基于自适应衰减卡尔曼滤波的多传感器信息融合

Multisensor information fusion based on adaptive fading Kalman filter

工程实践证明,标准卡尔曼滤波器的鲁棒性较差.在解决实际问题时,如果所建立的目标运动模型不能真实反映实际的运动过程,就会导致滤波器发散.针对此问题,提出了基于自适应衰减卡尔曼滤波的多传感器信息融合方法,这种方法可以有效地消除系统状态方程在建模存在误差时给信息融合带来的影响.

The application of enginerring has proved that the robustness of standard Kalman filter is not very good. When we meet the real problem, it will result to the divergence of the filter if the constructed model is unfit on the real process. Regarding this problem, we prefer multisenson information fusion based on adaptive fading Kalman filter. This way can help get rid of the influence of the model effectively .