一种新的临空高超声速飞行器滑跃段跟踪算法  

A New Tracking Algorithm for Near Space Hypersonic Vehicle in Gliding Jumping Phase

作　　者：郭相科 付强[2] 范成礼[2] 韦刚[2] 

机构地区：[1]北京航空航天大学电子信息工程学院,北京100191 [2]空军工程大学防空反导学院,西安710051

出　　处：《宇航学报》2017年第9期971-978,共8页Journal of Astronautics

基　　金：国家自然科学青年基金(61503408)

摘　　要：针对临空高超声速飞行器滑跃段跟踪中存在的跟踪不稳定问题,提出一种基于多传感器的多周期多模型估计的最大熵模糊数据关联滤波(MPMME-MEFPDAF)算法。首先,在临空高超声速飞行器滑跃段运动特性分析的基础上,采用多周期多模型估计方法实现模型集自适应。然后,采用最大熵模糊数据关联思想,解决杂波环境下多传感器航迹断续、点迹关联问题。最后,将多周期多模型估计与最大熵模糊概率数据关联相结合,实现临空高超声速机动目标的多传感器连续跟踪。通过仿真验证,该算法比传统算法对临近空间高超声速速飞行器滑跃段的跟踪具有更好的跟踪效果。To improve the tracking accuracy of a near space hypersonic vehicle,a multi-period and multi-model estimation maximum entropy fuzzy data association filter（ MPMME-MEFPDAF） algorithm based on multiple sensors is proposed. Firstly,according to the characteristics of the hypersonic vehicle in the gliding jumping phase,the multi-periodmulti-model estimation（ MPMME） is adopted to realize the model adaptation. Secondly,the maximum entropy fuzzy data association filter（ MEFPDAF） is considered to solve the problems of the discontinuous trajectory and point correlation in the clutter environment. Finally,the MPMME-MEFPDAF algorithm,combined with the MPMME and MEFPDAF,is used to complete the tracking of the near space hypersonic maneuvering target. The simulation results show that the proposed algorithm has better tracking effect than the traditional algorithm in the gliding jumping phase.

关 键 词：高超声速飞行器 机动目标跟踪 多周期多模型估计 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]