摘要
为满足运载体长航时、高精度的导航需求,解决系统可观测性弱导致的航向角易发散的问题,提出了一种基于MEMS非线性组合导航系统的用于提高航向角估计精度的算法。通过采用单天线GNSS航向角作为量测量进行航向约束,解决了MEMS-SINS/GNSS姿态估计中航向角可观测性弱、估计值收敛差的问题;通过转弯判断规则和常规无迹卡尔曼滤波改进算法,抑制了偏流角对系统估计精度的影响。仿真结果表明,该算法有效地抑制了航向角估计精度差的问题,水平姿态精度达到0.01°,航向角精度达到0.1°,提高了系统的导航精度及可靠性。
In order to meet the long-endurance and high-precision navigation requirements of the vehicle,the divergence problem of the course angle caused by the weak observability of the system is solved.An algorithm based on MEMS nonlinear integrated navigation system to improve the accuracy of course angle estimation is proposed.The problems of weak observability and poor convergence of estimation value in MEMS-SINS/GNSS attitude estimation are solved by using GNSS course angle as a measure for course constraint.Through the turning judgment rule and the improved Sage-Husa adaptive unscented Kalman filter algorithm,the influence of the yaw angle on the attitude estimation accuracy is suppressed.The simulation results show that the algorithm effectively suppresses the problem of poor course angle estimation.The accuracy of horizontal attitude is 0.01°and the accuracy of course angle is 0.1°,which improves the accuracy and reliability of the system.
作者
程建华
王诺
尚修能
CHENG Jian-hua;WANG Nuo;SHANG Xiu-neng(College of Automation, Harbin Engineering University, Harbin 150001, China)
出处
《导航定位与授时》
2020年第3期112-119,共8页
Navigation Positioning and Timing
基金
国家自然科学基金重点项目(61633008)
黑龙江省杰出青年基金(JJ2018JQ0059)
中央高校基本科研业务费专项基金(HEUCFP201768)
国家自然科学基金(61773132)。
关键词
非线性
可观测性分析
航向角估计
自适应
无迹卡尔曼滤波
Nonlinearity
Observability analysis
Course angle estimation
Adaptive
Unscented Kalman filter
