Reconstruction robust beam forming method based IAA interference plus noise covariance matrix

Abstract

The invention belongs to the technical field of antenna beam forming, and discloses a reconstruction robust beam forming method based on IAA interference plus noise covariance matrix. The method comprises the following steps of: firstly, estimating the direction of a signal more accurately in an iterative mode by using IAA method, then selecting the characteristic vector with the maximum correlation with the steering vector calculated by using the estimated direction of the desired signal from sampling covariance matrix characteristic vectors and rejecting the characteristic vector from the sampling covariance matrix, finally, selecting a proper diagonal loading factor to carry out diagonal loading on the matrix in order to prevent the covariance matrix after rejecting the signal from generating singular, in the case that the sample contains the desired signal, the signal to noise ratio of a self-adaptive beam former is improved and the robust performance of the self-adaptive beam former is improved in the case of a mismatch steering vector.

Description

technical field [0001] The invention belongs to the technical field of antenna beamforming, in particular to an IAA (Iterative Adaptive Approach, Iterative Adaptive) based interference-plus-noise covariance matrix reconstruction robust beamforming method, which is suitable for solving the problem of self-adaptation caused by strong expected signal power in sampling samples The beamformer output signal-to-interference-noise ratio declines, and the adaptive beamformer has good robust performance in the case of steering vector mismatch. Background technique [0002] Adaptive beamforming technology is an important research direction in the field of array signal processing. Compared with the traditional single antenna, the antenna array can calculate the weighting factors on each array element through an adaptive algorithm according to the change of the signal environment, so as to perform spatial filtering on the signal received by the array, so that the formed beam points to th...

AI Technical Summary

Problems solved by technology

In 2003, Vorobyov proposed the worst performance optimization algorithm, which constrains the mismatched signal steering vector in a spherical uncertainty set, and transforms the problem of solving the adaptive weight vector into a second-order cone programming problem , can maintain a certain robustness within a certain range of steering vector mismatch, but the selection of the constraint range of this algorithm affects the performance of the beamformer too much

In recent years, some improved beamforming algorithms based on existing algorithms have been proposed. For example, in 2012, Gu proposed a beamforming method for reconstruction of interference plus noise covariance matrix, but the impact of low snapshot number on algorithm performance is too big

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