Research On Time Delay Estimation And Location Algorithm For Underwater Acoustic Positioning System

The 21st century is the era of the ocean,and the country is paying more and more attention to the development of the ocean industry.Whether it is the development of marine resources,national marine security or scientific research,underwater acoustic positioning technology is needed to navigate and locate underwater targets to provide a basic guarantee.Therefore,the research on technologies of underwater acoustic positioning system is of great significance.However,the characteristics of the underwater acoustic channel are complex,and the research of high-reliability positioning technology has become a very challenging task.In this paper,the underwater acoustic signal delay estimation and target location and tracking under the condition of complex marine noise and channel are studied respectively.The specific work is as follows:(1)Briefly introduce the basic characteristics of the underwater acoustic channel,use the ray theory to describe the underwater acoustic channel propagation model,and use alpha stable distribution to model the marine noise,and through numerical simulation noise and measured ocean noise verify the applicability of the model.(2)Aiming at the defect that the accuracy of traditional estimation algorithms suffering from the limited sampling rate and it is difficult to correctly estimate the time delay under low signal-to-noise ratio,a correlation peak refinement time delay estimation algorithm based on stochastic resonance is proposed.The algorithm can achieve low signal-to-noise ratio and high-precision time delay estimation under the Gaussian or weak non-Gaussian noise.Aiming at the low characteristic index of alpha stable distribution noise,that is,under the condition of strong impulse interference noise,an improved variable step size Hassab-Boucher(HB)weighted adaptive time delay estimation algorithm based on correlation entropy is proposed.Simulation analysis shows that the proposed algorithm works under different impulse interference levels.Both can show good estimation performance and have strong toughness.(3)Aiming at the problem that the traditional positioning algorithm is easy to deteriorate when the underwater acoustic channel is complex,that is,the measurement error is large,a Time Difference Of Arrival(TDOA)positioning optimization method based on the hybrid particle swarm gravitation search algorithm with acceleration factor is proposed,and the simulation shows the proposed method can converge to the optimal solution faster and improve positioning accuracy and stability.Aiming at the poor realtime positioning of the above optimization method,a positioning and tracking method based on the maximum correlation entropy Kalman filter is proposed.The result of the Chan algorithm is estimated by the maximum correlation entropy Kalman filter for secondary estimation,which effectively improves the positioning and tracking of the algorithm.The accuracy and the performance of suppressing outliers ensure the real-time performance of the algorithm.