English  |  正體中文  |  简体中文  |  Items with full text/Total items : 6481/11653
Visitors : 23354329      Online Users : 268
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/987654321/11805

Title: Applying Image Processing and Neural Network Techniques to Data Association Algorithm
Authors: Chung, Yi-Nung
Contributors: 電機工程學系
Keywords: Multiple-target tracking;Data association;Competitive Hopeld neural network
Date: 2011-05
Issue Date: 2012-07-02T02:09:50Z
Publisher: Kyushu Tokai University
Abstract: Multiple-target tracking (MTT) is a prerequisite step for radar surveillance systems. Data association is the key technique used in radar MTT systems. This paper presents a new approach for data association that uses both quantity data and image information. In order to combine these two attributes, a fusion algorithm based on the competitive Hop eld neural network (CHNN) is developed to match radar measurements
with existing target tracks. When target maneuvering problems are detected, an adaptive maneuvering estimator is applied. Computer simulation results indicate that the proposed approach is suitable for multiple-target tracking problems and has good performance.
Relation: International Journal of Innovative Computing, Information and Control, 7(5A): 2427-2439
Appears in Collections:[電機工程學系] 期刊論文

Files in This Item:

File SizeFormat
index.html0KbHTML475View/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