摘要
针对自主式水下无人航行器(AUV)长时间潜航时的精确导航定位需求,以多波束测深系统为水下地形测量设备,提出一种基于贝叶斯估计的AUV水下地形匹配导航模型。针对贝叶斯滤波后验概率密度函数的求解问题,用高斯混合密度函数近似状态的后验概率密度函数,提出了基于高斯和粒子滤波的水下地形匹配导航方法。基于多波束测深数据的回放式仿真试验表明,提出的方法可以有效近似地形匹配的贝叶斯滤波模型,具有良好的实用性。
Aiming at the need for accurate navigation and positioning during long-term submergence of autonomous underwater vehicles,a multibeam sounding system is used as a submarine terrain measurement device,and an AUV subsea terrain matching navigation model based on Bayesian filtering is proposed.Aiming at the problem of solving the Bayesian filtering posterior probability density function,a Gaussian mixed density function is used to approximate the state of the posterior probability density function,and a seabed terrain matching navigation method based on Gaussian and particle filtering is proposed.The playback simulation experiments based on multi-beam sounding data show that the method proposed in this paper can effectively approximate the Bayesian filter model of terrain matching and has good practicability.
作者
韩月
陈鹏云
沈鹏
HAN Yue;CHEN Pengyun;SHEN Peng(College of Mechatronic Engineering,North University of China,Taiyuan 030051,China;Modern Education Information Centre,Taiyuan Tourism College,Taiyuan 030032,China;National Deep Sea Centre,Qingdao 266237,China)
出处
《无人系统技术》
2020年第1期48-54,共7页
Unmanned Systems Technology
基金
国家自然科学基金(51909245)
高性能舰船技术教育部重点实验室开放课题(gxnc19051802)
山西省高等学校科技创新项目(2019L0537)。
关键词
自主水下航行器
贝叶斯估计
粒子滤波
高斯和函数
地形辅助导航
回放式仿真
Autonomous Underwater Vehicle
Bayesian Estimation
Particle Filtering
Gaussian Sum Function
Terrain-Aided Navigation
Playback Simulation
