【作者】 贾正望； 李银伢； 毛明秀； 陈黎； 郭治；

【Author】 Jia Zhengwang,Li Yinya,Mao Mingxiu,Chen Li,Guo Zhi School of Automation,Nanjing University of Sciences and Technology,Nanijing 210094

【机构】 南京理工大学自动化学院；

【摘要】 针对联合概率数据关联算法过于复杂的弊端以及概率数据关联算法对多目标处理的片面性,本文提出了一种适用于实际应用的改进概率关联算法,该算法通过引进雷达多普勒测量信息,对进入跟踪门重叠区域中的公共测量值权重系数进行调整,从而使最终的估计值更加准确,关联精度得到进一步提高。理论分析和蒙特卡罗仿真结果表明,该算法具有较小的计算量以及良好的跟踪性能。更多还原

【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.更多还原