摘要
首先介绍了粒子滤波中自举滤波的原理和算法,说明该算法可用于处理非线性系统的状态估计问题。进而列出了捷联惯导系统速度误差方程和姿态误差方程,并将其用于惯导系统非线性对准。最后,通过对仿真结果的分析,指出通过结合粒子滤波和传统的扩展卡尔曼滤波,可以得到一种精度优于卡尔曼滤波,而计算量小于粒子滤波的非线性滤波方法。
The bootstrap filter, as a kind of particle filter, is discussed in this paper. This method could be used in non-linear estimation system. Error model of strapdown inertial navigation system (SINS) is derived and used in SINS alignment. The analysis shows that the particle filter and the Kalman filter could combine to form a new algorithm whose performance is low computational load and high precision. Finally, an example is showed to demonstrate the validity of the method.
出处
《中国惯性技术学报》
EI
CSCD
2003年第6期20-26,共7页
Journal of Chinese Inertial Technology
