摘要
针对临空高速目标运动状态多变,跟踪困难的问题,将扩展卡尔曼粒子滤波与交互多模算法相结合,提出IMM-EKPF算法,该算法不需要计算雅可比矩阵,能有效求解非线性非高斯环境的机动目标跟踪问题。在此基础上,有效结合模糊机动检测,可以在目标机动和非机动之间转换跟踪算法,以提高跟踪精度,减少计算量。仿真验证该方法在临空高速目标运动状态多变的情况下跟踪效果较好。
Aiming at the issue that it is difficult to trace variable motion states of near space high- speed targets, the extend Kalman particle filter （EKPF） and interaction multiple model （IMM） are com- bined to develop an interaction multiple model-extend Kalman particle filter （IMM-EKPF） algorithm. The algorithm needs not to calculate the Jacobi matrix, and it can effectively solve non Gauss and non- linear target trace. On this basis, combined with fuzzy maneuvering detection, rack algorithm is transi- tioned between maneuvering and non-maneuvering to improve the tracking accuracy and reduce the a- mount of calculation. Results demonstrate the feasibility of this method.
出处
《现代防御技术》
北大核心
2016年第2期143-150,共8页
Modern Defence Technology
基金
国家自然科学基金项目(61272011)
国家自然科学青年基金(61102109)
关键词
临空高速目标
信号融合
交互多模型算法
扩展卡尔曼粒子滤波
模糊机动检测
目标跟踪
near space high-speed target
signal fusion
interaction multiple model
extend Kalman particle filter
fuzzy maneuvering detection
target trace
