Optimized signal processing method for two-dimensional planar array antenna of vehicle-mounted point cloud imaging radar

Abstract

This invention discloses an optimized signal processing method for a two-dimensional area array antenna of a vehicle-mounted point cloud imaging radar, belonging to the field of radar signal optimization. The specific steps of the signal processing method are as follows: (1) Determine the radar system configuration; (2) Optimize and adjust the positions of the transmitting and receiving antennas; (3) Determine and process the snapshot data; (4) Accumulate and detect each group of channels; (5) Perform data interpolation on the two-dimensional antenna array. This invention can provide design criteria for the design of two-dimensional area array antenna arrays, maximize the aperture of the two-dimensional antenna array, and significantly increase the number of antenna channels, significantly reduce the sidelobe amplitude during angle measurement, improve the angle measurement resolution and accuracy, and reduce the generation of false targets.

Description

Technical Field

[0001] This invention relates to the field of radar signal optimization, and more particularly to a method for optimizing the signal processing of a two-dimensional array antenna for vehicle-mounted point cloud imaging radar. Background Technology

[0002] Millimeter-wave radar is the only sensor with all-weather capability and is an essential perception unit for autonomous driving systems. Traditional automotive millimeter-wave radar can only detect horizontal position and velocity information, and cannot measure target pitch and height information; also, due to its low resolution, it cannot perform 3D point cloud imaging of targets, severely limiting the application of automotive millimeter-wave radar in high-level autonomous driving systems. With the upgrading of autonomous driving, the requirements for the perception accuracy of automotive millimeter-wave radar are becoming increasingly higher, requiring millimeter-wave radar to be able to perform super-resolution point cloud imaging of surrounding targets and obstacles, and to accurately depict the 3D contour information of targets. Point cloud imaging millimeter-wave radar is the future development direction of automotive millimeter-wave radar for autonomous driving. As the core component of automotive millimeter-wave radar, the number and layout of antenna array channels determine the 3D perception capability and horizontal and pitch resolution of the automotive radar, ultimately determining the 3D point cloud imaging capability of the automotive millimeter-wave radar. Traditional automotive radar uses a uniform antenna array, using MIMO technology to virtually create more antenna channels in the horizontal dimension. In automotive millimeter-wave radar, the number of antenna transmit and receive channels is limited due to cost and size constraints. The virtual antenna multiplication capability of the currently used uniform linear array MIMO technology is limited and cannot meet the higher resolution requirements of autonomous driving. It lacks downward resolution and cannot achieve 3D point cloud imaging. Large-scale multiplication technology for two-dimensional area array antennas is still in its infancy. Therefore, it is necessary to construct new methods and technologies to virtually generate more antenna channels and build a two-dimensional super-resolution area array to significantly increase the horizontal and vertical angular resolution, thereby achieving 3D super-resolution point cloud imaging. Thus, inventing an optimized signal processing method for two-dimensional area array antennas in automotive point cloud imaging radar is particularly important. Summary of the Invention

[0003] The purpose of this invention is to address the shortcomings of existing technologies by proposing an optimized signal processing method for two-dimensional array antennas of vehicle-mounted point cloud imaging radar.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: An optimized signal processing method for a two-dimensional array antenna of a vehicle-mounted point cloud imaging radar is presented, and the specific steps of this signal processing method are as follows: (1) Determine the radar system configuration: Determine the number of transmitting antenna channels and receiving antenna channels in the radar system, confirm the positions of each group of transmitting antenna array elements and receiving antenna array elements, and construct a two-dimensional antenna array in half-wavelength units; (2) Optimize and adjust the positions of the transmitting and receiving antennas: Optimize and adjust the positions of each group of transmitting antenna elements and receiving antenna elements according to the optimization criteria, and uniformly configure each group of transmitting antenna elements and receiving antenna elements to generate a sparse two-dimensional array. At the same time, record and update the aperture of the two-dimensional antenna array. (3) Determine and process the snapshot data: Receive the MIMO signal transmitted by the sparse two-dimensional array, receive the signal returned by the target by the receiving array element, determine its snapshot data, and perform data processing on each received snapshot data; (4) Accumulate detection for each group of channels: Accumulate detection for each group of transmitting and receiving antenna channels based on the processed snapshot data, and record the detection data; (5) Data interpolation of the two-dimensional antenna array: The detection data is arranged on each channel according to the sparse array, and the data interpolation of the two-dimensional antenna array is performed according to the arrangement result.

