Angle measurement method, device, terminal and medium based on sparse array

Abstract

The present application discloses an angle measurement method, device, terminal, and medium based on a sparse array. The angle measurement method includes the following steps: constructing a MIMO radar virtual sparse array, including a number of continuous uniform array elements with the same spacing, and the other array elements are sparse array elements, and the spacing of the sparse array elements is an integer multiple of the spacing of the uniform array elements; extracting the target information obtained by the uniform array elements, calculating the amplitude and phase values ​​of the target signal, and obtaining the continuous linear change law of the target phase corresponding to different array elements; filling the sparse array according to the above law, calculating the target information corresponding to the missing array elements in the sparse array, and converting the sparse array into a uniform array; multiplying the filled virtual array by a window function and then calculating the target angle. The present application utilizes the signal law of existing channels to predict the array element signals at the vacant positions, thereby converting the sparse array into a uniform array with a spacing of approximately half a wavelength. After channel weighting, the target angle measurement calculation is performed to improve the angle measurement accuracy.

Description

Technical Field

[0001] The present application relates to the field of radar technology, and in particular to a sparse array-based angle measurement method, device, terminal, and medium. Background Art

[0002] With the rapid development of autonomous driving technology, the application of millimeter-wave radar is becoming increasingly widespread. Due to continuous technological advancements, millimeter-wave radar is also developing towards 4D and high-resolution. The key technology behind this is multi-channel technology. By creating a larger virtual antenna array, high angular resolution is achieved, while also increasing detection range. There are two specific implementations for virtual arrays: uniform arrays and sparse arrays. Uniform arrays generally use half-wavelength spacing to meet the angular measurement range. However, achieving a resolution of 1° to 2° requires a very large number of channels, which in turn requires higher hardware configuration, significantly increasing costs. Sparse arrays, in which different elements within a virtual array are sometimes spaced at half-wavelength spacing and sometimes at larger spacing, achieve higher resolution with fewer antennas and hardware configurations. However, there has been no effective method for angle calculation with virtual sparse arrays, and the resulting angle measurements are often inaccurate. Summary of the Invention

[0003] The present application provides a sparse array-based angle measurement method, device, terminal, and medium, which have the advantage of being able to improve the accuracy of sparse array angle measurement.

[0004] The technical solution of this application is as follows:

[0005] In one aspect, the present application provides a sparse array-based angle measurement method, characterized in that it includes the following steps:

[0006] S1: Construct a MIMO radar virtual sparse array, wherein the sparse array includes a number of continuous uniform array elements with the same spacing, and the other array elements are sparse array elements, and the spacing of the sparse array elements is an integer multiple of the spacing of the uniform array elements;

[0007] S2: Take out the target information obtained by the uniform array element, calculate the amplitude and phase values ​​of the target signal, and obtain the continuous linear change law of the target phase corresponding to different array elements;

[0008] S3: Fill the sparse array according to the above rules, calculate the target information corresponding to the missing array elements in the sparse array, and convert the sparse array into a uniform array;

[0009] S4: Multiply the padded virtual array by the window function and calculate the angle of the target.

[0010] Furthermore, in the sparse array, the array element spacing d of the uniform array elements is half a wavelength.

[0011] Furthermore, in step S2, obtaining the target phase continuous linear variation rule further includes: calculating the average phase difference between adjacent array elements in the uniform array element.

[0012] Furthermore, in step S3, the step of obtaining missing array elements is as follows: when the sparse array is compared with a uniform array with the same spacing and the same caliber, the array elements missing from the sparse array are the missing array elements.

[0013] Furthermore, in step S4, Taylor weighting is used to process the padded virtual array.

[0014] In another aspect, the present application provides a sparse array angle measurement device, comprising:

[0015] A sparse array construction unit is used to construct a MIMO radar virtual sparse array, wherein the sparse array includes a number of continuous uniform array elements with the same spacing, and the other array elements are sparse array elements, and the spacing of the sparse array elements is an integer multiple of the spacing of the uniform array elements;

[0016] The fitting unit is used to extract the target information obtained by the uniform array element, calculate the amplitude and phase values ​​of the target signal, and obtain the continuous linear change law of the target phase corresponding to different array elements;

[0017] A padding unit is used to pad the sparse array according to the above rules, calculate the target information corresponding to the missing array elements in the sparse array, and convert the sparse array into a uniform array;

[0018] The angle measurement unit is used to calculate the angle of the target after multiplying the padded virtual array by the window function.

