摘要
无人水下航行器(UUV)协同导航过程中,惯性导航系统(INS)在水下工作时的定位误差随时间累积,在不升出天线的情况下,难以利用全球定位系统(GPS)对惯导误差进行修正,地磁导航虽可以在水下修正惯导系统的误差,但传统的地磁匹配导航对先验地磁图过于依赖。受到生物利用地磁进行导航行为的启发,文中针对多UUV仿生协同导航问题,提出一种基于粒子群优化(PSO)算法的多UUV仿生协同导航方法,将导航过程归结为多目标搜索问题,通过共享UUV间的信息,完成导航任务,实时对惯导系统进行定位误差的修正。仿真结果证实了该方法的有效性。
Global positioning system(GPS) cannot be used to correct the accumulated inertial navigation positioning error when inertial navigation system(INS) works underwater. Although traditional geomagnetic matching navigation can solve this problem, this navigation method relies too much on prior geomagnetic map. The authors are inspired by the fact that some of living beings use geomagnetism for navigation, and propose a multi-unmanned undersea vehi- cle(UUV) bionic cooperative navigation algorithm based on particle swarm optimization. The navigation process is re- duced to a multi-objective search problem. Then the navigation tasks are accomplished by sharing the information among UUVs, and the positioning errors of the INS are corrected in real time. Simulation result verifies the effectiveness of the proposed method.
作者
王磊
王国臣
范世伟
WANG Lei;WANG Guo-chen;FAN Shi-wei(The First Military Representative Office of the Navy in Harbin,Harbin 150046,China;School of Instrumental Science and Engineering,Harbin Institute of Technology,Harbin 150001,China)
出处
《水下无人系统学报》
北大核心
2019年第3期272-276,共5页
Journal of Unmanned Undersea Systems
关键词
无人水下航行器
协同导航
仿生导航
粒子群优化算法
unmanned undersea vehicle(UUV)
cooperative navigation
bionic navigation
particle swarm optimization(PSO) algorithm
