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Maneuvering multi-target tracking based on PHD filter for phased array radar

机译:基于PHD滤波器的相控阵雷达机动多目标跟踪

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Tracking an unknown and time-varying number of maneuvering targets is a challenging problem in the presence of noise, clutter, uncertainties in target maneuvers, data association, and detection. To solve this problem, a novel multiple maneuvering targets tracking algorithm called multiple models unbiased converted measurement probability hypothesis density (MM-UBCM-PHD) is proposed in this paper for phased array radar. The method not only solves the converted error in the direction cosine coordinate, but also avoids higher bias estimation of target number. The simulation results indicate that the proposed method has better performance in terms of state filtering and target number estimation.
机译:在存在噪声,混乱,目标机动性不确定,数据关联和检测的情况下,跟踪未知数量和随时间变化的机动目标是一个具有挑战性的问题。为解决这一问题,本文提出了一种新型的多机动目标跟踪算法,称为相控阵雷达多模型无偏转换测量概率假设密度(MM-UBCM-PHD)。该方法不仅解决了方向余弦坐标转换后的误差,而且避免了目标数的较高偏差估计。仿真结果表明,该方法在状态滤波和目标数量估计方面具有较好的性能。

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