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中文摘要：
对目标机动的检测和准确跟踪，是目标跟踪研究中非常重要但难度较大的问题。将统计距离、统计距离增量作为系统方差的调整参量，采用模糊专家规则系统，提出了一种适用于机动目标的模糊自适应概率多假设跟踪（FA-PMHT）算法。该算法将数据关联寻优与运动模型寻优联合处理，从而实现了数据关联寻优、目标模型寻优一体化。仿真结果表明，所提算法与交互式多模型概率多假设跟踪（IMM—PMHT）算法相比在跟踪精度上有明显提高，并且满足实时性要求，证明该算法是有效的。
英文摘要：
The fast target maneuver detecting and highly accurate tracking are very important and rather difficult to be solved in target tracking study. A fuzzy adaptive probabilistic multi-hypothesis tracking （FA-PMHT） algorithm for maneuvering targets is proposed in this paper , which extends the traditional optimization of data association of PMHT to the joint optimization of data association and dynamic modeling through introducing a set of fuzzy rules, variance of process noise in dynamic model is adaptively and iteratively optimized. Hence our FA-PMHT obtains better adaptive ability no matter that the target maneuvers or not. Computer simulation of a benchmark target tracking shows that our FA- PMHT is superior to the classical IMM-PMHT in tracking precision and meets real time requirement.
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