National Changhua University of Education Institutional Repository : Item 987654321/11752
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 6507/11669
Visitors : 30071973      Online Users : 620
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
LoginUploadHelpAboutAdminister

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11752

Title: Applying Likelihood on Hopfield Neural Network for Radar Tracking
Authors: Chung, Yi-Nung;Yang, Maw-Rong;Juang, Dend-Jyi;Hsu, Tsung-Chun;Hsu, Shun-Peng
Contributors: 電機工程學系
Keywords: Data association;Likelihood;Neural network
Date: 2008-03
Issue Date: 2012-07-02T02:07:12Z
Publisher: Chinese Institute of Engineers
Abstract: The multiple‐target tracking (MTT) algorithm plays an important role in radar systems. Data association is the most important technique to solve the tracking problems associating dense measurements with existing tracks. A new approach applying Likelihood to measurements and existing tracks in a radar system based on Neural Network computation is investigated in this paper. The proposed algorithm will solve both the data association and the target tracking problems simultaneously. With this approach, the matching between radar measurements and existing target tracks can achieve global relevance. Computer simulation results indicate the ability of this algorithm to keep track of targets under various conditions.
Relation: Journal of The Chinese Institute of Engineers, 31(2): 339-342
Appears in Collections:[Department and Graduate Institute of Electronic Engineering] Periodical Articles

Files in This Item:

File SizeFormat
2050200710004.pdf88KbAdobe PDF701View/Open


All items in NCUEIR are protected by copyright, with all rights reserved.

 


DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback