摘要
目前地磁仿生导航大多是基于进化策略的搜索导航,导航耗时长、效率低。针对这一问题,提出一种基于进化梯度搜索的AUV地磁仿生导航方法。将仿生的进化搜索算法与经典梯度算法结合起来搜索函数极值,不仅可以保证搜索具有全局最优性,而且具有快速的收敛性,可以提高地磁仿生导航的效率。仿真结果表明,该方法不需要先验地磁信息,可以依据地磁趋势完成导航任务。通过与传统仿生导航的进化搜索策略对比,验证了进化梯度搜索策略的有效性和优越性。
At present,bio-inspired geomagnetic navigation is mostly based on evolutionary strategy,which requires long navigation time and low efficiency.To solve this problem,a bio-inspired geomagnetic navigation method for AUV based on evolutionary gradient search is proposed.Combining the bionic evolutionary search algorithm with the classical gradient algorithm to search the function extremum can not only ensure the global optimization of the search,but also have fast convergence,which can improve the efficiency of bio-inspired geomagnetic navigation.The simulation results show that this method does not need prior geomagnetic information and can complete navigation tasks according to the geomagnetic trend.Comparing with the evolutionary search strategy,the effectiveness and superiority of the evolutionary gradient search strategy are verified.
作者
郭娇娇
刘明雍
刘坤
牛云
王梦凡
GUO Jiaojiao;LIU Mingyong;LIU Kun;NIU Yun;WANG Mengfan(School of Marine Science and Technology, Northwestern Polytechnical University, Xi′an 710072, China)
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2019年第5期865-870,共6页
Journal of Northwestern Polytechnical University
基金
国家自然科学基金(51679201,51879219)
水下信息与控制重点实验室开放项目(6142218051806)
中央高校基本科研业务费专项资金(3102019HHZY030027)资助
关键词
地磁场
地磁导航
仿生导航
进化策略
进化梯度搜索
geomagnetism,geomagnetic navigation
bio-inspired navigation
evolutionary strategies
evolutionary gradient search
