| The ocean covers approximately two-thirds of the surface of the Earth.The ocean plays an important role in maintaining and protecting the stability of ecosystems.Strong ocean exploration capabilities have become an important requirement for modern national defense and ocean exploration.Currently,sonar has become an important means of detecting underwater environments with its effective detection capabilities.However,the detection range of a single sonar limits its applicability to underwater environments,and the strong noise and weak communication characteristics of underwater environments also pose great challenges.Therefore,this article focuses on the problem of target detection in underwater acoustic sensor networks and studies the target detection algorithm of sensor networks under decision fusion.The main work of this article is as follows:Firstly,a fusion algorithm based on Bayesian method is proposed for target detection in sensor networks with unknown power and position.Firstly,a fusion detection framework for underwater sensor networks was designed.Then,using the measurement model of passive sensor nodes,a decision algorithm for local sensor nodes was proposed.Then,based on the local decision of each sensor node,a decision statistic based on Bayesian method was derived,and the existence of the target was determined based on the comparison with the threshold.Finally,performance analysis was conducted on the mentioned algorithm,and corresponding simulations verified the effectiveness of the algorithm.Secondly,to address the problem of high false alarm rates caused by strong noise and weak communication in underwater environments,a target detection algorithm based on active passive fusion was designed for underwater sensor networks.Firstly,an active and passive measurement model was utilized to design a local decision weight algorithm based on chi square test,achieving local decision-making under active and passive detection.Then,considering the communication energy consumption and threshold optimization of underwater sensor networks,a hybrid Bayesian decision fusion algorithm based on a two-layer multi group structure was designed.The communication transmission protocol under two-layer multi group structure was proposed,and the test statistics based on the hybrid Bayesian decision fusion algorithm were derived.Based on the comparison of statistics and thresholds,the fusion detection of the system was achieved,further improving the detection performance of the system.Finally,performance analysis was conducted on the system,and the effectiveness of the algorithm was verified through simulation results. |
