter and the angle interval parameter for detecting the long-distance object, the method further includes:

[0154] S1, obtaining at least one reference radar array information;

[0155] S2, acquiring target simulation results corresponding to at least one reference radar array information, a distance parameter, and an angle interval parameter, wherein the target simulation results include a main-sidelobe ratio parameter;

[0156] S3, determining target radar array information from at least one reference radar array information according to the target simulation result, wherein the target radar array information is used for array parameters of the target radar object.

[0157] In the above step S1, obtaining at least one reference radar array information can be determined according to design requirements, such as detection distance, angle coverage, performance indicators (angle resolution, angle measurement accuracy, etc.) and detection target type. The above radar array information includes but is not limited to the number of receiving antennas, the number of transmitting antennas, antenna formation, DDMA waveform parameters, processing cycle and other information.

[0158] In the above step S2, according to at least one reference radar array information, the distance parameter and the angle interval parameter, the target simulation results respectively corresponding to the at least one reference radar array information are obtained.

[0159] In such Figure 4 In the 4-transmit 4-receive radar antenna layout shown in the figure, the minimum number of channels used is determined to be 14. The angle-dimensional spectrum is obtained by simulating any combination as follows: Figure 8 As shown, the main lobe ratio within the selected FOV is calculated, and the schematic diagram is as follows Fig. 9 As shown, further select the optimal sub-array as Fig.10 The thick lines mark the corresponding subarrays.

[0160] Further in the above step S3, the target radar array information is determined from at least one reference radar array information according to the target simulation result.

[0161] As an optional implementation, for example, there are array combinations A, B, and C, where array combination A includes subarrays a1, a2, and a3. Subarray a1 uses a specific antenna layout. When detecting long-range targets, its radiation energy in the main lobe direction is relatively strong, but the side lobes also have a certain energy distribution; subarrays a2 and a3 have different antenna layouts and have their own radiation characteristics; array combination B is composed of subarrays b1, b2, and b3. Subarray b1 uses another antenna arrangement method, and its main lobe has a high energy concentration in the direction of the long-range target, and the side lobe energy is relatively low; subarrays b2 and b3 are also designed to optimize the signal reception of long-range targets, but they are different from the characteristics of subarray b1; array combination C includes subarrays c1, c2, and c3. The antenna layout of subarray c1 focuses on improving signal gain within a specific angle range, and its main lobe side lobe ratio shows certain characteristics; subarrays c2 and c3 work together in the entire array combination to meet the needs of long-range target detection.

[0162] For the subarray a1 in the array combination A, through simulation or theoretical calculation, its main lobe radiation energy is EA, and the side lobe radiation energy is Ea1, then the main-side lobe ratio Ra1=EA / Ea1, and the main-side lobe ratio of each subarray is calculated based on the same method.

[0163] For example, in array combination A, Ra2 is the maximum value, in array combination B, Rb1 is the maximum value, and in array combination C, Rc3 is the maximum value. Further comparison of Ra2, Rb1, and Rc3, if Rb2 is the largest, array 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-sidelobe ratio, multiple factors need to be considered, such as antenna performance, target height distribution, long-range FOV requirements, signal-to-noise ratio, etc.

[0164] The complete implementation method of long-range array is to analyze the height distribution of targets in the range of 0 to 300 meters and determine that the change of target height at a distance of 100 meters has little effect on the azimuth angle measurement, so the long-range and short-range segmentation threshold is set to 100 meters.

[0165] Analyze the long-range functional area that the radar needs to cover, such as setting it to cover 180 degrees in front to meet the needs of multi-lane target detection. Calculate the FOV of the long-range segment (100 meters to the maximum detection distance) to ensure that the required detection area can be covered within the long-range segment.

[0166] Evaluate the signal-to-noise ratio and main-sidelobe ratio when using 1 to 3 of the 4 transmitting antennas as subarrays in the long-range segment (greater than or equal to 100 meters). Assume that when using 2 transmitting antennas as subarrays, the signal-to-noise ratio meets the minimum requirement and the main-sidelobe ratio reaches the optimal value, so the subarray configuration with 2 transmitting antennas is selected as the optimal subarray.

[0167] Based on the optimal subarray selected in the previous step, the main-sidelobe ratios under different configurations were further compared, and finally the subarray configuration using two transmitting antennas was confirmed as the main array configuration for long-range target detection. This ensures that in long-range detection, the radar system can maintain a high signal-to-noise ratio and a high main-sidelobe ratio while reducing the amount of calculation, thereby improving the accuracy and efficiency of target detection.

