Research of improved probability data association algorithm for multi-target tracking

Jiang ZhengWang, L. Yinya, Mao Mingxiu, Chen Li, Guo Zhi
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引用次数: 2

Abstract

An improved probabilistic data association is proposed to overcome both the drawback of complication in joint probabilistic data association and the unneutrality of multi-targets processing by probabilistic data association. It incorporates the radar Doppler measurement information and modifies weighting of state estimation of measurements in the common region, and then makes the final estimation more exact and improves further performance. The theoretical analysis and Monte-Carlo simulation results show that the algorithm has small computation cost and a better real-time tracking performance.
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多目标跟踪的改进概率数据关联算法研究
针对联合概率数据关联的复杂性和概率数据关联处理多目标的不中立性,提出了一种改进的概率数据关联方法。该方法结合雷达多普勒测量信息,修改公共区域测量状态估计的权重,使最终估计更加精确,进一步提高了性能。理论分析和蒙特卡罗仿真结果表明,该算法计算量小,具有较好的实时跟踪性能。
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