Research On Time Delay Estimation Algorithm Of Underwater Acoustic Pulse Signal Under Low SNR

The research on time-delay estimation of underwater acoustic pulse signal has always been the key research content of underwater acoustic workers.Based on the overview of the historical development and research of adaptive filtering technology and time-delay estimation methods,this paper focuses on the adaptive filtering algorithm based on the minimum mean square error criterion and the time-delay estimation method based on correlation analysis and adaptive processing technology under the condition of low signal-to-noise ratio(SNR),and conducts an in-depth discussion and research.The noise suppression algorithm using adaptive filtering is studied.In order to overcome the problem that the estimation performance of traditional time delay estimation methods significantly degrades under low SNR conditions,a new and improved variable step size(MVSS-LMS)adaptive algorithm is proposed based on the idea of variable step size with the help of adaptive noise canceler principle.Meanwhile an improved sparse norm constraint(PNPRLMS)adaptive algorithm is proposed by making full use of the sparse characteristics of underwater acoustic channel,which lays a good foundation for the introduction of subsequent delay estimation methods.The time delay estimation method based on correlation analysis is studied.The basic signal model of time delay estimation is established and its evaluation criteria is given.Several typical time delay estimation methods are deduced,and the characteristics and applicable conditions of various methods are summarized.The generalized cross-correlation time delay estimation method based on noise cancellation preprocessing is introduced here.That is to do basic crosscorrelation analysis on the two received signals after filtering preprocessing.Aiming at the performance degradation of traditional cross-correlation estimation under the condition of low signal-to-noise ratio,propose an amplitude weighted cross-correlation time delay estimation algorithm based on PN-PRLMS filtering.Compared with other preprocessing basic crosscorrelation methods,the estimation performance of this algorithm is slightly improved.The adaptive time delay estimation method based on minimum mean square error is studied.This paper analyzes the performance of the LMSTDE algorithm and compares it with the amplitude weighting method,makes improvements for the drawback of the fixed step size of the LMSTDE algorithm,and proposes a sparse parametric constrained adaptive time delay estimation(Lp-LMSTDE)algorithm in combination with the PN-PRLMS filtering algorithm,but the estimation performance of this algorithm is degraded compared with the amplitude weighting method in a certain range of SNR.In view of this disadvantage,by analyzing the characteristics of hyperbolic cosine function,a variable step size adaptive time delay estimation based on hyperbolic cosine function is proposed(cosh-LMSTDE)algorithm,the performance of the algorithm is better than the Lp-LMSTDE algorithm,under the condition of low signalto-noise ratio,it has approximate estimation error with amplitude weighting method,but has higher estimation efficiency.The feasibility of the above algorithm is verified by simulation analysis.