Underwater Positioning Based on an Artificial Lateral Line and a Generalized Regression Neural Network

作     者：Xiande Zheng Yong Zhang Mingjiang Ji Ying Liu Xin Lin Jing Qiu Guanjun Liu 

作者机构：Science and Technology on Integrated Logistics Support Laboratory National University of Defense Technology Changsha 410073 China College of Intelligence Science National University of Defense Technology Changsha 410073 China 

出 版 物：《Journal of Bionic Engineering》 (仿生工程学报（英文版）)

年 卷 期：2018年第15卷第5期

页      面：883-893页

核心收录：

学科分类：12[管理学] 08[工学] 0710[理学-生物学] 0831[工学-生物医学工程（可授工学、理学、医学学位）] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0836[工学-生物工程] 0811[工学-控制科学与工程] 0702[理学-物理学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The author appreciates the support of the National Natural Science Foundation of China (Grant Nos. 51675528 and 51605482 as well as the National Key R&D Program of China (Grant No. 2016YFF0203400). The author also thanks Kehong Lv and Peng Yang for guiding in the design of the experimental platform. Besides  the author thanks Qin Wang and Bailiang Chen for assisting in the fabrication of the sensor array and the experimental platform 

主　　题：lateral line underwater positioning generalized regression neural network bionics 

摘      要：Taking advantage of the lateral line organ, fish can navigate, feed, and avoid predators and obstacles by sensing surrounding flow fields. The lateral line organ provides an important reference for the development of new underwater detection technology. Inspired by the lateral line organ, in this paper, for the sake of localizing the target dipole source in three-dimensional underwater space, an artificial lateral line consisting of nine underwater pressure sensors forming a cross-shaped sensor array is applied. Combined with the method of gener- alized regression neural network, which is suitable for solving nonlinear pattern recognition problems, a corresponding experimental platform has been built to sample data for training the neural network from a 12 cm by 12 cm by 24 cm cuboid space. The experimental results indicate that the cross-shaped artificial lateral line can localize the target dipole source two body-lengths away. The well- performing perceptual distance is below 13 cm away from the sensing array. Moreover, decreasing the data sampling interval and in- creasing the number of sensors utilized can help improve the positioning accuracy.