Array data covariance matrix inversion method based on iterative dimension reduction processing

The invention relates to the technical field of sonar signal processing, in particular to an array data covariance matrix inversion method based on iterative dimensionality reduction processing, which adopts a dimensionality reduction processing mode of matrix partitioning, comprehensively utilizes the Hermitian property of an array data covariance matrix, and improves the inversion accuracy of the array data covariance matrix. According to the method, the inversion speed of the array data covariance matrix in the adaptive array processing can be effectively improved, the error of approximate inversion is very small, and the effect of the adaptive array processing is not influenced. 本发明涉及声纳信号处理技术领域，尤其是一种基于迭代降维处理的阵列数据协方差矩阵求逆方法，采用矩阵分块的降维处理方式，综合利用阵列数据协方差矩阵的Hermitian性质，本发明能够有效提高自适应阵列处理中阵列数据协方差矩阵求逆的速度，并且近似求逆的误差很小，不影响自适应阵列处理的效果。