Research On Underwater Target Signal Detection Technology Based On Permutation Entropy And Constant False Alarm Detection

Underwater target signal detection is one of the important contents of underwater detection.In practical applications,problems such severe natural or artificial signal interference brings difficulties to the underwater target signal detection and affects the detection system's performance.This article focuses on co-frequency signal interference to improve the performance of underwater target detection?1.Simulation analysis of several signal detection methods,including: Power-Law detection method,entropy detection and methods based on higher-order statistics.Simulation results show that in the case of interfering signals,the classic underwater acoustic signal detection algorithm mistaken the interference and targets,which may increase the false alarm probability of detection;fixed detection thresholds are difficult to meet the signal detection under low signal-to-noise ratio and background mutation caused by the interference environment demand.2.In order to solve the influence of interference signal,this paper gives a multi-scale permutation entropy(MPE)detection.Through simulation verification,it can be found that the MPE detection algorithm has a certain suppression effect to signal interference.Based on the MPE,an improved wavelet transform-multiscale permutation entropy(WT-MPE)and an empirical mode decomposition-multiscale permutation entropy(EMD-MPE)are given.Through simulation analysis,it is found that the detection performance of the WT-MPE and the EMD-MPE is better than the MPE under the condition of low signal-to-noise ratio.3.In order to solve the problem of environmental change in 1,constant false alarm rate detector and Notch filter are combined to provide a constant false alarm rate detection method based on Notch filter.Through simulation analysis,the threshold of the constant false alarm detection method based on the Notch filter is adaptive and can solve the problem of environmental change.4.This paper uses different detection algorithms to test the experimental data of the pool experiment and the Qiandao Lake experiment.And analyze its detection performance.It is proved that the improvement of the MPE detection algorithm improves the detection performance of the algorithm.The constant false alarm threshold is changed with the change of environmental noise.The main work of this paper is mainly reflected in the improved MPE algorithm and the adaptive Notch-based constant false alarm rate detection algorithm.It has performered ideal performance by simulation and data processing.