[0019] On the other hand, the present application provides a MIMO radar signal processing terminal, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is called and executed by the processor, the sparse array-based angle measurement method as described above is implemented.

[0020] On the other hand, the present application provides a computer-readable medium, characterized in that a computer program is stored in the computer-readable medium, and when the computer program is called and executed by a computer, the angle measurement method based on the sparse array as described above is implemented.

[0021] In summary, the beneficial effects of the present application are as follows: utilizing the signal patterns of existing channels to predict the array element signals at the vacant locations, thereby transforming the sparse array into an array with a uniform spacing of approximately half a wavelength. After channel weighting, target angle measurement calculation is performed. Normally, angle measurement is to perform DBF calculation on the target signals of each channel. After using the method of the present application, the main peak of the target signal calculation result is smooth and continuous. When there is a single target, there is only one maximum point, and this maximum point is the maximum point. The judgment is simple and clear. The other maximum points are systematic noise with stable intensity and a large difference from the main peak. When the method of the present application is not adopted, after DBF calculation, there are multiple maximum points on the main peak when there is a single target. The multiple maximum points are not much different, which makes it easy to identify one target as multiple targets, or cause confusion when measuring more than two targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a schematic diagram of a virtual array of antennas in a specific embodiment of the present application;

[0023] Figure 2 This is a schematic diagram of the radar antenna angle measurement principle in a specific embodiment of the present application;

[0024] Figure 3 This is a schematic diagram of a virtual array filling zeros for a missing array and DBF calculation results in a specific embodiment of the present application;

[0025] Figure 4 This is a schematic diagram of the window function and DBF calculation results after the virtual array fills the missing array with zeros in a specific embodiment of the present application;

[0026] Figure 5 This is a schematic diagram of a virtual array phase value in a specific embodiment of the present application;

[0027] Figure 6 This is a schematic diagram of the results of completing missing elements in a virtual array, adding a window function, and calculating DBF in a specific embodiment of the present application;

[0028] Figure 7 This is a schematic diagram of the steps of an angle measurement method based on a sparse array in a specific embodiment of the present application. DETAILED DESCRIPTION

[0029] The specific implementation of the present application is described in detail below with reference to the accompanying drawings.

[0030] A specific embodiment of the present application provides an angle measurement method based on a sparse array, such as Figure 7 , including the following steps:

[0031] S1: Construct a MIMO radar virtual sparse array, where the sparse array includes several continuous uniform array elements with the same spacing, and the other array elements are sparse array elements. The spacing between sparse array elements is an integer multiple of the uniform array element spacing. Let the spacing between uniform array elements be d. In the sparse array, the element spacing d is half a wavelength.

[0032] The distance from the first array element to the last array element is called the aperture.

[0033] S2: Receive target information obtained by the uniform array element, calculate the amplitude and phase values ​​of the target signal, and obtain the continuous linear variation law of the target phase corresponding to different array elements; obtaining the continuous linear variation law of the target phase also includes: calculating the average phase difference between adjacent array elements in the uniform array element.

[0034] S3: Completing the sparse array according to the above rules, calculating the target information corresponding to the missing elements in the sparse array, and converting the sparse array into a uniform array; the steps for obtaining the missing elements are: comparing the sparse array with a uniform array with the same spacing and the same caliber, the missing elements in the sparse array are the missing elements.

[0035] S4: Multiplying the padded virtual array by the window function to calculate the target angle. Specifically, Taylor weighting is used to process the padded virtual array.

[0036] The method proposed in this embodiment is described in detail below using a specific application scenario.

[0037] In this scenario, a MIMO radar with three transmitting antennas and four receiving antennas is used as an example. The receiving antennas are spaced half a wavelength apart, or 0.5λ. Therefore, the receiving antenna coordinates are (0, 0), (0.5λ, 0), (λ, 0), and (1.5λ, 0). The transmitting antenna coordinates are (0, 8λ), (2λ, 8λ), and (8λ, 8λ).

