CN118884358A - Angle measurement method, device, terminal and medium based on sparse array - Google Patents

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 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; taking out 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 to calculate the angle of the target. The present application uses the signal law of the existing channel to predict the array element signal at the vacant position, thereby converting the sparse array into a uniform array with a spacing of approximately half a wavelength, and then performing target angle measurement calculation after channel weighting to improve the angle measurement accuracy.

Description

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

Technical Field

The present application relates to the field of radar technology, and in particular to an angle measurement method, device, terminal and medium based on a sparse array.

Background Art

With the vigorous development of autonomous driving technology, the application of millimeter-wave radar is becoming more and more extensive. Due to the continuous iteration of technology, millimeter-wave radar is also developing in the direction of 4D and high resolution. Its key technology is multi-channel technology, which virtualizes a larger antenna array to achieve high angle resolution and improve the detection distance. There are two specific implementation plans for virtual arrays, one is a uniform array and the other is a sparse array. In order to meet the range of angle measurement, the uniform array basically adopts a half-wavelength spacing, but to achieve a resolution of 1° to 2°, a lot of channels are required, which means that higher hardware configuration is required, which greatly increases the cost. In a sparse array, different array elements in a virtual array use a half-wavelength spacing and a larger spacing, so that a higher resolution can be achieved with fewer antennas and hardware configurations. However, there has been no good way to calculate the angle of a virtual sparse array, and the resulting angle measurement is often not accurate.

Summary of the invention

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.

The technical solution of this application is as follows:

On the one hand, the present application provides an angle measurement method based on a sparse array, characterized in that it includes the following steps:

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;

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

S3: Completing the sparse array according to the above rules, calculating the target information corresponding to the missing array elements in the sparse array, and converting the sparse array into a uniform array;

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

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

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.

Furthermore, in step S3, the step of obtaining the 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.

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

On the other hand, the present application provides a sparse array angle measuring device, comprising:

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;

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

A filling unit is used to 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;

The angle measuring unit is used to calculate the angle of the target after multiplying the padded virtual array by the window function.

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.

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.

In summary, the beneficial effects of the present application are as follows: using the signal law of the existing channels to predict the array element signals at the vacant positions, thereby transforming the sparse array into a uniform array with a spacing of approximately half a wavelength, and after the channels are weighted, the target angle measurement calculation is performed. Normally, the angle measurement is to perform DBF calculation on the target signals of each channel, etc. After using the method of the present application, the main peak of the target signal calculation result is smooth and continuous, and there is only one maximum point for a single target, and this maximum point is also the maximum value point, and the judgment is simple and clear. Other maximum points are systematic noise, and the intensity is stable and has a large difference from the main peak. When the method of the present application is not used, after the DBF calculation, there are multiple maximum points on the main peak for a single target, and 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

FIG1 is a schematic diagram of a virtual array of antennas in a specific embodiment of the present application;

FIG2 is a schematic diagram of the angle measurement principle of a radar antenna in a specific embodiment of the present application;

FIG3 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;

FIG4 is a schematic diagram of a window function and DBF calculation result after a virtual array fills a missing array with zeros in a specific embodiment of the present application;

FIG5 is a schematic diagram of a virtual array phase value in a specific embodiment of the present application;

FIG6 is a schematic diagram of a window function and DBF calculation result after missing elements of a virtual array are completed in a specific embodiment of the present application;

FIG. 7 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

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

A specific embodiment of the present application provides an angle measurement method based on a sparse array, as shown in FIG7 , comprising the following steps:

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; let the spacing of the uniform array elements be d, and in the sparse array, the array element spacing d of the uniform array elements is half a wavelength.

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

S2: taking out the target information obtained by the uniform array element, calculating the amplitude and phase value of the target signal, and obtaining 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 of adjacent array elements in the uniform array element.

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 step of obtaining the missing elements is: 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.

S4: multiplying the padded virtual array by the window function to calculate the angle of the target. Specifically, Taylor weighting is used to process the padded virtual array.

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

In this scenario, a MIMO radar with three transmitting antennas and four receiving antennas is taken as an example. The spacing between the receiving antennas is half a wavelength, i.e., 0.5λ. Therefore, the coordinates of the receiving antennas are (0, 0), (0.5λ, 0), (λ, 0), (1.5λ, 0), and the coordinates of the transmitting antennas are (0, 8λ), (2λ, 8λ), (8λ, 8λ).

Using MIMO (multiple input multiple output) technology, the virtual antenna array consists of 12 antenna elements, as shown in Figure 1. The black solid points in Figure 1 are the antenna elements in the virtual antenna array. The 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), and (9.5λ, 0).

