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A Particle Filter Based Algorithm for State Estimation of Dim Moving Point Target in IR Image Sequence

机译:基于粒子滤波器的IR图像序列中昏暗移动点目标的状态估计算法

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Under the condition of the target's initial information is already estimated successfully, This paper present a realtime target tracking algorithm that based on particle filter (PF) update algorithm. According to the particles' transmission characteristics and the measurements from a single frame detection, the algorithm estimate the target's following moving state, in this way, tracking the dim moving point target successfully under the background of low signal-noise-ratio (SNR) in IR image sequence. The paper introduced the related theory and the concrete steps for accomplishing the algorithm and also simulated the proposed tracking algorithm on the MATLAB platform. Experimental analysis and results showed that the algorithm achieved real-time, dynamic stability and robustness while tracking the random moving target in high clutter environment.
机译:在目标的初始信息的条件下已经成功估算,本文提出了一种基于粒子滤波器(PF)更新算法的实时目标跟踪算法。根据粒子的传输特性和从单帧检测的测量,算法以这种方式估计目标之后的移动状态,在低信噪比(SNR)的背景下成功地跟踪DIM移动点目标IR图像序列。本文介绍了相关理论和实现算法的具体步骤,并在MATLAB平台上模拟了所提出的跟踪算法。实验分析和结果表明,该算法在跟踪高杂波环境中的随机移动目标时实现了实时,动态稳定性和鲁棒性。

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