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The Particle Filter Algorithm Research For Target Tracking Based On Information Fusion

机译:基于信息融合的目标跟踪粒子滤波器算法研究

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This paper researches the particle filters Algorithms for target tracking based on Information Fusion, it combines the traditional Kalman filter with the particle filter. For multi-sensor and multi-target tracking system with complex application background, which is nonlinear and non-gaussian system, the paper proposes an effective particle filtering algorithm based on information fusion for distributed sensor, this algorithm contributes to the solution of particle degradation problems and the phenomenon of particle lack, and achieve high precision for target tracking.
机译:本文研究了基于信息融合的目标跟踪的粒子过滤器算法,它将传统的卡尔曼滤波器与粒子过滤器相结合。对于具有复杂应用背景的多传感器和多目标跟踪系统,该系统是非线性和非高斯系统,本文提出了一种基于对分布式传感器的信息融合的有效粒子滤波算法,该算法有助于解决粒子劣化问题的解决方案以及粒子缺乏的现象,实现了高精度的目标跟踪。

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