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. As shown in Figure 2, R1, R2, R3, and R4 are different receiving antennas, the direction of the arrow is the direction of the signal path returned by the target, Δd is the distance difference of the signal, and the phase difference of the signals of each receiving antenna is Δd/λ, λ is the wavelength of the carrier frequency. And because Δd=Lsinθ, L is the virtual array element spacing, that is, the phase difference between the signals of each receiving antenna is Lsinθ/λ. When the target angle is constant, the phase difference of the signals between the receiving antennas with the same spacing is the same. At the same time, because the distance from the target to the receiver is relatively far, the signal amplitude is almost the same with a small distance difference. From this, the amplitude and phase of the receiving antennas at adjacent positions with the same spacing can be derived.

For the missing array elements shown in Figure 1, zero padding is performed and DBF (Digital Beamforming) calculation is performed. The result is shown in Figure 3. A single target will have multiple peaks, and the target cannot be determined.

For the missing array elements shown in Figure 1, zero padding is performed, DBF (Digital Beamforming) calculation is performed, and weighting is performed. The result is shown in Figure 4. The effect is significantly improved, but still does not meet expectations.

Assuming the coordinates of the target are (10,50), and assuming the modulus of the target's echo signal 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:

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.

Take the phase value of the target signal and list the phase values as shown in Figure 5. Since the signal will exceed positive and negative π after continuous changes, folding will occur. The dotted box is the phase value derived according to the phase law.

According to the calculated phase value and the modulus value of the signal, the target signal is completed as follows:

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.

After completing the array, the following weights are added 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 DBF is used to calculate and get the angle measurement results, as shown in Figure 6. It can be seen that the angle measurement effect is significantly improved.

In the actual radar angle measurement process, even after calibration, the phase obtained by each array element still has errors such as noise, so multiple array elements with the same spacing are required to obtain the average phase difference in order 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.

Another specific embodiment of the present application provides a sparse array angle measuring device, comprising:

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;

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

A filling unit is used to 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;

The angle measuring unit is used to calculate the angle of the target after multiplying the padded virtual array by the window function.

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 as described above is implemented.

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.

The above is only a preferred implementation of the present application. It should be pointed out that a person skilled in the art can make several modifications and improvements without departing from the inventive concept of the present application, and these all fall within the scope of protection of the present application.

Claims (8)

1. The angle measurement method based on the sparse array is characterized by comprising the following steps of:

S1: constructing a MIMO radar virtual sparse array, wherein the sparse array comprises a plurality of continuous uniform array elements with the same spacing, 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;

s2: taking out the target information obtained by the uniform array elements, and calculating the amplitude and phase value of the target signal to obtain the continuous linear change rule of the target phase corresponding to different array elements;

s3: filling the sparse array according to the rule, calculating target information corresponding to the missing array elements in the sparse array, and converting the sparse array into a uniform array;

S4: and multiplying the supplemented virtual array by a window function, and then performing angle calculation on the target.

2. The sparse array-based angular measurement method of claim 1, wherein the array element spacing d of the uniform array elements in the sparse array is half a wavelength.

3. The sparse array-based goniometry method of claim 1, wherein in step S2, obtaining a continuous linear change law of the target phase further comprises: and calculating the average phase difference of adjacent array elements in the uniform array elements.

4. The angle measurement method based on the sparse array according to claim 1, wherein in the step S3, the missing array elements are obtained by comparing the sparse array with the uniform array with the same caliber and the same pitch, and the missing array elements are the missing array elements.

5. The sparse array-based goniometry method of claim 1, wherein in step S4, the aligned virtual arrays are processed using taylor weighting.

6. An angle measuring device of a sparse array, characterized by comprising the following steps:

the sparse array construction unit is used for constructing a MIMO radar virtual sparse array, wherein the sparse array comprises a plurality of continuous uniform array elements with the same spacing, other array elements are sparse array elements, and the spacing of the sparse array elements is integral multiple of the spacing of the uniform array elements;

The fitting unit is used for taking out target information obtained by the uniform array elements, calculating the amplitude and phase value of the target signal and obtaining the continuous linear change rule of the target phase corresponding to different array elements;

the filling unit is used for filling the sparse array according to the rule, calculating target information corresponding to the missing array elements in the sparse array, and converting the sparse array into a uniform array;

And the angle measurement unit is used for multiplying the virtual array after the alignment by the window function and then calculating the angle of the target.

7. A MIMO radar signal processing terminal comprising a processor and a memory, the memory storing a computer program which, when invoked by the processor for execution, implements a sparse array based goniometry method as claimed in any one of claims 1-5.

8. A computer readable medium, characterized in that it has stored therein a computer program which, when executed by a computer call, implements the sparse array based goniometry method of any of claims 1-5.