[0038] Using MIMO (multiple input multiple output) technology, the virtual antenna array consists of 12 antenna elements, such as Figure 1 As shown, Figure 1 The black solid dots in the middle are antenna elements in the virtual sky array. Their coordinates are (0,0), (0.5λ,0), (λ,0), (1.5λ,0), (2λ,0), (2.5λ,0), (3λ,0), (3.5λ,0), (8λ,0), (8.5λ,0), (9λ,0), (9.5λ,0).

[0039] When the distance of the target is much greater than the far-field condition, the angle θ from the target to each receiving antenna is considered to be approximately the same. Figure 2As shown in the figure, R1, R2, R3, and R4 are different receiving antennas. The arrows indicate the return signal path from the target. Δd is the signal path difference. The phase difference between the signals from each receiving antenna is Δd / λ, where λ is the carrier wavelength. Since Δd = Lsinθ, and L is the virtual array element spacing, the phase difference between the signals from each receiving antenna is Lsinθ / λ. When the target angle is constant, the signal phase difference between receiving antennas with the same spacing is the same. Furthermore, because the target-to-receiver distance is relatively long, even small distance differences result in nearly identical signal amplitudes. This allows us to deduce the amplitude and phase of adjacent receiving antennas with the same spacing.

[0040] right Figure 1 The missing elements shown are filled with zeros and DBF (Digital Beamforming) calculations are performed. The results are as follows Figure 3 As shown, a single target will have multiple peaks, making it impossible to determine the target

[0041] right Figure 1 The missing elements shown are filled with zeros, and DBF (Digital Beamforming) calculation is performed and weighted. The result is as follows Figure 4 As shown, the effect has improved significantly, but still cannot meet expectations.

[0042] Assuming the target's coordinates are (10, 50), and assuming the target's echo signal modulus is 1, the target's echo signal is calculated based on the distance relationship between the target and the array elements in the virtual array of the receiving antenna as follows:

[0043] 0.7191 - 0.6949i, 0.9884 - 0.1517i, 0.8944 + 0.4472i, 0.4718 + 0.8817i, -0.1256 + 0.9921i, -0.6757 + 0.7372i, -0.9774 + 0.2113i, -0.9199 - 0.3921i, -0.9414 + 0.3374i, -0.9633 - 0.2686i, -0.6311 - 0.7757i, -0.0670 - 0.9978i.

[0044] Get the phase value of the target signal and list the phase values ​​as follows: Figure 5 As shown in the figure, folding will occur because the signal will exceed positive and negative π after continuous changes. The dotted box is the phase value derived based on the phase law.

[0045] Based on the calculated phase value and the modulus value of the signal, the target signal is completed as follows:

[0046] 0.7191 - 0.6949i, 0.9884 - 0.1517i, 0.8944 + 0.4472i, 0.4718 + 0.8817i, -0.1256 + 0.9921i, -0.6757 + 0.7372i, -0.9774 + 0.2113i, -0.9199 - 0.3921i, -0.5248 - 0.8512i, 0.0635 - 0.9980i, 0.6284 - 0.7779i, 0.9623 - 0.2720i, 0.9434 +0.3316i, 0.5784 + 0.8158i, 0.0008+ 1.0000i, -0.5770 + 0.8168i, -0.9414 +0.3374i, -0.9633 - 0.2686i, -0.6311 - 0.7757i, -0.0670 - 0.9978i.

[0047] After completing the array, add the following weights to the 20 channels: 0.2220, 0.3086, 0.4670, 0.6737, 0.9034, 1.1346, 1.3498, 1.5330, 1.6679, 1.7400, 1.7400, 1.6679, 1.5330, 1.3498, 1.1346, 0.9034, 0.6737, 0.4670, 0.3086, 0.2220. Then use DBF to calculate and get the angle measurement result, as shown below: Figure 6 , it can be seen that the angle measurement effect is significantly improved.

