摘要
针对自主式水下无人航行器的地形辅助导航问题,提出一种基于粒子滤波的地形辅助定位方法。为了解决粒子滤波的“粒子贫化”问题,引入了辅助采样,提出一种基于辅助采样粒子滤波的海底地形辅助定位方法,减小了由于重采样带来的粒子多样性的损失。基于半物理测试平台的仿真实验表明:本文所提出方法的精度较高,可适应不同地形特征下的地形辅助定位,可满足水下无人航行器(autonomous underwater vehicle,AUV)水下导航定位的需求。
Focusing on the seabed terrain-aided navigation of autonomous underwater vehicle(AUV),a terrain-aided positioning method based on the particle filtering method is proposed in this study.To solve the particle depletion problem of the particle filtering method,the auxiliary sampling technology is introduced.Then,a terrain-aided positioning method based on the auxiliary sampling particle filtering method,which can reduce the loss of particle diversity caused by resampling,is proposed.Simulation tests based on the semi-physical test platform show that the proposed method has high terrain positioning accuracy and strong adaptability to terrain features,which can meet the demand of AUV navigation.
作者
韩月
陈鹏云
沈鹏
HAN Yue;CHEN Pengyun;SHEN Peng(Modern Education Information Centre,Taiyuan Tourism College,Taiyuan 030032,China;College of Mechatronic Engineering,North University of China,Taiyuan 030051,China;National Deep Sea Centre,Qingdao 266237,China)
出处
《智能系统学报》
CSCD
北大核心
2020年第3期553-559,共7页
CAAI Transactions on Intelligent Systems
基金
国家自然科学基金项目(51909245)
山西省自然科学基金项目(201901D211244,201801D221210)
山西省高等学校科技创新项目(2019L0537)
高性能舰船技术教育部重点实验室基金项目(gxnc19051802).
关键词
水下无人航行器
水下环境
多波束测深
地形辅助定位
Bayesian估计
粒子滤波
辅助采样
半物理仿真
autonomous underwater vehicle
underwater environment
multi-beam sounding
terrain-aided positioning
Bayesian estimation
particle filter
auxiliary sampling
semi-physical simulation
