多传感器交互式多模型系统中数据融合的一种算法

An algorithm of data fusion in multisensor IMM system

交互式多模型Kalman滤波器是一种基于“软切换”的机动目标跟踪方法,该方法在多目标跟踪系统中取得了良好的效果.本文提出了一种基于方差范数最小意义下的多传感器交互式多模型信息融合方法,并通过仿真验证了该方法的有效性.

The interacting multiple model (IMM) is an algorithm that estimates the state of a dynamic system with several behavior modes which can switch from one to another. The IMM estimator can be a self-adjusting variable-band width filter, which makes it natural for tracking maneuvering targets. In this paper, we present a new algorithm based on the least norm of target state's variance to obtain the fusion information of the multisensor IMM system. And we prove the validity of this algorithm by simulation.