[0048] In the actual radar angle measurement process, even after calibration, the phase obtained by each array element still has errors such as noise. Therefore, multiple array elements with the same spacing are required to obtain the average phase difference to ensure the accuracy of the prediction. At the same time, other sparse array elements can be used to verify the estimated value to ensure the accuracy of the supplementary value.

[0049] Another specific embodiment of the present application provides a sparse array angle measurement device, comprising:

[0050] A sparse array construction unit is used to construct a MIMO radar virtual sparse array, wherein the sparse array includes a number of continuous uniform array elements with the same spacing, and the other array elements are sparse array elements, and the spacing of the sparse array elements is an integer multiple of the spacing of the uniform array elements;

[0051] The fitting unit is used to extract the target information obtained by the uniform array element, calculate the amplitude and phase values ​​of the target signal, and obtain the continuous linear change law of the target phase corresponding to different array elements;

[0052] A padding unit is used to pad the sparse array according to the above rules, calculate the target information corresponding to the missing array elements in the sparse array, and convert the sparse array into a uniform array;

[0053] The angle measurement unit is used to calculate the angle of the target after multiplying the padded virtual array by the window function.

[0054] Another specific embodiment of the present application provides a MIMO radar signal processing terminal, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is called and executed by the processor, the sparse array-based angle measurement method described above is implemented.

[0055] Another specific embodiment of the present application provides a computer-readable medium, characterized in that a computer program is stored in the computer-readable medium, and when the computer program is called and executed by a computer, the angle measurement method based on the sparse array as described above is implemented.

[0056] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this field, several variations and improvements can be made without departing from the creative concept of the present application, and these all fall within the scope of protection of the present application.

Claims

1. A method for angle measurement based on a sparse array, characterized in that: The following steps are involved: S1: Constructing a MIMO radar virtual sparse array, wherein the sparse array includes a number of continuous uniform array elements with the same spacing, and the other array elements are sparse array elements, and the spacing of the sparse array elements is an integer multiple of the uniform array element spacing; in the sparse array, the array element spacing d of the uniform array elements is half a wavelength; S2: extracting target information obtained by the uniform array element, calculating the amplitude and phase values ​​of the target signal, and obtaining a continuous linear variation law of the target phase corresponding to different array elements; obtaining the continuous linear variation law of the target phase also includes: calculating the average phase difference between adjacent array elements in the uniform array element; S3: Fill the sparse array according to the above rules, calculate the target information corresponding to the missing array elements in the sparse array, and convert the sparse array into a uniform array; S4: Multiply the padded virtual array by the window function and calculate the angle of the target.

2. The angle measurement method based on sparse array according to claim 1, characterized in that: In step S3, the step of obtaining missing array elements is as follows: when the sparse array is compared with a uniform array with the same spacing and the same caliber, the array elements missing from the sparse array are the missing array elements.

3. The angle measurement method based on sparse array according to claim 1, characterized in that: In step S4, Taylor weighting is used to process the padded virtual array.

4. A sparse array angle measuring device, characterized in that: include: A sparse array construction unit is used to construct a MIMO radar virtual sparse array, wherein the sparse array includes a number of continuous uniform array elements with the same spacing, and the other array elements are sparse array elements, and the spacing of the sparse array elements is an integer multiple of the uniform array element spacing; in the sparse array, the array element spacing d of the uniform array elements is half a wavelength; The fitting unit is used to extract the target information obtained by the uniform array element, calculate the amplitude and phase values ​​of the target signal, and obtain the continuous linear change law of the target phase corresponding to different array elements; obtaining the continuous linear change law of the target phase also includes: calculating the average phase difference between adjacent array elements in the uniform array element; A padding unit is used to pad the sparse array according to the above rules, calculate the target information corresponding to the missing array elements in the sparse array, and convert the sparse array into a uniform array; The angle measurement unit is used to calculate the angle of the target after multiplying the padded virtual array by the window function.

5. A MIMO radar signal processing terminal, characterized in that: The invention comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is called and executed by the processor, the angle measurement method based on the sparse array according to any one of claims 1 to 3 is implemented.

6. A computer-readable medium, characterized in that The computer-readable medium stores a computer program, and when the computer program is called and executed by a computer, the angle measurement method based on a sparse array according to any one of claims 1 to 3 is implemented.

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