A Robust Beamforming Method Based on Covariance Matrix Reconstruction and Steering Vector Estimation

Abstract

The invention discloses a robust beam forming method based on covariance matrix reconstruction and steering vector estimation. Firstly, the covariance matrix of the antenna received data is decomposed by eigenvalue to obtain the noise subspace, the multiple signal classification algorithm is used to estimate the arrival angle of the interference signal and the steering vector is calculated, and then the robust Capon beamforming algorithm is used to correct it. The power of the interference signal is obtained by the orthogonality of the vector, and the interference plus noise covariance matrix is ​​constructed; the constraint condition for solving the steering vector of the desired signal is constructed by finding the subspace orthogonal to the steering vector of the desired signal, and the solution is solved according to the maximum output power. Precise desired signal steering vector. The present invention has good robustness to steering vector errors and interference plus noise covariance matrix errors caused by array position errors, non-interrelated local scattering and total amplitude and phase errors, and has higher robustness than existing methods. Output signal-to-interference-noise ratio, with better output performance.

Description

technical field [0001] The invention belongs to the field of array signal processing, and mainly relates to a robust beamforming method for reconstructing an interference-plus-noise covariance matrix and estimating a steering vector in an amplitude-phase error scenario. Background technique [0002] Adaptive beamforming technology can make the target signal direction in the array output be received and enhanced as effectively as possible, while interference and noise in other directions can be effectively suppressed, thereby improving the SINR of the array. In recent years, it has been widely used in many fields such as radar, radio astronomy, sonar, medical imaging, microphone voice array processing, seismic survey, cognitive radio and wireless communication. When there is a certain deviation between the actual working environment and the ideal assumption model, such as array calibration errors, non-correlated local scattering, and overall amplitude and phase errors, the ad...

AI Technical Summary

Problems solved by technology

It is designed to solve the problem of beamformer performance attenuation caused by the error of the steering vector and interference plus noise covariance matrix caused by the existing array position error, non-local cross-correlation scattering and amplitude phase error

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