摘要
提出了一种解决时变噪声条件下传递对准的改进自适应平方根滤波算法。该算法将状态方差调节因子阵、自适应调节的系统噪声和量测噪声方差以及噪声有限记忆尺度融入平方根滤波结构中,采用序列算法滤波解算。算法通过一步控制和多步自适应调节过程,以较少的计算量从数值计算、噪声抑制及自适应调节方面提高滤波性能。仿真结果表明,该算法滤波稳定性强,能够根据实际噪声快速调整,且滤波精度高,为机载导弹提供了一种有效的快速精确传递对准方法。
An improved adaptive square root filtering algorithm for solving transfer alignment under time varying noise is designed.In the algorithm,the state covariance adjusting factor matrix,adaptive adjusting system noise and measurement noise covariance,as well as the infinite noise memory scale are incorporated into the square root filtering structure which is computed by a sequential filtering algorithm.Through one-step controlling and multi-step adaptive adjusting process,the performance in numerical computing,noise refraining and adaptive adjusting of the algorithm is remarkable improved with low calculation cost.Simulation results show that the algorithm possesses strong stability,high filtering accuracy and is capable of quickly adjusting according to the real noise,which provides an effective rapid and accurate transfer alignment method.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2011年第3期622-626,共5页
Systems Engineering and Electronics
关键词
传递对准
自适应滤波
平方根滤波
机载导弹
卡尔曼滤波
transfer alignment
adaptive filtering
square root filtering
airborne missile
Kalman filtering
