A Passive Locating Algorithm for Motive Target Based on Modified Particle Filter Method

Yang Kui, Huang Liang, L. Zhong, Zhang Guodong
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Abstract

Passive tracking of motive target is in difficulty and interacting multiple model (IMM) is the classical method that requires accurate and timely target maneuver detection. In order to passively locate moving target using aerial mobile observe, a new hybrid particle filter positioning algorithm is proposed based on bearings crossing locating method. According to the existing initialization problems of particle filter, the new algorithm gets the proposal distribution from bearings crossing locating method and generates the required particles by the constraints of angle measurement to state variables. It avoids the randomness when generating particles and brings down the number of required particles in high dimensional cases. As a result, the present algorithm reduces the computing costs and improves real-time performance of the particle filter. By simulation analysis with particle filter, the new algorithm shows the superior positioning ability to other methods.
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基于改进粒子滤波法的运动目标被动定位算法
动态目标的被动跟踪是一个难点,多模型相互作用(IMM)是对目标机动进行准确、及时检测的经典方法。为了利用空中移动观测被动定位运动目标,提出了一种基于方位交叉定位方法的混合粒子滤波定位算法。针对粒子滤波存在的初始化问题,该算法从方位交叉定位法中获取建议分布,并通过角度测量对状态变量的约束生成所需粒子。它避免了生成粒子时的随机性,减少了高维情况下所需粒子的数量。结果表明,该算法降低了计算成本,提高了粒子滤波的实时性。通过粒子滤波仿真分析,新算法的定位能力优于其他方法。
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