[0168] Flowchart Fig.11 The above process is described in detail:

[0169] S1102, array design that meets system requirements;

[0170] Traverse each array and execute S1104 to evaluate the distance segmentation; S1106 to evaluate the long-range FOV; S1108 to evaluate the optimal subarray.

[0171] Specifically, S1104, the evaluation distance segment includes: S1104-1, confirming the target distribution height; S1104-2, calculating the pitch angle distribution of targets at different distances; S1104-3, simulating the influence of the pitch angle on the azimuth measurement at different distances; S1104-4, screening the distance where the azimuth measurement error and the main-sidelobe ratio change are within a reasonable range; that is, this item is evaluated based on the target height distribution range and the influence of the pitch channel on the azimuth measurement.

[0172] S1106, evaluating the long-range FOV includes: S1106-1, confirming the functional area according to the radar type; S1106-2, confirming the long-range FOV in combination with the distance segment value; that is, calculating the FOV according to the radar functional area and the long-range distance segment.

[0173] S1108, evaluating the optimal subarray includes: S1108-1, traversing all arrays that meet the system requirements; S1108-2, setting the minimum number of virtual channels used; S1108-3, each array selects a subarray according to the minimum number of channels used; S1108-4, the subarray meets the high main-sidelobe ratio requirement in the long-distance main FOV; if the requirements are met, execute S1108-5, record the number of channels used and the main-sidelobe ratio of the current subarray; S1108-6, obtain the optimal subarray of the number of channels and the main-sidelobe ratio; S1108-7, record the current array and the optimal subarray; that is, consider the signal-to-noise ratio to set the minimum number of MIMO channels used, and select the subarray that meets the requirements according to the high main-sidelobe ratio requirement of the long-distance main FOV subarray.

[0174] S1110, traverse all group array + sub-array combinations, and select the sub-array combination with the highest main-sidelobe ratio;

[0175] S1112, final formation.

[0176] The following process Fig.12 An overall description of this plan:

[0177] S1202, complete antenna and DDMA waveform design according to radar system performance requirements;

[0178] S1204, determining the long-range starting position, the short-range virtual sub-array size, and the long-range angle range;

[0179] S1206, performing signal processing on the original echo data to complete target detection;

[0180] Specifically, S1, according to the performance requirements of the radar system, complete the radar antenna and waveform design, and the transmission channel transmits DDMA waveforms with different phase changes. Including the number of MIMO antenna receiving array elements Nr and the number of transmitting antennas Nt. The phase offset Δ corresponding to the transmitting antenna under the DDMA system θ The number of chirps in the processing cycle M D and the number of fast time sampling points M for each chirp R . Determine the system distance resolution Δ r , velocity resolution Δ d .

[0181] For example: Design radar antenna parameters: number of receiving array elements = 8, number of transmitting antennas = 4, and the dimension of the virtual array = 8*4 = 32. DDMA waveform: The transmission phase offset of the second to fourth channels relative to the first channel among the four transmitting antennas is Δ θ They are 84.375°, 140.625°, and 267.1875° respectively. One processing cycle is one frame, the number of chirps in one frame = 512, and the number of fast time sampling points of each chirp = 512. The system distance resolution is 0.5 meters, and the speed resolution is 0.45 meters per second.

[0182] S2, determine the signal processing long-distance starting position R far . Evaluate and calculate the short-range transmission subarray size Nt' that meets the system requirements, and select the angle range θ of interest for long-range target detection processing based on functional requirements. pro , forming a spatial subdomain.

[0183] For example, the long-range starting distance is set to 100 meters, and the transmitting subarray used for short-range processing selects the 2nd to 4th transmitting array elements, that is, Nt'=3. The size of the virtual subarray formed is 8*3=24; Taking the common front radar as an example, the angle range of interest for long-range is set to θ pro ∈[-20°~20°].

[0184] S3, down-convert the radar echo data, and obtain the original echo data after completing the digital-to-analog conversion. The original echo data enters the signal processing link for target detection processing.

[0185] S3-1, after performing range dimension FFT on the fast time sampling points of the original echo data, Doppler FFT in the chirp dimension is performed to obtain range Doppler FFT (RDFFT) data.

