A plane phased array antenna stage interference rejection implementation method

Abstract

The application relates to the field of phased array antennas, and discloses a subarray-level anti-interference implementation method based on a planar phased array, which can quickly and accurately perform null processing on multiple interference signals at the subarray level when the planar phased array performs digital beam forming, thereby effectively receiving the expected signals while suppressing the interference. The implementation scheme is as follows: the planar phased array is arranged, and the center position coordinates of each subarray and the array element position coordinates are stored; the target information features are extracted by using a fast capture technology to determine the spatial target positions of the expected signals and the interference signals; a subarray-level constraint matrix C and a constraint vector f required for anti-interference are constructed; the optimal weight values are solved in the unit of the subarray; and a directional diagram is scanned. The anti-interference implementation method based on the planar phased array can be implemented at the subarray level, does not need to know the expected signals and calculate the covariance matrix of the received signals, saves the calculation resources, and can conveniently and quickly perform null processing on the positions of all the interference signals in the directional diagram.

Description

A method for anti-interference implementation based on planar phased array subarray level Technical Field

[0001] This invention relates to beamforming anti-interference algorithms in the field of phased array antennas, and is particularly applicable to subarray-level beamforming anti-interference in planar phased array antennas. Background Technology

[0002] Beamforming uses a beam of a specific shape to guide useful signals or signals with desired direction while suppressing interference from unwanted directions; essentially, it constructs a spatial filter for the signal within the system. In engineering, the signal is often converted from analog to digital at the array element or subarray level. After passing through digital receivers at each stage, the signal is weighted and summed in a signal processor or FPGA to "guide" the antenna array beam to the desired direction over a period of time, thus obtaining the radiation pattern.

[0003] In adaptive digital beamforming methods for array signal processing, the linearly constrained minimum variance (LCMV) criterion is commonly used and can be expressed as:

[0004]

[0005] Where R is the autocorrelation matrix of the received signal, C is the M×(J+1) dimensional constraint matrix, f is the (J+1) dimensional constraint vector, M is the number of antennas in the array, and J is the number of interfering signals. It requires complete knowledge of the desired signal form and direction of attack, and the optimal solution is:

[0006] w = R -1 C[C H R -1 C] -1 f Summary of the Invention

[0007] The technical problem to be solved by this invention is to perform null processing on multiple interference signals quickly and accurately at the subarray level when a planar phased array is performing digital beamforming, so as to achieve effective reception of the desired signal while suppressing interference.

[0008] The technical solution of this invention is as follows:

[0009] A method for anti-interference based on planar phased array subarray level includes the following steps:

[0010] (1) Arrange the planar phased array and store the center position coordinates of each subarray and the position coordinates of the array elements;

[0011] (2) Use fast acquisition technology to extract target information features and determine the azimuth and elevation information of all interference signals and the desired signal;

[0012] (3) Based on the subarray center position and the azimuth and elevation information of all interference signals and desired signals, obtain the steering vectors of all interference signals and desired signals, and construct the subarray-level constraint matrix C and constraint vector f required for anti-interference.

[0013] (4) Solve for the optimal weight vector in units of submatrix based on the submatrix level constraint matrix C and constraint vector f;

[0014] (5) Based on the position coordinates of the array elements, the optimal weight vector and the guiding vector of the scanning direction, the scanning direction pattern is drawn, and the anti-interference implementation result is verified by simulation.

[0015] Furthermore, step (2) specifically includes the following processes:

[0016] (201) Divide the scanning airspace into four regions, issue multiple different directional guide vector weights to the beamformer to form four beams simultaneously, and scan the targets in each region.

[0017] (202) After deframing the four data received by the array element, perform FFT operation to obtain the energy of each beam, compare the signal-to-noise ratio of the four beams, and store the maximum signal-to-noise ratio and the corresponding beam number for the current scan.

[0018] (203) Adjust the beam pointing according to the scanning interval, scan the targets in each area again, return to step (202), until the spatial domain scanning is completed, obtain the beams arranged in descending order of signal-to-noise ratio, and obtain the corresponding beam pointing according to the beam number and the number of scans.

[0019] (204) Calculate the angle error and AGC voltage based on the beam pointing and difference beam data obtained in step (203). Perform beam tracking based on the angle error and AGC voltage. Successful tracking is determined as the desired signal, and the rest are determined as interference signals.