[0005] The feature is that, in step (1), the number of transmitting antenna channels is marked as M, the number of receiving antenna channels is marked as N, and the positions of each group of transmitting antenna elements and receiving antenna elements are respectively represented by... and The expression is given by, where m = 1, 2, ..., M; q = 1, 2, ..., N, and the half wavelength is specifically represented as D = λ / 2.

[0006] The optimization and adjustment steps in step (2) are characterized by the following specific steps: Step 1: Label the aperture of the two-dimensional antenna array in the horizontal and elevation directions as L, respectively. h and L v ; Step 2: Optimize the two-dimensional antenna array according to the optimization criteria, which are as follows: (1) (2) (3) in, Represents a set The momentum, Represents a set The momentum; Step 3: Obtain the two-dimensional antenna array L through optimization criteria. h and L v The maximum value is recorded, and the positions of the transmitting and receiving antenna elements under the maximum antenna aperture are also recorded. and .

[0007] The data processing steps in step (3) are characterized by the following specific steps: Step 1: After receiving the returned signal, the receiving antenna array element takes the signal with the length of the coherent processing period as a snapshot and generates snapshot data through data conversion processing. Step 2: Perform distance-Doppler processing on each group of received snapshot data.

[0008] The feature is that the specific steps of the accumulation detection in step (4) are as follows: S1: Take the amplitude of the distance-Doppler spectrum for each transmit antenna channel and receive antenna channel, and merge the channels in each group; S2: Perform constant false alarm rate (CFAR) detection on each set of transmit and receive antenna channels to detect each possible target and record the range-Doppler position of each detected target. and the distance to each corresponding channel - Doppler complex value .

[0009] The data interpolation process in step (5) is characterized by the following specific steps: P1: Position of any sparse MIMO array Perform collection, and collect the set of row elements it belongs to in the sparse array. sum of elements set ; P2: The signal value at this location is virtually interpolated using the array data in P1. The specific calculation formula is as follows: (4) in, For weights, express and The signal value of the m-th array element; P3: Based on the array data in the horizontal and vertical directions, a set of Kriging equations is constructed to calculate the corresponding interpolation. Based on the calculated interpolation, a two-dimensional antenna array with a significantly increased number of antenna channels is obtained. The specific set of Kriging equations is as follows: (5) in, It is a variation function. This is the mean.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This optimized signal processing method for a two-dimensional area array antenna of a vehicle-mounted point cloud imaging radar, compared with previous inventions, firstly collects basic information of the radar system and marks the apertures of the two-dimensional antenna array in the horizontal and elevation directions as Lh and Lv, respectively. Simultaneously, it optimizes the two-dimensional antenna array according to optimization criteria and obtains the maximum values ​​of Lh and Lv. Then, it collects the positions of any sparse MIMO array and collects the row and column element sets of the array. Based on the collected array data, it performs virtual interpolation calculations on the signal values ​​at these positions and constructs a Kriging equation system based on the array data in the horizontal and elevation directions to calculate the corresponding interpolation. Based on the calculated interpolation, it obtains a two-dimensional antenna array with a significantly increased number of antenna channels. This provides a design criterion for the design of two-dimensional area array antenna arrays, maximizing the aperture of the two-dimensional antenna array, significantly increasing the number of antenna channels, significantly reducing the sidelobe amplitude during angle measurement, improving angle measurement resolution and accuracy, and reducing the generation of false targets. Attached Figure Description

[0011] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0012] Figure 1 This is a flowchart of the optimized signal processing method for a two-dimensional array antenna of a vehicle-mounted point cloud imaging radar proposed in this invention. Detailed Implementation

[0013] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0014] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0015] Reference Figure 1 An optimized signal processing method for a two-dimensional array antenna of a vehicle-mounted point cloud imaging radar is described, and the specific steps of this signal processing method are as follows: Determine the radar system configuration: Determine the number of transmitting antenna channels and receiving antenna channels in the radar system, confirm the positions of each group of transmitting antenna elements and receiving antenna elements, and construct a two-dimensional antenna array in half-wavelength units.

