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Beam forming method based on expected steering vector estimation and matrix reconstruction

A technology that expects steering vector and steering vector, applied in radio wave measurement systems, instruments, etc., can solve problems such as general performance, and achieve the effect of improving performance, improving output signal-to-interference noise ratio, and improving output performance

Pending Publication Date: 2022-07-22
南京理工大学紫金学院
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Problems solved by technology

Although this method effectively improves the output signal-to-dry ratio performance of the algorithm, it does not perform well in common uniform arrays.

Method used

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  • Beam forming method based on expected steering vector estimation and matrix reconstruction
  • Beam forming method based on expected steering vector estimation and matrix reconstruction
  • Beam forming method based on expected steering vector estimation and matrix reconstruction

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Embodiment 1

[0103] refer to Figures 1 to 2 , which is an embodiment of the present invention, provides a beamforming method based on expected steering vector estimation and matrix reconstruction, including:

[0104] S1: construct a sampling covariance matrix according to the data received by the array;

[0105] Further, the data received by the array is the signal received by the array, it can be seen that figure 2 , which shows a model of a uniform linear array receiving signal. The signal received by the array is set as a far-field narrowband signal. Taking a uniform linear array as an example, it can be expressed as:

[0106]

[0107] where x i (t) represents the signal received by the i-th array element, and N represents the number of array elements;

[0108] It should be noted that the uniform linear array is a basic array form proposed according to the antenna electromagnetic field theory and objective laws. It is a commonly used analytical model for sonar or radar signal pr...

Embodiment 2

[0191] refer to image 3, which is an embodiment of the present invention, provides a beamforming method based on expected steering vector estimation and matrix reconstruction. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0192] A uniform linear array with 16 array elements received three far-field narrowband signals, in which the desired signal was incident from -0°, and the interference signal was incident from -30° and 40°, respectively, and the array element spacing was half wavelength. The simulation objects include Worst Case Optimal Algorithm (WSC), Diagonal Loading (DL), Eigen Subspace (ESB), and Sampling Matrix Inversion (SMI), as well as the proposed algorithm (proposed) for comprehensive simulation. Simulation results are used to analyze the advantages of the present invention, wherein the error range of the WSC algorithm is set to 3, and the diagonal loading factor of t...

Embodiment 3

[0195] refer to Figures 4 to 5 , which is an embodiment of the present invention, provides a beamforming method based on expected steering vector estimation and matrix reconstruction. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0196] Same as the previous embodiment, a uniform linear array with 16 array elements receives three far-field narrowband signals, where the desired signal is incident from -0°, and the interference signal is incident from -30° and 40°, respectively. The element spacing is half wavelength. The simulation objects include Worst Case Optimal Algorithm (WSC), Diagonal Loading (DL), Eigen Subspace (ESB), and Sampling Matrix Inversion (SMI), as well as the proposed algorithm (proposed) for comprehensive simulation. Simulation results are used to analyze the advantages of the present invention, wherein the error range of the WSC algorithm is set to 3, and the di...

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Abstract

The invention discloses a beamforming method based on expected steering vector estimation and matrix reconstruction. The beamforming method comprises the following steps: constructing a sampling covariance matrix according to data received by an array; correcting an expected signal steering vector according to the sampling covariance matrix; estimating a steering vector of an interference signal by using a Capon spatial spectrum, and estimating noise power on the basis of the steering vector; estimating interference signal power by using the steering vector of the interference signal, and reconstructing an interference and noise matrix in combination with the noise power; and substituting the desired signal steering vector and the reconstructed interference and noise matrix into an MVDR beam former to obtain a final weight vector expression. According to the method, the expected signal steering vector can be obtained more accurately, and the algorithm performance is improved; expected signal components in the sampling covariance matrix are effectively removed, and the output signal to interference plus noise ratio of the beam former is improved; in non-ideal environments such as low signal-to-noise ratio and low sampling snapshot number, the algorithm still has an ideal effect.

Description

technical field [0001] The present invention relates to the technical field of adaptive beamforming in array signal processing technology, in particular to a beamforming method based on expected steering vector estimation and matrix reconstruction. Background technique [0002] Although the traditional adaptive beamforming algorithm has better performance under ideal conditions, the actual transmission environment is very complex, and there are various errors, such as steering vector, expected signal direction of arrival, number of sampling snapshots, transmission channel error, etc. Unsatisfactory conditions will affect the performance of traditional beamforming algorithms, especially when the received snapshot data contains the desired signal, as the input signal-to-noise ratio increases, the output performance will actually decrease. "self-cancellation" effect. Therefore, one of the main goals of the adaptive beamforming algorithm is to solve the "self-cancellation" phen...

Claims

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Application Information

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IPC IPC(8): G01S7/41G01S7/539
CPCG01S7/41G01S7/539
Inventor 赵丹邵建功
Owner 南京理工大学紫金学院
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