[0020] Furthermore, step (3) specifically includes the following processes:

[0021] Based on the three-dimensional spatial coordinates (x) of the subarray center m ,y m ,z m Using the desired signal direction (θ0, φ0) obtained in step 2, calculate the distance difference that needs to be compensated for at the center of each subarray on the array surface: M is the number of subarrays;

[0022] Calculate the steering vector of the desired signal:

[0023] Based on the three-dimensional spatial coordinates of the subarray center and the direction (θ) of the nth interference signal obtained in step 2 n ,φ n), calculate the distance difference that needs to be compensated at the center of each subarray on the array surface:

[0024]

[0025] Calculate the steering vector of the nth interference signal:

[0026] Constructing the subarray-level constraint matrix C = [a0a1…a] required for interference resistance n …a N ], constraint vector N represents the number of interfering signals.

[0027] Furthermore, step (4) specifically includes the following processes:

[0028] Solving for optimal weights on a submatrix basis: w_center = C[C H C] -1 f is then extended, and all elements within the same subarray are assigned the same weights, resulting in a weight vector w composed of the weights of each element.

[0029] Compared with the prior art, the present invention has the following advantages:

[0030] 1. The anti-interference implementation method based on planar phased array subarray level proposed in this invention does not require the known desired signal or the calculation of the covariance matrix of the received signal, thus saving computational resources.

[0031] 2. The fast acquisition method proposed in this invention can obtain the spatial target position of the desired signal and interference signal, which can meet the requirements of high dynamic target angle acquisition.

[0032] 3. The anti-interference implementation method based on the subarray level of the planar phased array proposed in this invention is implemented at the subarray level, which reduces the engineering implementation cost and allows for convenient and rapid nulling of the positions of all interference signals in the radiation pattern. Attached Figure Description

[0033] Figure 1 is a flowchart of the anti-interference implementation method of the present invention based on the subarray level of planar phased array.

[0034] Figure 2 is a schematic diagram of the center and array elements of the planar phased array antenna subarray of the present invention;

[0035] Figure 3 is a side view of the radiation pattern obtained by solving the optimal weights according to the present invention;

[0036] Figure 4 is a pitch angle cross-section plotted in the directional diagram through the desired direction 0;

[0037] Figure 5 is an azimuth section view taken through the interference direction 1 in the azimuth diagram. Detailed Implementation

[0038] The present invention will be further described below with reference to specific implementation steps:

[0039] A method for anti-interference based on planar phased array subarray level, as shown in Figure 1, specifically includes the following steps:

[0040] Step 1, referring to Figure 2, the planar phased array antenna used in this invention is composed of 48 subarrays in 6 rows and 8 columns. Each subarray contains 8*8 array elements. The three-dimensional spatial coordinates of the center of all subarrays are stored in zuobiao_center, and the matrix size is 48*3. The three-dimensional spatial coordinates of all array elements are stored in zuobiao, and the matrix size is 3072*3.

[0041] Step 2: Extract target information features using fast acquisition technology, and determine the desired signal (θ0,φ0) and interference signals (θ1,φ1)~(θ0,φ0). 10 ,φ 10 The spatial target location.

[0042] The scanning airspace is divided into four regions. Multiple guide vector weights in different directions are sent to the beamformer to form four beams simultaneously. The targets in each region are scanned at a scanning frequency of 40Hz and an azimuth-elevation interval of 1°.

[0043] In the FPGA, after deframe processing of the four data streams received by the array element, a 4096-point FFT operation is performed using a Fast Fourier Transform (FFT) IP core to calculate the energy of each beam: S = I 2 +Q 2 Compare the signal-to-noise ratios (S / N) of the four beams and store the maximum value (SN_max) and the corresponding beam number (beam_num) for the current scan.

[0044] After adjusting the beam pointing according to the scanning interval, the scanning calculation is repeated to update the maximum signal-to-noise ratio and the corresponding beam number until the spatial domain scanning is completed. The beam numbers are obtained in descending order of signal-to-noise ratio, and the beam pointing corresponding to the beam number is stored.

