Adaptive estimation method for spatially non-uniform sea clutter covariance matrix

Abstract

The invention discloses an adaptive estimation method for a spatially non-uniform sea clutter covariance matrix. The method comprises the following steps of first performing NSCM (normalized sample covariance matrix) estimation by utilizing a reference sample to obtain an NSCM estimation value, and preprocessing the NSCM estimation value; then determining a normalized outer product matrix of the reference sample, and preprocessing the normalized outer product matrix; next calculating a weighting coefficient by utilizing preprocessing data obtained by the two preprocessing; and finally substituting the weighting coefficient into an estimation algorithm for a diagonally loaded adaptive covariance matrix to obtain a final covariance matrix estimation value. According to the method, the aim of adaptively reflecting statistical properties of sea clutters is fulfilled, the influence of clutter power on the performance of a detector is eliminated, and the problem of finite usable reference samples is solved; and the method can be applied to covariance matrix estimation under a non-uniform sea clutter background.

Description

technical field [0001] The invention relates to the technical field of radar signal processing, in particular to an adaptive estimation method of a space non-uniform sea clutter covariance matrix. Background technique [0002] At present, the estimation technology of the covariance matrix mainly realizes the estimation method of the covariance matrix by injecting the diagonal loading method of the noise matrix, for example, the invention patent applied by Xidian University: the robust adaptive beamforming method of the covariance matrix diagonal loading ( Patent application number: 201210484821.8, publication number: CN102944870A). Based on the HKB adaptive beamforming algorithm, this patent proposes a robust adaptive beamforming algorithm based on covariance matrix diagonal loading, and its loading varies adaptively with the number of samples. The patent application injects the noise matrix to reduce the dispersion of the eigenvalues ​​of the covariance matrix, and uses th...

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Problems solved by technology

The main deficiency of this patent is: the implicit condition of the diagonal loading algorithm is that it must be applicable in a spatially stable noise environment

The main shortcomings of this patent are: due to the existence of iterative operations, the amount of calculation is large, and the sea clutter environment is required to be uniform, and a large number of reference samples are required to ensure that the covariance matrix is ​​invertible

In practice, the sea clutter environment is non-uniform, resulting in a limited number of reference samples that can be used to estimate the covariance matrix

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