协方差交叉融合鲁棒Kalman滤波器

对于带未知互协方差的两传感器系统,提出一种协方差交叉（CI）融合鲁棒稳态Kalman滤波器,它关于未知互协方差具有鲁棒性.严格证明了该滤波器的实际精度高于每个局部滤波器的精度,但低于带已知互协方差的最优融合Kalman滤波器的精度.基于协方差椭圆给出了精度关系的几何解释.进一步将上述结果推广到一般多传感器情形.一个跟踪系统的Monte-Carlo仿真例子表明,其实际精度接近于带已知互协方差的最优融合器的精度.

Covariance intersection fusion robust steady-state Kalman filter

For two-sensor systems with unknown cross-covariance,a covariance intersection(CI) fusion robust steady-state Kalman filter is presented,which has robustness with respect to unknown cross-covariances.It is rigorously proved that its the actual accuracy of the fitter is higher than that of each local filter,and is lower than that of the optimal fusion Kalman filter with known cross-covariance.The geometric interpretation of the accuracy relations is given based on the covariance ellipses.Further,the above results are extended to the multisensor case.A Monte-Carlo simulation example for a tracking system shows that its actual accuracy is close to that of the optimal Kalman fuser with known cross-covariance.