水下运载体相对浮标定位的神经网络模型

Neural Network Positioning Model of Underwater Vehicle Relative to Buoy

提出一种用普通浮标结合训练好的BP神经网络代替声学浮标,将信号浮标位置向水下延伸,进行水下运载体定位的方法。仿真表明,本方法可行,其对提高水下运载体浮标定位系统的经济性具有重要意义。

This article presents a positioning method of underwater vehicle. It extends the position of the signal buoy to underwater vehicle, the acoustic buoy also has been replaced by the common buoy and BP neural network. The feasibility of the method can be illustrated by simulation. In conclusion, it is economical to the positioning system of the underwater vehicle depending on buoy.