Energy Constrained Multi-platform Sonar Detection Performance

With the gradual increase of the sonar platform underwater sonar detection performance requirements, networking sonar system become more and more concerned about the field of study. Traditional single platform passive sonar system due to incomplete detection information, it is difficult to complete the goal of continuously accurate detection.Networking sonar system can fuse the detection results of each platform, in order to improve the detection performance. Problem of this paper is to establish networking sonar system detects model and platform configurations optimized according to the final detection results.Contents of this paper is divided into two parts, the regional network sonar detection performance model based on a single, multi-platform sonar equation is the main content of the first part of the detection model uses the resulting combination of particle swarm optimization algorithm to optimize the configuration of the first the main contents of the second parts.The first part,analyzes the basic characteristics of underwater acoustic channel, and using a ray acoustics software Bellhop to simulate propagation loss of networking sonar.Then next we analysis the characteristics of the marine environment noise, platforms noise,radiation noise, etc. Networking sonar systems are established in the noise field and developed simulation analysis. Secondly, because the operation in the offshore environment for active sonar systems seriously is affected by ocean reverberation, seabed reverberation works as the main limiting constraints particularly. Therefore, we studied the seabed scattering intensity model based on Voronovich small-slope approximation theory and Wurmser rough elastic seabed interface theory, establish networking sonar system physical model in shallow water reverberation field. Finally, under a variety of restrictions, establish networking sonar performance model. The model has a feature of the number and positions of the platforms, propagation characteristics, marine environment characteristics, target headings and other parameters adjustable. Forecast for the region to achieve detection performance,The second part, we first introduced the standard particle swarm optimization principles and characteristics and give the simulation analysis. Next, for the problem about networking sonar platform configurations we developed a standard particle swarm optimization based algorithm to improve the algorithm,namely sequential particle swarm optimization. And for the problem about how to select the new sonar platform to increase the coverage of detecting area, we developed two sub-algorithms Greedy and Hybrid, and used computer to compare the algorithms with simulation. Finally, we combined the network sonar system detection model established in the first part and the Greedy algorithm to give simulation analysis networking configuration optimization. Through the establishment of networking sonar detection model and combination with the optimization algorithm to optimize the configuration, we achieved nearly maximum area coverage.