模糊数据互联滤波器及其在机动目标跟踪中的应用

Fuzzy Data Association Filter with Application to Maneuvering Target Tracking

为解决机动目标跟踪过程中的数据关联问题,提出了模糊数据互联滤波器,分析了其工作机理,并将其应用于机动目标跟踪中。与概率数据互联滤波器不同,在进行数据关联时,模糊数据互联滤波器假定目标当前转弯率在一定范围内取值,其预测中心不再是一个点,而是一线段;在计算测量的权重系数时,依据的是测量距该线段的距离。仿真实验表明,杂波环境下对机动目标跟踪时,采用模糊数据互联滤波器降低了航迹丢失率。

To solve the problem of data association in maneuvering target tracking, the fuzzy data association filter （FDAF） was proposed, its operational mechanism was analyzed, and its application to maneuvering target tracking was introduced. Being different from the probabilistic data association filter （PDAF）, FDAF assumes that the current turn rate of a maneuvering target changes within a limited range in data association. Therefore, the forecasting center is not a point but a short line. The distance between a measurement and the short line is utilized to compute the weight factor of the measurement. Simulation results show FDAF reduces the percentage of lost tracks in tracking a maneuvering target in presence of clutter.