[0016] It should be further noted that the number of transmit antenna channels is marked as M, and the number of receive antenna channels is marked as N. The positions of each group of transmit antenna elements and receive antenna elements are respectively represented by M. and The expression is given by , where m = 1, 2, ..., M; q = 1, 2, ..., N, and the half-wavelength is specifically represented as D = λ / 2.

[0017] The positions of the transmitting and receiving antennas are optimized and adjusted: the positions of each group of transmitting antenna elements and receiving antenna elements are optimized and adjusted according to the optimization criteria, and the transmitting and receiving antenna elements are uniformly configured to generate a sparse two-dimensional array. At the same time, the aperture of the two-dimensional antenna array is recorded and updated.

[0018] Specifically, the apertures of the two-dimensional antenna array in the horizontal and elevation directions are first labeled as L. h and L v After marking, the two-dimensional antenna array is optimized according to the optimization criterion, and the L-shaped antenna array is obtained through the optimization criterion. h and L v The maximum value is recorded, and the positions of the transmitting and receiving antenna elements under the maximum antenna aperture are also recorded. and It can provide design guidelines for the design of two-dimensional area array antennas, maximizing the aperture of the two-dimensional antenna area array.

[0019] It should be further explained that the specific optimization criteria are as follows:

[0020]

[0021]

[0022] in, Represents a set The momentum, Represents a set The momentum.

[0023] It should be further noted that, based on the traditional MIMO method with uniform spacing, the aperture of the virtualized T-shaped array is L. h =L v =8D; while the aperture of the two-dimensional antenna array of the T-shaped array obtained by the optimization criterion is L. h =L v =24D; It can be seen that the optimization criterion significantly increases the antenna aperture by 3 times, thus significantly improving the horizontal and pitch angle resolution of the vehicle radar.

[0024] Determine and process snapshot data: Receive MIMO signals transmitted by a sparse two-dimensional array, receive signals returned by the target from the array element, determine its snapshot data, and process each received snapshot data.

[0025] Specifically, after the receiving antenna array element receives the returned signal, it takes the signal with the length of the coherent processing period as a snapshot, and generates snapshot data through data conversion processing. At the same time, it performs range-Doppler processing on each group of received snapshot data.

[0026] Accumulated detection of each channel group: Based on the processed snapshot data, accumulated detection of each group of transmit and receive antenna channels is performed, and the detection data is recorded.

[0027] Specifically, the amplitude of the range-Doppler spectrum for each transmit and receive antenna channel is calculated. Simultaneously, the channels are merged, and constant false alarm rate (CFAR) detection is performed on each transmit and receive antenna channel to detect each possible target. The position of each detected target on the range-Doppler spectrum is then recorded. and the distance to each corresponding channel - Doppler complex value .

[0028] Data interpolation for a two-dimensional antenna array: The detection data is arranged in a sparse array on each channel, and the data interpolation process is performed on the two-dimensional antenna array based on the arrangement result.

[0029] Specifically, the staff determined the location of any sparse MIMO array. Perform collection, and collect the set of row elements it belongs to in the sparse array. sum of elements set The system performs virtual interpolation calculations on the signal value at the location based on the collected array data, constructs a Kriging equation system based on the array data in the horizontal and elevation directions to calculate the corresponding interpolation, and obtains a two-dimensional antenna array with a significantly increased number of antenna channels based on the calculated interpolation. This significantly increases the number of antenna channels, significantly reduces the sidelobe amplitude during angle measurement, improves angle measurement resolution and accuracy, and reduces the generation of false targets.

[0030] It should be further explained that the specific virtual interpolation calculation formula is as follows:

[0031] in, For weights, express and The signal value of the m-th array element.

[0032] It should be further explained that the specific Kriging equations are as follows:

[0033] in, It is a variation function. To find the mean, solve this system of equations to obtain the coefficients. Thus, virtual array elements are obtained. value at .

[0034] It should be further explained that, through the above interpolation, a two-dimensional antenna array with a significantly increased number of antenna channels can be obtained. The large-scale virtual array obtained after interpolating the optimized two-dimensional MIMO array has an increase in the number of antenna channels from 64 to 2209, which is 34.5 times. After interpolation, the angle measurement accuracy can be improved and the sidelobe effect can be reduced. The sidelobe is significantly reduced after interpolation, the target peak is narrower and sharper, and the angular resolution is improved.

