arrow
返回

Data association and target identification using range profile

delete2004-03-01
delete6
PRE
AI
J
Jae-Chern Yoo *
K
Kim, YS
DOI:10.1016/j.sigpro.2003.11.020delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
We present a new data association algorithm using range-profile, which has maneuver-following capability. In this approach, targets can be identified as a by-product of the data association, not requiring a separate step for target identification. Early data association cannot identify targets and thus requires a large amount of computation not to miss tracks when targets maneuver and cross each other. Our method using range profile mitigates the complexity of data association. And once the classes of tracks are identified, the tracks can be more efficiently tracked and associated even when target maneuvers. Furthermore, our approach can provide the optimum tracking filter gain for tracking maneuvering target and thus will contribute to the improvement of performance for maneuvering target tracking. Extensive computer simulations have demonstrated that the new data association is not only more efficient in terms of the computational complexity without requiring a separate step for target identification, but also can provide the optimum tracking filter gain for tracking maneuvering target. (C) 2003 Elsevier B.V. All rights reserved.
Keyword:
data association
target tracking
radar signals
multiple-target tracking
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Signal Processing 封面图
Signal Processing
IF:
3.6
论文数:
10.0K
被引数:
1.7W

机构

暂无机构信息
引用论文

引用论文

err分享
err收藏
err分享
err收藏
Effect of eicosapentaenoic acid and docosahexaenoic acid on diabetic osteopenia
err1995-10-01
err0
PREAI
errYuya Yamada; Hisako Fushimi; Toru Inoue; Yukiko Matsuyama; Masakuni Kameyama; Takeshi Minami; Yuko Okazaki; Yasuhisa Noguchi; Toshio Kasama
err分享
err收藏
没有更多内容