[0045] The baseband processor calculates the angle error and AGC voltage by processing the sum and difference beam data pointing downwards. The beam control software performs beam tracking based on these two data points. Successful tracking is determined as the desired signal, while the rest are determined as interference signals.

[0046] Step 3: Based on the three-dimensional spatial coordinates zuobiao_center of the subarray center and the desired signal direction (θ0, φ0) obtained in Step 2, calculate the distance difference that needs to be compensated for at the center of each subarray on the array surface:

[0047]

[0048] Calculate the steering vector of the desired signal:

[0049] Based on the three-dimensional spatial coordinates of the subarray center and the direction (θ) of the nth interference signal obtained in step 2 n ,φ n ), calculate the distance difference that needs to be compensated at the center of each subarray on the array surface:

[0050]

[0051] Calculate the steering vector of the nth interference signal:

[0052] Constructing the subarray-level constraint matrix C = [a0a1…a] required for interference resistance 10 ], constraint vector f = [10000000000].

[0053] Step 4, solve for the optimal weights on a subarray basis: w_center = C[C H C] -1 f is then expanded so that all elements within the same subarray have the same weight, resulting in a weight vector w with 3072 elements.

[0054] Step 5: Based on the three-dimensional spatial coordinates of the array element, refer to Step 3 to calculate the guiding vector a of the scanning direction (θ, φ). s Draw the direction diagram P = w'·a s The results are shown in Figure 3. Refer to Figures 4 and 5 for pitch and azimuth angle processing and analysis.

[0055] In addition to the above embodiments, the present invention may have other implementations. Since conformal arrays and other irregular arrays have the same coordinate expression form as surface arrays in three-dimensional space, all technical solutions that adopt equivalent substitution or equivalent transformation forms fall within the protection scope claimed by the present invention.

Claims

1. A method for implementing anti-interference based on a planar phased array subarray, characterized in that, Includes the following steps: (1) Arrange the planar phased array and store the center position coordinates of each subarray and the position coordinates of the array elements; (2) Use fast acquisition technology to extract target information features and determine the azimuth and elevation information of all interference signals and the desired signal. (3) Based on the center position of the subarray and the azimuth and elevation information of all interference signals and the desired signal, the steering vectors of all interference signals and the desired signal are obtained, and the subarray-level constraint matrix required for anti-interference is constructed. and constraint vector (4) Based on the subarray level constraint matrix and constraint vector (5) Solve for the optimal weight vector in units of subarrays; (6) Based on the position coordinates of array elements, the optimal weight vector and the guide vector of the scanning direction, scan and draw the direction map, and simulate and verify the anti-interference implementation results; Among them, step (2) specifically includes the following process: (201) Divide the scanning space into four regions, send multiple guide vector weights in different directions to the beamformer to form four beams at the same time, and scan the targets in each region; (202) After deframing the four data received by the array elements, perform FFT operation, calculate the energy of each beam, compare the signal-to-noise ratio of the four beams, and store the maximum signal-to-noise ratio of the current scan. and the corresponding beam number; (203) Adjust the beam pointing according to the scanning interval, scan the target in each area again, return to step (202), until the spatial domain scanning is completed, obtain the beams arranged in descending order of signal-to-noise ratio, and obtain the corresponding beam pointing according to the beam number and the number of scans; (204) Calculate the angle error and AGC voltage according to the sum and difference beam data under the beam pointing obtained in step (203), perform beam tracking according to the angle error and AGC voltage, and determine the successful tracking as the desired signal, and the rest as interference signals; Among them, step (3) specifically includes the following process: according to the three-dimensional spatial coordinates of the subarray center The desired signal direction obtained in step 2 Calculate the distance difference that needs to be compensated at the centers of each subarray on the array surface: ， The number of subarrays; calculate the steering vector of the desired signal: Based on the three-dimensional spatial coordinates of the subarray center and the first obtained in step 2... One direction of interference signal Calculate the distance difference that needs to be compensated at the centers of each subarray on the array surface: ; Calculate the first The steering vector of the interference signal: Construct the subarray-level constraint matrix required for interference resistance. constraint vector ， The number of interference signals; wherein, step (4) specifically includes the following process: solving for the optimal weights on a subarray basis: Furthermore, the process is expanded so that all elements within the same subarray are assigned the same weights, resulting in a weight vector composed of the weights of each element. 。

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