[0186] S3-2, the following formula can be used to calculate the transmission phase offset Δ θ Calculate the corresponding Doppler unit number:

[0187]

[0188] Calculate R based on distance accuracy far The corresponding distance dimension unit number R far__idx The formula is as follows:

[0189] R far_idx =R far / Δ r .

[0190] By R far_idx Determine the distance range of the RDFFT data involved in the processing, and calculate the RDFFT data of different distance ranges according to Δ θ_idx Doppler demodulation of different transmitting sub-arrays is performed to obtain demodulated data.

[0191] S3-3, the demodulated data is subjected to angle-dimensional coherent processing, and after being arranged according to the virtual array channels, the angle-dimensional FFT generates a three-dimensional data matrix Ω of range, Doppler, and angle (RDA).

[0192] S3-4, by the angle range of interest θ pro Calculate the angle unit number θ corresponding to the azimuth dimension FFT pro_idx The formula is as follows:

[0193]

[0194] Where ceil(·) means rounding up. mod(x,A) means taking x modulo A.

[0195] Therefore, different angle ranges can be selected according to different distance information to obtain the corresponding spatial subdomain RDA 3-dimensional data matrix Ω'.

[0196] S3-5, perform target detection on the RDA 3D data matrix Ω' to obtain the target point distance, speed, and angle unit information R t , D t , A t The target distance, speed, and angle estimates can be calculated using the following formula:

[0197] Estimated target distance = R t ×Δ r ; Target estimated speed = Dt ×Δ d ;

[0198] Thereby completing the output of target point trace information.

[0199] The above step S3 is described in a specific implementation manner:

[0200] The size of the received original echo data is 512×512×8. The data is processed for target detection. The specific steps are as follows:

[0201] After performing range-dimensional FFT and Doppler-dimensional FFT on the eight receiving channels of the original echo data, the range unit range of the RDFFT data is [0,511], and the Doppler unit range is [0,511], that is, the RDFFT data dimension is 512×512×8.

[0202] The transmit phase offset Δ is calculated according to the following formula θ Calculate the corresponding Doppler unit number:

[0203]

[0204] Therefore, the Δ of the second to fourth channels relative to the first channel in the transmitting antenna can be obtained. θ_idx They are 120, 200 and 380 respectively.

[0205] The formula for calculating the corresponding distance unit number from the distance resolution is:

[0206] R far_idx =R far / Δ r , and then get R far_idx =200.

[0207] For data with a range unit number less than 200, the Doppler transmit demodulation operation is as follows:

[0208] The RDFFT data corresponding to the second transmitting antenna in the original transmitting array is circularly shifted by 120 units along the Doppler dimension. That is, the data of the original RDFFT data Doppler dimension unit number [0:511] becomes [120:511,0:119]. The data corresponding to the third and fourth transmitting antennas are circularly shifted by 200 and 380 units respectively and then sequentially concatenated with the receiving antenna Nr dimension, forming a demodulated data matrix with a dimension of 200×512×24.

[0209] For RDFFT data with range unit numbers greater than or equal to 200, all transmitting antennas are used to participate in demodulation, that is, the RDFFT data is cyclically shifted [0, 120, 200, 380] in the Doppler dimension and then concatenated to form demodulated data with a dimension of 312×512×32.

[0210] The demodulated data after close transmission is further arranged according to the virtual array channel, and the azimuth dimension FFT point number M is performed. A =48, forming an RDA 3D data matrix Ω of size 200×512×48. And Ω'=Ω.

[0211] The demodulated data of the long-distance transmission is arranged according to the virtual array channel, and the azimuth dimension FFT point number M is performed. A =64, thus forming an RDA 3D data matrix Ω of size 312×512×64.

[0212] By formula Calculate the long-distance angle dimension processing unit number range θ pro_idx ∈[0:11,53:63].

[0213] Therefore, the size of the RDA 3D data Ω' used for close-range target detection is 200×512×48, and the size of the RDA 3D data Ω' used for long-range target detection is 312×512×23.

[0214] According to different distance units, the corresponding RDA 3D data Ω' is used for target detection. Take a target with a distance of 20 meters, a speed of 10 meters per second, and an angle of 10 degrees relative to the radar coordinate system as an example:

[0215] After CA-CFAR hypothesis test on the detection matrix Ω', the target point distance unit R is obtained. t =40, Doppler unit D t =22, angle unit A t =4, the target point information to be detected is obtained by the following formula:

[0216] Estimated target distance = R t ×Δ r =20 (meters); target estimated speed = D t ×Δ d =9.9 (meters per second); This completes the output of target point information.

