多传感器时滞系统CI融合滤波算法

Fusion filtering algorithm for multi-sensor delay Systems based on CI algorithm

针对多传感器信息融合时存在的时滞问题,建立了带状态和观测时滞的传感器网络移动目标追踪仿真模型,利用增广矩阵将时滞系统化为非时滞系统,提出了多传感器时滞系统协方差交叉(covariance intersection,CI)融合滤波算法。该方法避免了计算任意2个局部滤波误差互协方差阵,极大地减小了计算量与计算时间。分析了该方法的精度,比较了CI融合滤波算法与局部和最优融合Kalman滤波算法的精度,结果表明,CI融合滤波算法的精度高于局部滤波精度,但低于最优加权融合滤波精度。

In order to solve the problem of time delay in multi-sensor information fusion, a simulation model of moving target tracking in sensor networks with state and observation delay is established. Transforming time-delay systems into non-time-delay systems by using augmented matrices, a covariance intersection (CI) fusion filtering algorithm for multi-sensor systems with time-delay is presented in this paper. The method avoids the calculation of the mutual covariance matrix of any two local filtering errors, and the calculation amount and the calculation time are greatly reduced. The precision of the method is analyzed, and the accuracy of the covariance intersection fusion filtering algorithm and that of the local and optimal fusion Kalman filtering algorithm are compared. The results show that the accuracy of CI fusion filtering algorithm is higher than that of local filtering, but lower than that of optimal weighted fusion filtering.