摘要
针对捷联惯导系统静基座自对准过程中常规卡尔曼滤波器估计精度低且易发散的问题,提出了一种复合自适应卡尔曼滤波算法.该算法采用衰减记忆法利用信息实时估计系统噪声方差阵,并基于模糊推理的自适应因子调节滤波增益阵和系统噪声阵.仿真验证了该自适应算法较常规卡尔曼滤波有更强的稳定性和更高的滤波估计精度.
A complex adaptive Kalman filtering algorithm is presented by analyzing the characteristic of stationary alignment of SINS seriously. The algorithm can be used to estimate the eovariance matrix of system noise in real time by innovation vectors. When a divergent trend is found, the gain matrix and covariance matrix of system noise are tuned simultaneously by adaptive factor, which is acquired through fuzzy inference system. The simulation results show that the complex adaptive Kalman filter outperforms the standard Kalman filter with stronger robustness and better accuracy.
出处
《战术导弹技术》
2009年第1期70-74,共5页
Tactical Missile Technology