[0217] The above process is shown in the flowchart Fig.13 As shown:

[0218] S1302, performing range and Doppler dimension FFT on the original echo data to obtain RDFFT data;

[0219] S1304, performing distance judgment on the RDFFT data;

[0220] In the case of close range, S1304-1 is executed to complete transmit Doppler dimension demodulation according to the close range virtual sub-array;

[0221] In the long-distance case, S1304-2 is executed to complete transmit Doppler dimension demodulation according to the long-distance virtual sub-array;

[0222] S1306, after completing the angle dimension FFT, the RDA 3-dimensional data matrix Ω is obtained;

[0223] S1308, performing distance judgment on the RDA 3-dimensional data matrix Ω;

[0224] In the case of close range, S1308-1 is executed to perform target detection on the close range data matrix Ω';

[0225] In the long-distance case, S1308-2 is executed to perform target detection on the long-distance data matrix Ω';

[0226] Finally, S1310 is executed to detect the target and output the traces;

[0227] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0228] According to another aspect of the embodiment of the present application, a radar data processing device for implementing the above radar data processing method is also provided. Fig.14 As shown, the device comprises:

[0229] A first determining unit 1402 determines a distance parameter and an angle interval parameter for detecting a distant object;

[0230] The second determining unit 1404 determines the target distance unit sequence number corresponding to the distance parameter when first radar data matching the target spatial region is acquired, wherein the first radar data is obtained by performing a fast Fourier transform operation on the target echo data, and the target echo data is echo data received by the target radar object and matching the target spatial region;

[0231] The acquisition unit 1406 performs a Doppler transmission demodulation operation on the first radar data according to the target distance unit sequence number to obtain second radar data;

[0232] The third determination unit 1408 determines the target angle unit serial number interval corresponding to the angle interval parameter, and determines the target radar data from the second radar data according to the target angle unit serial number interval, wherein the target radar data is used to detect the target object in the target space area, and the target object is an object outside the target distance indicated by the distance parameter in the target space area.

[0233] Optionally, the acquisition unit 1406 is further configured to determine a first radar data subset and a second radar data subset from the first radar data according to the range unit number, wherein the range unit number of the data elements in the first radar data subset is greater 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 less than the target range unit number; obtain a Doppler unit number that matches the transmit phase offset parameter of the target radar object; perform a cyclic shift operation on the first radar data subset according to the cyclic shift parameter indicated by the Doppler unit number to obtain a first reference data subset; and splice multiple data matrices included in the first reference data subset according to a matrix splicing method indicated by a subarray dimension of a long-range virtual subarray to obtain second radar data, wherein the subarray dimension of the long-range virtual subarray is determined by a simulation operation performed on the target radar.

[0234] Optionally, the radar data processing device further includes a fourth determination module, which is used to determine the target range unit number based on the ratio between the range parameter and the range resolution of the target radar object; and to determine the Doppler unit number based on the product between the transmission phase offset parameter and the 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.

[0235] Optionally, the acquisition unit 1406 further includes a matrix processing module, which is used to perform a cyclic shift operation on the second radar data subset according to the cyclic shift parameter indicated by the Doppler unit sequence number to obtain a second reference data subset; and to splice multiple data matrices included in the second reference data subset according to a matrix splicing method indicated by a subarray dimension of a close-range virtual subarray to obtain second close-range radar data, wherein the subarray dimension of the close-range virtual subarray is determined by a simulation operation performed on the target radar, and the second close-range radar data is used to perform object detection on a reference object, and the reference object is an object within the target distance indicated by the distance parameter in the target space area.

[0236] Optionally, the third determination unit 1408 includes a fifth determination module, which is used to arrange the second radar data according to the virtual array channel, and perform a fast Fourier transform operation on the arranged second radar data in the azimuth dimension according to the first number of points to obtain long-range three-dimensional radar data; according to the target angle unit sequence number interval, determine a long-range three-dimensional data subset from the long-range three-dimensional radar data, wherein the angle unit sequence numbers of the data elements included in the long-range three-dimensional data subset are within the target angle unit sequence number interval; and determine the long-range three-dimensional data subset as the target radar data.

