A Noise Reduction and Target Detection Method of FM Sequence Matrix Based on Low Rank Features

Abstract

The invention relates to a low-rank characteristic-based frequency modulation sequence matrix noise reduction and target detection method. The method includes the following steps that: received signals of L periods are continuously obtained, and the received signals are down-converted to a base band, and beat signals of L periods can be obtained; discrete sampling is performed on the beat signals, so that an L-row and N-column matrix S can be obtained; based on two sets of random sampling, nuclear norm optimization solution is performed obtained matrixes respectively, and a noise reduction result S' can be obtained; N<FFT>-point FFT is performed on each row of the matrix S', so that a matrix SR can be obtained; N<FFT>-point FFT is performed on each column of the matrix SR, so that a matrix SRD can be obtained; and two-dimensional average unit-ordered statistics constant false alarm rate detection is performed on the matrix SRD, and the distance and speed of a target are extracted. According to the method of the invention, nuclear norm optimization solution can be performed on the matrixes through utilizing a matrix filling theory according to the low-rank characteristics of signals, and therefore, noise reduction of the two-dimensional matrix can be realized, and a signal to noise ratio can be improved effectively; and based on the two-dimensional average unit-ordered statistics constant false alarm rate detection, noise estimation in Doppler domain can be improved, and problems existing multi-target detection can be solved.

Description

technical field [0001] The invention relates to the field of radar technology, in particular to a method for noise reduction and target detection of a frequency modulation sequence matrix based on low-rank features, and is especially suitable for noise reduction and multi-target detection of a two-dimensional matrix of frequency modulation sequence signals. Background technique [0002] Radar echo signals are usually accompanied by various noises, clutter and interference. The traditional noise reduction method is to filter out noise, clutter and interference by filtering, etc., but the effect of this method on improving the signal-to-noise ratio is not obvious. The detection of radar signals is carried out in the background of noise, clutter and interference. Modern radar adopts constant false alarm probability constant false alarm detection technology, but average unit constant false alarm detection has many shortcomings in the case of multiple targets, and Ordered statist...

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Problems solved by technology

[0002] Radar echo signals are usually accompanied by various noises, clutter and interference. The traditional noise reduction method is to filter out noise, clutter and interference by filtering, etc., but the effect of this method on improving the signal-to-noise ratio is not obvious

The detection of radar signals is carried out in the background of noise, clutter and interference. Modern radar adopts constant false alarm probability constant false alarm detection technology, but average unit constant false alarm detection has many shortcomings in the case of multiple targets, and Ordered Statistical CFAR Detection is Robust in Multi-Target Situations, but Requires High Computational Power

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