摘要
考虑到空天飞行器飞行环境和运动特性下导航传感器误差的噪声统计特性不可能完全精确已知,若使用常规卡尔曼滤波进行在线标定,将会导致滤波精度下降甚至发散。设计一种基于新息自适应滤波方法的惯性测量单元(IMU)误差在线标定方案和算法,克服常规卡尔曼滤波需预先知道噪声统计特性的不足,设计包含IMU安装误差、刻度因子误差和随机常值误差在内的27维高阶状态变量的误差标定模型,分析提出可同时对系统噪声和量测噪声协方差矩阵进行动态调整的新息自适应滤波在线标定算法。仿真验证实验表明,相较于采用常规卡尔曼滤波以及Salychev O自适应滤波算法进行在线标定,所设计的新息自适应滤波在线标定方法能更有效实现对IMU误差的动态标定及补偿,进一步提高了惯性导航系统精度。实物验证实验表明,该方法可有效标定IMU误差残差,提高导航精度,为工程应用带来较大便利。
Considering the flight environment and motion characteristics of aerospace vehicle, the noise statistical characteristics of the navigation sensors＇ errors can＇ t be completely known, which may serious- ly degrade the filtering precision or even cause filtering divergence if the conventional Kalman Filter is used. An online calibration method for IMU errors of SINS based on the innovation-based adaptive filtering is proposed, which can overcome the weakness of that the conventional Kalman filter should know the statistical characteristics of the system noise and measurement noise in advance. An error calibration model of 27-D high-order state variables is established, including the installation error, scale factor error and random constant error of IMU, and an online calibration algorithm based on the innovation-based adaptive filtering is proposed, which can adjust the covariance matrices of system noise and measurement noise dynamically. Simulation shows that the proposed method performs higher calibration accuracy and better navigation performance compared to the conventional Kalman filter and Salychev 0 adaptive filte ring algorithm. It is proved by the field test that this method could calibrate the IMU residual errors effec- tively, improve the navigation accuracy and bring a great convenience for engineering application.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2016年第7期1203-1213,共11页
Acta Armamentarii
基金
国家自然科学基金项目(61533008
61533009
61374115)
国家留学基金委资助项目(2012年)
江苏省六大人才高峰资助项目(2013-JY-013)
江苏省高校优势学科建设工程项目(2014年)
中央高校基本科研业务费专项资金项目(NP2015406
NJ20150012
NP20152212
NS2014031)
南京航空航天大学研究生创新基地(实验室)开放基金项目(kfjj20150315)
关键词
控制科学与技术
惯性导航系统
惯性测量单元误差
在线标定
自适应滤波
control science and technology
inertial navigation system
inertial measurement unit error
online calibration
adaptive filtering
作者简介
王洁（1990-），女，硕士研究生。E-mail：wangjie813@nuaa．edu．ca；
熊智（1976-），男，研究员，博士生导师。E．mail：xznrc@nuaa．edu．cn