[0237] Optionally, the fifth determination module is also used to obtain at least one angle boundary value in the angle interval parameter; determine the first reference value corresponding to each of the at least one angle boundary values ​​according to half of the product between the sine value of each of the at least one angle boundary values ​​and the first point number; determine at least one angle unit boundary number according to the modulo result between at least one first reference value and the first point number; and determine the target angle unit boundary number interval according to at least one angle unit boundary number.

[0238] Optionally, the above-mentioned matrix processing module includes an execution module for arranging the second short-range radar data according to the virtual array channel, and performing a fast Fourier transform operation on the arranged second short-range radar data in the azimuth dimension according to the second number of points to obtain short-range three-dimensional radar data; and performing an object detection operation based on the short-range three-dimensional radar data.

[0239] Optionally, the first determination unit 1402 is further used to obtain a height estimation parameter of the target object; determine the pitch angle corresponding to each of the multiple candidate object distances based on the height estimation parameter and the multiple candidate object distances; when at least one reference radar array information is obtained, obtain at least one reference simulation result based on the reference radar array information and the multiple 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; determine the distance parameter based on at least one reference simulation result that satisfies the first constraint condition.

[0240] Optionally, the first determining unit 1402 is further configured to determine a functional area for detecting the target object according to the type of the target radar object; and to determine an angle interval parameter according to the distance parameter and the functional area.

[0241] Optionally, the radar data processing device further includes a second acquisition module, which is used to acquire at least one reference radar array information; based on at least one reference radar array information, a distance parameter and an angle interval parameter, a target simulation result corresponding to the at least one reference radar array information is acquired, wherein the target simulation result includes a main-sidelobe ratio parameter; based on the target simulation result, the target radar array information is determined from the at least one reference radar array information, wherein the target radar array information is used for the array parameters of the target radar object.

[0242] For a specific embodiment, reference may be made to the example shown in the above radar data processing method, which will not be described in detail in this example.

[0243] Among them, the memory 1502 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 embodiment of the present invention. The processor 1504 executes various functional applications and data processing by running the software programs and modules stored in the memory 1502, that is, realizing the above-mentioned radar data processing method. The memory 1502 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 memory, or other non-volatile solid-state memory. In some instances, the memory 1502 may further include a memory remotely located relative to the processor 1504, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. Among them, the memory 1502 can be specifically, but not limited to, used to store file information such as target files. As an example, such as Fig.15 As shown, the memory 1502 may include, but is not limited to, the first determination unit 1402, the second determination unit 1404, the acquisition unit 1406, and the third determination unit 1408 in the radar data processing device. In addition, other module units in the radar data processing device may also be included but are not limited to, which will not be repeated in this example.

[0244] Optionally, the transmission device 1506 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 1506 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices and routers via a network cable so as to communicate with the Internet or a local area network. In one example, the transmission device 1506 is a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0245] In addition, the electronic device further includes: a display 1508, and a connection bus 1510, which is used to connect various module components in the electronic device.

[0246] According to one aspect of the present application, a computer program product is provided, the computer program product comprising a computer program / instruction, the computer program / instruction comprising a program code for executing the method shown in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through a 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.

[0247] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0248] It should be noted that the computer system of the electronic device is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0249] In particular, according to an embodiment of the present application, the process described in each method flow chart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer readable medium, and the computer program contains a program code for executing the method shown in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through a 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.

[0250] According to one aspect of the present application, a computer-readable storage medium is provided, and 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 methods provided in the above-mentioned various optional implementations.

[0251] Optionally, in this embodiment, the computer-readable storage medium may be configured to store a computer program for performing the following steps:

[0252] S1, determining a distance parameter and an angle interval parameter for detecting a distant object;

[0253] S2, when first radar data matching the target spatial region is obtained, determining a target distance unit 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 matching the target spatial region received by the target radar object;

[0254] S3, performing a Doppler transmission demodulation operation on the first radar data according to the target range unit sequence number to obtain second radar data;

[0255] S4, determining a target angle unit serial number interval corresponding to the angle interval parameter, and determining target radar data from the second radar data according to the target angle unit serial number interval, wherein the target radar data is used to detect a target object in a target space area, and the target object is an object outside a target distance indicated by a distance parameter in the target space area.

[0256] Optionally, in this embodiment, a person of ordinary skill in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing hardware related to the electronic device through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0257] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0258] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling one or more computer devices (which can be personal computers, servers or network devices, etc.) to execute all or part of the steps of the methods of each embodiment of the present application.

