基于可观测度反馈的SINS/DVL组合导航算法  

The SINS/DVL Integrated Navigation Algorithm Based on Observable Degree Feedback

作　　者：李志炜 岳崴[2] 高胜峰[2] 蔡鹏[2] 朱海荣[2] LI Zhi-wei;YUE Wei;GAO Sheng-feng;CAI Peng;ZHU Hai-rong(91001th Unit,the People’s Liberation Army of China,Beijing 100080,China;Navy Submarine Academy,Qingdao 266199,China)

机构地区：[1]中国人民解放军91001部队,北京100080 [2]海军潜艇学院,山东青岛266199

出　　处：《水下无人系统学报》2020年第2期155-161,共7页Journal of Unmanned Undersea Systems

摘　　要：针对捷联惯导/多普勒计程仪(SINS/DVL)组合导航中部分系统状态对无人水下航行器(UUV)导航精度影响较大但可观测性相对较弱的问题,提出一种基于可观测度反馈的SINS/DVL组合导航算法。该算法通过量化分析系统各状态参数的可观测性,根据系统状态参数在不同机动状态下可观测度不同的特点,构造基于可观测度反馈的自适应调节因子,增加高可观测度时的系统状态参数的估计占比,以此来提高组合导航滤波算法的适应性和滤波估计精度。利用湖试数据对上述算法的性能进行了验证。结果表明,可观测度反馈滤波算法累积误差明显小于常规卡尔曼滤波算法,在相同的精度要求下,可延长水下SINS/DVL组合导航自主航行的时间。Aiming at the problem that some system states in strap-down inertial navigation system(SINS)/Doppler velocity log(DVL) integrated navigation have significant influence on navigation accuracy but have relatively weak observability, a SINS/DVL integrated navigation algorithm based on observable degree feedback is proposed. The algorithm quantitatively analyzes the observability of each state parameter of the system, and constructs an adaptive factor based on observability feedback according to the fact that the observability of the system state parameters depends on maneuver states in order to increase the estimated proportion of state parameters when they have high observable degree, and so as to improve the adaptability and accuracy of the algorithm. The performance of the proposed algorithm is verified through lake trial, and the results show that the accumulated error of this observable degree feedback filtering algorithm is obviously smaller than that of the conventional Kalman filter algorithm, and the autonomous navigation time of the SINS/DVL integrated navigation can be prolonged under the same accuracy requirement.

关 键 词：无人水下航行器 组合导航 捷联惯导 多普勒计程仪 可观测度 

分 类 号：TJ630[兵器科学与技术—武器系统与运用工程] U666.1[交通运输工程—船舶及航道工程]