An Improved Target Tracking Data Association Algorithm

被引：0

作者：

Zuo Xiangang ^{[1
]}

Yu Zhou ^{[1
]}

机构：

[1] Henan Inst Sci & Technol, Dept Informat Engn, Xinxiang, Peoples R China

来源：

PROCEEDINGS OF 2009 CONFERENCE ON COMMUNICATION FACULTY | 2009年

关键词：

target tracking; association probability; joint probabilistic data association; Monte Carlo;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

For the Joint Probabilistic Data Association (JPDA), which complexity is outstandingly increased with increased targets and measurements. To reduce the expense of memory and the time for JPDA, a new improved JPDA algorithm was introduced for data association. Firstly, in this new method, removing the small probability events by selecting the right threshold values of the targeting gate; secondly, fade the probability density of association events according to the association probability of the targets in the targeting gate, after that compute the association probability of the targets. The theory analysis and computer simulation show that this algorithm can keep the rate of success of the target tracking with low CPU computing time.

引用

页码：476 / 480

页数：5