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Random sample consensus algorithm for multiple target tracking in over-the-horizon radar

机译:超视距雷达中多目标跟踪的随机样本共识算法

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Multiple target tracking in over-the-horizon radar (OTHR) suffers from two major challenges due to the multipath propagation phenomenon. The first is multipath detection that detects appearing and disappearing targets automatically, while one target may produce s tracks for s propagation paths. The second is multipath tracking that calculates the target-to-measurement-to-path assignment matrices to estimate target states, which is computationally intractable due to the combinatorial explosions. A joint multipath target detection and tracking method is proposed based on random sample consensus (RANSAC). Using the iterative hypothesize-and-test framework of RANSAC, the close loop between identification of target-to-measurement-to-path and estimation of target states is established, which is conducive to improving the tracking performance by utilizing multipath measurements. Numerical simulations demonstrate the effectiveness of the proposed method.
机译:由于多径传播现象,超视距雷达(OTHR)中的多目标跟踪面临两个主要挑战。第一种是多路径检测,可自动检测出现和消失的目标,而一个目标可能会为s条传播路径产生s条轨迹。第二种是多路径跟踪,它计算目标到测量路径的分配矩阵以估计目标状态,由于组合爆炸,该状态在计算上难以处理。提出了一种基于随机样本共识(RANSAC)的联合多径目标检测与跟踪方法。利用RANSAC的迭代假设测试框架,建立了目标到路径的识别与目标状态估计之间的闭环,有利于利用多径测量提高跟踪性能。数值模拟证明了该方法的有效性。

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