A method for forming steady beam based on interfering noise covariance matrix estimation

Abstract

The present invention relates to the field of self-adaption beam forming during array signal processing, in particular, relates to a method for forming a steady beam based on an interfering noise covariance matrix estimation. The present invention includes using an antenna array to receive a distant field narrowband incident signal, using a limited snapshot number to estimate the covariance matrix for receiving data, then performing characteristic decomposition on the covariance matrix for receiving data, wherein prior information of the number of an incident signal source can be obtained via a method of estimating the number of the signal source; optimally obtaining a more accurate desired signal steering vector at a projection of a noise subspace according to an estimated desired signal steering vector, and performing estimation obtaining of the interfering noise covariance matrix according to interference signal steering vector prior information and an estimated noise power so as to perform beam forming. The present invention first performs the interfering noise covariance matrix estimation to get rid of the component of the desired signal in the training data, which can avoid the generation of signal cancellation.

Description

technical field [0001] The invention relates to the field of adaptive beamforming in array signal processing, in particular to a robust beamforming method based on interference noise covariance matrix estimation. Background technique [0002] Since the 1960s and 1970s, researchers began to gradually extend one-dimensional signal processing to the field of multi-dimensional signal processing, opening up a new important research field of array signal processing. Array signal processing is to arrange several or dozens of sensors into a sensor array at different positions in space according to a certain combination method, use it to receive and process spatial signals, extract signal features of useful signals, and analyze the information contained in the signals. Compared with the one-dimensional signal processing of the signal received by a single sensor, the sensor array has the advantages of flexible beam steering, high processing gain, strong interference suppression and hi...

AI Technical Summary

Problems solved by technology

However, in practical applications, the desired signal is often included in the received signal of the array, and errors such as waveform distortion, array element position error, signal direction of arrival (Direction of Arrive) estimation error, array element inconsistency and other errors will lead to the expected Error in signal steering vector

The Capon beamforming algorithm is very sensitive to the steering vector error. At this time, the desired signal will be suppressed as interference, resulting in the cancellation of the desired signal, resulting in a sharp drop in performance.

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