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| 多传感器多目标跟踪的粒子PHD滤波算法 | |
| 引用本文： | 郝燕玲,孟凡彬,张崇猛,蔡艺峰,王素鑫. 多传感器多目标跟踪的粒子PHD滤波算法[J]. 传感器与微系统, 2010, 29(4) |
| 作者姓名： | 郝燕玲 孟凡彬 张崇猛 蔡艺峰 王素鑫 |
| 作者单位： | 1. 哈尔滨工程大学自动化学院,黑龙江,哈尔滨,150001 2. 哈尔滨工程大学自动化学院,黑龙江,哈尔滨,150001;天津航海仪器研究所,天津,300131 3. 天津航海仪器研究所,天津,300131 |
| 摘 要： | 针对单传感器跟踪系统的缺陷,提出了基于粒子概率假设密度(PHD)滤波的多传感器多目标跟踪算法.这种算法不仅避免了多传感器多目标跟踪的数据关联问题,而且在漏检、目标密集、航迹交叉、小范围内目标数多的杂波环境下能够稳定、精确地估计目标状态和目标数.仿真实验比较了单传感器粒子PHD滤波与多传感器的粒子PHD滤波的跟踪性能,验证了该方法的跟踪性能和精度. |
| 关 键 词： | 随机有限集 多传感器 多目标跟踪 粒子滤波 概率假设密度 |
Particle PHD filter algorithm for multisensor multitarget tracking |
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| HAO Yan-ling,MENG Fan-bin,ZHANG Chong-meng,CAI Yi-feng,WANG Su-xin. Particle PHD filter algorithm for multisensor multitarget tracking[J]. Transducer and Microsystem Technology, 2010, 29(4) | |
| Authors: | HAO Yan-ling MENG Fan-bin ZHANG Chong-meng CAI Yi-feng WANG Su-xin |
| Affiliation: | HAO Yan-ling1,MENG Fan-bin1,2,ZHANG Chong-meng2,CAI Yi-feng2,WANG Su-xin2(1.College of Automation,Harbin Engineering University,Harbin 150001,China,2.Tianjin Navigation Instrument Research Institute,Tianjin 300131,China) |
| Abstract: | In order to avoid the flaw of single-sensor tracking system,a multisensor multitarget tracking algorithm based on particle probability hypothesis density(PHD) filter is proposed.This algorithm can not only avoid data association problem of multisensor multitarget tracking,but also can track a time-varying number of targets robustly and their states under miss detection,dense target,cross track and large number of targets under clutter environment,achieving real-time performance.Simulation result validated m... |
| Keywords: | random finite sets multisensor multitarget tracking particle filter probability hypothesis density |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |