水下滑翔器位姿估计的改进高斯混合粒子滤波器设计与验证（英文）  

Design and verification of improved Gaussian mixture particle filter for position and attitude estimation of underwater glider

作　　者：黄浩乾[1,2] 陈熙源[1,2] 吕才平 周智恺[1,2] 赵伟洪 

机构地区：[1]东南大学 仪器科学与工程学院,南京210096 [2]微惯性仪表与先进导航技术教育部重点实验室,南京210096

出　　处：《中国惯性技术学报》2014年第5期601-605,共5页Journal of Chinese Inertial Technology

基　　金：海洋公益性行业科研专项经费资助(201205035);国家自然科学基金(51375087);高等学校博士学科点专项科研基金资助课题(20110092110039);江苏省研究生创新项目(No.CXLX12_0082)

摘　　要：近年用于水下滑翔器的低成本导航系统成为研究热点,导航器件的成本与精度之间的折中问题仍然是目前的难题。针对因使用低成本的导航元件而造成低精度位姿估计的问题,提出用于位姿估计的改进高斯混合粒子滤波(IGMPF)方法。用高斯混合模型来估计非高斯噪声,改进的粒子滤波进一步提高位姿估计精度。为了验证其效果,该方法应用于自主设计的水下滑翔器导航系统中并做了车载实验,实验结果表明所提IGMPF方法在实际应用中比传统的EKF和UKF表现更优,姿态角和位移误差比EKF和UKF减小了至少30%。For the last few years, low cost navigation system applied to the underwater glider becomes a research hotspot, and the trade-off between accuracy and cost for navigation sensors is still a difficult problem currently. Aiming to the low accuracy of position and attitude estimation due to using low-cost navigation components, this paper proposes a novel improved Gaussian mixture particle filter (IGMPF) method for position and attitude estimation. By using the Gaussian mixture model to estimate the non-Gaussian noise, the improved particle filter further improves the position and attitude estimation accuracy. For verification, this method is implemented in the new underwater glider navigation system designed in our lab. A vehicle experiment is made to assess the performance of the proposed method. The results show that the proposed IGMPF method is better than the conventional EKF and UKF in the practical application with the attitude error and the position error reduced by ≥30% compared with EKF and UKF.

关 键 词：惯性导航系统 位姿估计 高斯混合 改进粒子滤波器 

分 类 号：TN713[电子电信—电路与系统]