林雪原, 衣晓. 一种基于分步式滤波的多传感器组合导航系统算法研究[J]. 武汉大学学报 ( 信息科学版), 2011, 36(7): 811-815.
引用本文: 林雪原, 衣晓. 一种基于分步式滤波的多传感器组合导航系统算法研究[J]. 武汉大学学报 ( 信息科学版), 2011, 36(7): 811-815.
LIN Xueyuan, YI Xiao. Study on One Multi-Sensor Integrated Navigation System Algorithm Based on Filtering Step by Step[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 811-815.
Citation: LIN Xueyuan, YI Xiao. Study on One Multi-Sensor Integrated Navigation System Algorithm Based on Filtering Step by Step[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 811-815.

一种基于分步式滤波的多传感器组合导航系统算法研究

Study on One Multi-Sensor Integrated Navigation System Algorithm Based on Filtering Step by Step

  • 摘要: 提出了一种多传感器组合导航系统的分步滤波算法。当所有传感器的观测值到来时,首先对该时刻的系统状态进行预测,然后利用常规卡尔曼滤波器和各导航传感器的观测值依次对该时刻的状态向量估计值进行更新,进而得到该时刻状态向量基于全局信息的最优融合估计。最后利用GPS/SST/高度表/SINS多组合导航系统对上述算法进行验证。仿真结果表明,该算法与集中式卡尔曼滤波算法的估计精度相同,但计算量得到降低。

     

    Abstract: One of normal algorithm for multi-sensor integrated navigation system is centralized Kalman filter which has the shortcoming of heavy computation burden and bad fault-tolerant.Thus,this paper puts forward one filtering step by step algorithm for multi-sensor integrated navigation system,when the observation values of all sensors come together,firstly the system state at this time is predicted,then the conventional Kalman filter and every navigation sensor's observation are used to update the estimate value of this time's state vector in turn.Accordingly the optimal fused estimated value of this time's state vector can be obtained based on the global information.At last the GPS /SST/altimeter/SINS integrated navigation system is used to examine the above algorithm,the simulated results show that this algorithm has the same estimated precision as the centralized Kalman filter,but has lower computation burden.

     

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