Extend Kalman Gaussian Mixture Probability Hypothesis Density Filter Based on Radar and IR Sensor Fusion
In this paper, we proposed a method to fuse data from radar and IR sensor in Extend Kalman probability hypothesis density (EK-GMPHD) filter. Firstly the multitarget is estimated with infrared (IR) sensor using EKGMPHD filter, and then the filtering results are fused with measurements from radar through sequential filter, in this way, the multi-target state is updated at the tracking system. Under false alarms, missed detections and dense targets environment, this method has a high reliability when tracking multi-target. Simulation experiments are presented to demonstrate the performance of the proposed method.
random sets data fusion multi-target tracking GMPHD filter Extend Kalman filter
Yanling Hao Fanbin Meng Xiangwei Qiao Ziyang Zhao Congmeng Zhang Yifeng Cai
College of Automation Harbin Engineering University Harbin,China Tianjin Navigation Instrument Research Institute China Shipping Group Tianjin,China
国际会议
2010 IEEE信息与自动化国际会议(ICIA 2010)
哈尔滨
英文
1-5
2010-06-20（万方平台首次上网日期，不代表论文的发表时间）