An effective method for underwater target radiation signal detecting and reconstructing

Abstract

Using the sparse feature of the signal, compressed sensing theory can take a sample to compress data at a rate lower than the Nyquist sampling rate. The signal must be represented by the sparse matrix, however. Based on the above theory, this article puts forward a sparse degree of adaptive algorithms which can be used for the detection and reconstruction of the underwater target radiation signal. The received underwater target radiation signal, at first, transits the noise energy into signal energy under test by the stochastic resonance system, and then based on Gerschgorin disk criterion, it can make out the number of underwater target radiation signals in order to determine the optimal sparse degree of compressed sensing, and finally, the detection and reconstruction of the original signal can be realized by utilizing the compressed sensing technique. The simulation results show that this method can effectively detect underwater target radiation signals, and they can also be detected quite well under low signal-to-noise ratio(SNR).