| 随机集的概率假设密度粒子滤波 |
| |
| 引用本文： | 田淑荣,盖明久,何友.随机集的概率假设密度粒子滤波[J].海军航空工程学院学报,2006,21(4):455-458. |
| |
| 作者姓名： | 田淑荣 盖明久 何友 |
| |
| 作者单位： | 海军航空工程学院基础部，海军航空工程学院基础部，海军航空工程学院信息融合研究所 海军航空工程学院信息融合研究所山东烟台，264001，山东烟台，264001 |
| |
| 基金项目： | 国家自然科学基金资助项目(60172033) |
| |
| 摘 要： | 多目标跟踪问题中,当目标数已知时,可以用概率数据互联(PDA)或联合概率数据互联(JPDA)算法。而当目标数未知或随时间变化时,需要对不同目标数的跟踪进行比较。可以把目标集看作随机集进行讨论,目标数N是随机变量。随机集的跟踪通过有限集统计(FISST)理论来完成。文中讨论了用粒子滤波实现跟踪随机集的方法。实验表明,在杂波环境下,粒子滤波可以稳健跟踪目标状态和目标数。
|
| 关 键 词： | 多目标跟踪 随机集 粒子滤波 有限集统计 概率假设密度(PHD)滤波 |
| 修稿时间： | 2006年4月15日 |
PHD particle filtering for random sets |
| |
| TIAN Shurong,GAI Mingjiu and HE You.PHD particle filtering for random sets[J].Journal of Naval Aeronautical Engineering Institute,2006,21(4):455-458. |
| |
| Authors: | TIAN Shurong GAI Mingjiu and HE You |
| |
| Institution: | TIAN Shurong1,2,GAI Mingjiu1,HE You2 |
| |
| Abstract: | In multi-target tracking problem,when the number of objects to track is known,standard Bayesian methods like PDA/JPDA can be employed.However,when the number of objects to track is unknown or varies over time,tracking hypothesis with different numbers of objects have to be compared.This can be addressed by viewing the set of object as a random set,in which the number of objects,N,is a stochastic variable.Tracking of random sets is formulated with finite set statistics (FISST).The contribution of this paper is a particle implementation of tracking random sets.Experiments show the particle filter to be able to estimate both the number of tracked objects,as well as the states of the objects,robustly from noisy observations. |
| |
| Keywords: | multi-target tracking random sets particle filter finite set statistics probability hypothesis density (PHD) filter |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《海军航空工程学院学报》浏览原始摘要信息 |
| 点击此处可从《海军航空工程学院学报》下载免费的PDF全文 |
|
