Research On Distributed Cooperative Location Technology Of Single Underwater Target

As countries in the world pay more and more attention to the marine field,the research of underwater target detection and positioning technology is particularly important.Due to the increasing complexity of the modern naval battle environment,the traditional single-node detection and positioning system can no longer meet the requirements of diversified underwater target monitoring,so a multi-node coordinated system has emerged as the times require.It makes up for the shortcomings of a single node with a small area of action and a single functional form.It also improves the performance of the system in a larger geographic area and a more complex working environment.The thesis first studied the single-node detection and distributed collaborative detection methods.The principles of several common mean constant false alarm detectors are deduced in detail,and their advantages and disadvantages are observed through simulation.In the part of distributed collaborative detection,the principle analysis and simulation of K/N fusion and Neiman Pearson fusion are carried out.Under the bistatic layout,the influence of different distances between the transmitting station and the receiving station on the detection performance of the system is studied;under the one-transmit-two-receiving and one-transmit-three-receiving layouts,the detection probability and coverage of the system under different cooperative detection algorithms are studied.Secondly,the methods of bistatic positioning and distributed co-location are studied.Starting from the typical bistatic time-of-arrival(TOL)algorithm and the direction-of-arrival(BOL)algorithm,aiming at the blind area of the two algorithms in the baseline area,the paper carries out the research on the distributed collaborative positioning algorithm.Simulation analysis of the multi-static TOL algorithm,and in order to improve the positioning accuracy of the entire system,the theoretical derivation and simulation analysis of the linear least square algorithm and the data fusion algorithm are carried out.It focuses on the analysis of the positioning accuracy of the distributed system under different geometric layouts and different numbers of nodes.Then,in the process of linear least squares algorithm positioning,due to the improper selection of initial values,the positioning accuracy is reduced.A co-location algorithm based on adaptive weighted particle swarm optimization is designed,and the number of populations,the number of nodes and the layout are discussed.The influence of the method on the positioning error of the system.Simulation analysis shows that the performance of the algorithm in terms of target positioning accuracy and positioning success rate has been improved,and it is less affected by time measurement errors,and is more suitable for underwater environments.At the same time,in view of the problem of the loss of system positioning accuracy caused by the failure of distributed system nodes,an adaptive weighted particle swarm optimization algorithm based on k-means clustering is designed.Simulation analysis shows that after k-means algorithm clustering,the system’s positioning The accuracy has been significantly improved.Finally,part of the positioning algorithm was verified using Songhua Lake test data.