Research on passive acoustic localization algorithm based on multi-stage neural network
.基于多级神经网络的被动声定位算法研究*

In order to solve the problems of precise mathematic model which is hard to establish, nonlinearity when solving the position equations and multi-array data fusion, a passive acoustic localization algorithm based on multi-stage neural network was presented. The location of sound source was obtained by the first stage RBF neural network, which may include invalid data eliminated by decision rule. The valid data entered the second stage RBF neural network, and get the higher precision of localization. The performance of the algorithm based on multi-stage neural network was simulated. The simulation results indicated that passive acoustic algorithm based on multi-stage neural network can improve the localization accuracy, positioning speed and robustness, and its performance is better than the algorithm based on single RBF neural network and the traditional algorithms. Even after individual sensors fail, it works well.