现代电子技术2012，Vol.35Issue(4)：18-21,24,5.
多目标跟踪中基于特征辅助的概率数据关联算法
Algorithm base on feature assist for probability data association in multi-target tracking
马璐 1王刚2
作者信息
- 1. 北京市遥感信息研究所,北京100192
- 2. 北京环球信息开发应用中心,北京100094
- 折叠
摘要
Abstract
In traditional multi-target tracking systems, the information only relative to target state vector has been used for data association. A new association algorithm based on the generalized probability data association (GPDA) algorithm - feature aided tracking (FAT) algorithm is presented in this paper. FAT algorithm combines feature information with traditional state information in a probabilistic way. It preferably solves the tracking problem of closely spaced targets in dense clutter. The ID range profile information of targets is taken as an example to perform a simulation. The simulation results verifies that the FAT algorithm outperforms the conventional probability data association algorithm.关键词
多目标跟踪/特征辅助跟踪/广义概率数据关联/密集杂波Key words
multi-target tracking/ feature aided tracking/ generalized probability data association/ dense clutter分类
信息技术与安全科学引用本文复制引用
马璐,王刚..多目标跟踪中基于特征辅助的概率数据关联算法[J].现代电子技术,2012,35(4):18-21,24,5.