[0259] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0260] In the several embodiments provided in 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 schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0261] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0262] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0263] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for processing radar data, characterized in that: include: Determining distance parameters and angle interval parameters for detecting distant objects; 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; Performing a Doppler transmission demodulation operation on the first radar data according to the target distance unit sequence number to obtain second radar data; Determine a target angle unit serial number interval corresponding to the angle interval parameter, and determine target radar data from the second radar data according to the target angle unit serial number interval, wherein the target radar data is used to detect a target object in the target space area, and the target object is an object outside the target distance indicated by the distance parameter in the target space area.

2. The method according to claim 1, characterized in that The performing a Doppler transmission demodulation operation on the first radar data according to the target distance unit sequence number to obtain the second radar data comprises: Determine a first radar data subset and a second radar data subset from the first radar data according to the range unit sequence number, wherein the range unit sequence number of the data elements in the first radar data subset is greater than or equal to the target range unit sequence number, and the range unit sequence number of the data elements in the second radar data subset is less than the target range unit sequence number; 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; The second radar data is obtained by splicing a plurality of data matrices included in the first reference data subset according to a matrix splicing mode indicated by a subarray dimension of a long-range virtual subarray, wherein the subarray dimension of the long-range virtual subarray is determined by a simulation operation performed on the target radar.

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 determining the first radar data subset and the second radar data subset from the first radar data according to the range unit sequence number, the method further includes: performing a cyclic shift operation on the second radar data subset according to the cyclic shift parameter indicated by the Doppler unit sequence number to obtain a second reference data subset; According to the matrix splicing mode indicated by the subarray dimension of the close-range virtual subarray, multiple data matrices included in the second reference data subset are spliced ​​to obtain second close-range radar data, wherein the subarray dimension of the close-range virtual subarray is determined by a simulation operation performed on the target radar, and the second close-range radar data is used to perform object detection on a reference object, and the reference object is an object within the target distance indicated by the distance parameter in the target space area.

5. The method according to claim 1, characterized in that The step of determining an angle unit sequence number interval corresponding to the angle interval parameter, and determining target radar data from the second radar data according to the angle unit sequence number interval, comprises: Arranging the second radar data according to the virtual array channels, and performing a fast Fourier transform operation on the arranged second radar data in the azimuth dimension according to the first number of points 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 the target radar data.

6. The method according to claim 5, characterized in that The determining of the target angle unit sequence number interval corresponding to the angle interval parameter comprises: Obtaining at least one angle boundary value in the angle interval parameter; Determine a first reference value corresponding to each of the at least one angle boundary value according to half of the product between the sine value of each of the at least one angle boundary value and the first point number; Determine at least one angle unit boundary number according to a modulo result between at least one of the first reference values ​​and the first number of points; The target angle unit number interval is determined according to at least one of the angle unit boundary numbers.

7. The method according to claim 5, characterized in that The step of determining an angle unit sequence number interval corresponding to the angle interval parameter, and determining target radar data from the second radar data according to the angle unit sequence number interval, comprises: Arranging the virtual array channels, and performing a fast Fourier transform operation on the arranged data in the azimuth dimension according to a second number of points to obtain close-range three-dimensional radar data; An object detection operation is performed based on the close-range three-dimensional radar data.

8. The method according to claim 1, characterized in that The determining of a distance parameter for detecting a long-distance object comprises: Obtaining height estimation parameters of the target 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; 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 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; The distance parameter is determined according to the at least one reference simulation result that satisfies the first constraint condition.

9. The method according to claim 1, characterized in that: Determine the angle interval parameters used to detect distant objects, including: Determining a functional area for detecting the target object according to the type of the target radar object; The angle interval parameter is determined according to the distance parameter and the functional area.

10. The method according to any one of claims 8 to 9, characterized in that After determining the distance parameter and the angle interval parameter for detecting the distant object, it also 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 for array parameters of the target radar object.

11. A radar data processing device, characterized in that: include: A first determination unit determines a distance parameter and an angle interval parameter for detecting a distant object; a second determining unit, 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; an acquisition unit, performing a Doppler transmission demodulation operation on the first radar data according to the target distance unit sequence number to obtain second radar data; A third determination unit determines a target angle unit serial number interval corresponding to the angle interval parameter, and determines target radar data from the second radar data according to the target angle unit serial number interval, wherein the target radar data is used to detect a target object in the target space area, and the target object is an object outside 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.

Images