[0035] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An optimized signal processing method for a two-dimensional array antenna of a vehicle-mounted point cloud imaging radar, characterized in that, The specific steps of this signal processing method are as follows: (1) Determine the radar system configuration: Determine the number of transmitting antenna channels and receiving antenna channels in the radar system, confirm the positions of each group of transmitting antenna array elements and receiving antenna array elements, and construct a two-dimensional antenna array in half-wavelength units; (2) Optimize and adjust the positions of the transmitting and receiving antennas: Optimize and adjust the positions of each group of transmitting antenna elements and receiving antenna elements according to the optimization criteria, and uniformly configure each group of transmitting antenna elements and receiving antenna elements to generate a sparse two-dimensional array. At the same time, record and update the aperture of the two-dimensional antenna array. (3) Determine and process the snapshot data: Receive the MIMO signal transmitted by the sparse two-dimensional array, receive the signal returned by the target by the receiving array element, determine its snapshot data, and perform data processing on each received snapshot data; (4) Accumulate detection for each group of channels: Accumulate detection for each group of transmitting and receiving antenna channels based on the processed snapshot data, and record the detection data; (5) Data interpolation of the two-dimensional antenna array: The detection data is arranged in each channel according to the sparse array, and the data interpolation of the two-dimensional antenna array is performed according to the arrangement result. The specific steps for optimization and adjustment described in step (2) are as follows: Step 1: Label the aperture of the two-dimensional antenna array in the horizontal and elevation directions as L, respectively. h and L v ; Step 2: Optimize the two-dimensional antenna array according to the optimization criteria, which are as follows: （1） （2） （3） in, Represents a set The momentum, Represents a set The momentum; Step 3: Obtain the two-dimensional antenna array L through optimization criteria. h and L v The maximum value is recorded, and the positions of the transmitting and receiving antenna elements under the maximum antenna aperture are also recorded. and ; The specific steps of data interpolation in step (5) are as follows: P1: Position of any sparse MIMO array Perform collection, and collect the set of row elements it belongs to in the sparse array. sum of elements set ; P2: The signal value at this location is virtually interpolated using the array data in P1. The specific calculation formula is as follows: （4） in, For weights, express and The signal value of the m-th array element; P3: Based on the array data in the horizontal and vertical directions, a set of Kriging equations is constructed to calculate the corresponding interpolation. Based on the calculated interpolation, a two-dimensional antenna array with a significantly increased number of antenna channels is obtained. The specific set of Kriging equations is as follows: （5） in, It is a variation function. This is the mean.

2. The method for optimizing the signal processing of a two-dimensional array antenna for vehicle-mounted point cloud imaging radar according to claim 1, characterized in that, The number of transmitting antenna channels in step (1) is marked as M, and the number of receiving antenna channels is marked as N. The positions of the transmitting antenna elements and receiving antenna elements in each group are respectively represented by M. and The expression is given by, where m = 1, 2, ..., M; q = 1, 2, ..., N, and the half wavelength is specifically represented as D = λ / 2.

3. The method for optimizing the signal processing of a two-dimensional array antenna for vehicle-mounted point cloud imaging radar according to claim 1, characterized in that, The specific steps of data processing described in step (3) are as follows: Step 1: After receiving the returned signal, the receiving antenna array element takes the signal with the length of the coherent processing period as a snapshot and generates snapshot data through data conversion processing. Step 2: Perform distance-Doppler processing on each group of received snapshot data.

4. The method for optimizing the signal processing of a two-dimensional array antenna for vehicle-mounted point cloud imaging radar according to claim 1, characterized in that, The specific steps of the accumulation detection described in step (4) are as follows: S1: Take the amplitude of the distance-Doppler spectrum for each transmit antenna channel and receive antenna channel, and merge the channels in each group; S2: Perform constant false alarm rate (CFAR) detection on each set of transmit and receive antenna channels to detect each possible target and record the range-Doppler position of each detected target. and the distance to each corresponding channel - Doppler complex value .

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