Implementation method of adaptive signal processing based on Gaussian elimination

Abstract

The invention discloses an implementation method for adaptive signal processing based on Gaussian elimination, and the method comprises the steps of generating a corresponding echo vector according toan echo signal; calculating an autocorrelation matrix of the echo vector, calculating a generalized inner product value of the signal by adopting a Gaussian elimination method, screening the echo vector according to the generalized inner product value to generate a screening vector, calculating the autocorrelation matrix of the screening vector, and calculating a weighting coefficient by adoptingthe Gaussian elimination method; carrying out weighted summation on the echo vector, carrying out constant false alarm rate detection on a weighted summation result of any distance gate, and calculating an adaptive correlation estimation value of the echo signal by adopting a Gaussian elimination method when the signal-to-noise ratio of the distance gate is judged to be greater than a first preset threshold value; and when the adaptive correlation estimation value of the echo signal is greater than a second preset threshold, judging that a target corresponding to the distance gate exists. According to the technical scheme, the process of calculating the inverse matrix is avoided through the Gaussian elimination method, and therefore the implementation efficiency of the self-adaptive signal processing algorithm is improved.

Description

technical field [0001] The present application relates to the technical field of radar signal processing, in particular, to an implementation method of adaptive signal processing based on Gaussian elimination. Background technique [0002] Since there may be interference in the working environment, the radar system will receive the interference signal and the target echo signal at the same time, so it is necessary to suppress the interference signal and distinguish the authenticity of the target, usually using Adaptive Digital Beamforming (Adaptive Digital Beamforming) , ADBF), Space-Time Adaptive Processing (Space-Time Adaptive Processing, STAP) and other adaptive signal processing algorithms to process the echo signal, among them, calculate the generalized inner product value (Generalized Inner-Product, GIP), the optimal weighting coefficient And adaptive correlation estimation (Adaptive Coherent Estimation, ACE) is the core content of this kind of algorithm. [0003] How...

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Problems solved by technology

[0003] However, the existing technology usually adopts the strategy of directly calculating the inverse matrix of the autocorrelation matrix. This method of calculating the inverse matrix has a large amount of calculation and takes a long time, which seriously affects the implementation efficiency of adaptive signal processing algorithms such as ADBF and STAP.

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