Robust covariance matrix diagonal loaded adaptive beam-forming method

Abstract

The invention discloses a robust covariance matrix diagonal loaded adaptive beam-forming method and mainly solves the problem of loading coefficient determining in the adaptive diagonal loading method in the prior art. The scheme includes: (1) calculating a covariance matrix of radar antenna array receiving signals; (2) solving a linear combination expression of adaptive weight vectors by aid of steering vectors of radar antenna array target signals; (3) solving an identical transformation expression of radar antenna array output power through the covariance matrix and the weight vector expression and defining the remained vectors; (4) constructing a covariance matrix of the remained vectors; (5) leading an inverse matrix of the covariance matrix of the remained vectors to serve as a weighting matrix in a two-step weighted least squares theory and solving loading coefficients of the covariance matrix of the radar antenna array receiving signals; and (6) calculating the adaptive weight vectors to perform beam-forming. The robust covariance matrix diagonal loaded adaptive beam-forming method improves beam-forming performance by adding a noise matrix to reduce covariance matrix eigenvalue dispersion degree.

Description

technical field [0001] The invention belongs to the technical field of array signal processing and is an important aspect of array processing. By performing diagonal loading calculation on the sample covariance matrix of the array output signal, the covariance matrix of the array output signal can be estimated more accurately. This loading technique can be used in beamforming, spatial spectrum estimation and other fields. Background technique [0002] Beamforming, also known as airspace filtering, is a major aspect of array signal processing. It is used in aviation, aerospace, radar and communication systems, and has gradually become one of the symbols of array signal processing. Its essence is to perform airspace filtering by weighting each array element. Filtering to achieve the purpose of enhancing the desired signal and suppressing the interference signal; and the weighting factor of each array element can be adaptively changed according to the change of the signal envir...

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Problems solved by technology

This loading algorithm is superior to the above two loading algorithms, but its computational load is particularly large, and in the process of solving the minimum mean square error of the covariance matrix, due to the lack of knowledge of the prior distribution information of the useful signal, the estimation operation There will be a large error, so the application of this algorithm is limited

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