Suboptimal Filter Algorithm of Initial Alignment in Inertial Navigation System
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摘要: 分析了惯导系统(INS)初始对准的动态误差向量方程及其动态误差向量的可观性问题,并研究了按动态误差向量的可观度划分观测子空间.在惯导系统初始对准问题中通过使用变量可观度的概念构造次优卡尔曼估计算法.并用C语言编程实现了初始对准的最优及次优卡尔曼滤波算法.从仿真结果可见次优卡尔曼滤波算法可用于INS初始对准的实用计算中.Abstract: The dynamic error vector equation of the initial alignment in an inertial navigation system and the observability problem of the dynamic error vector are analysed.The system state space is divided into observable subspaces by using the observable degree of the dynamic error vector.In the initial alignment problem of an inertial navigation system, a suboptimal Kalman filter algorithm is constructed by using the concept of the observable degree of a variable.The optimal Kalman filter algorithm and the suboptimal Kalman filter algorithm of the initial alignment are realized by using C language to programming.Simulation results show that the proposed suboptimal Kalman filter algorithm is available to the initial alignment in an inertial navigation system.
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Key words:
- inertial navigation /
- observability /
- Kalman filtering /
- initial alignment
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