English  |  正體中文  |  简体中文  |  Items with full text/Total items : 26988/38789
Visitors : 2314592      Online Users : 39
RC Version 4.0 © 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://ntour.ntou.edu.tw:8080/ir/handle/987654321/40769

Title: Neural network aided adaptive Kalman filtering for GPS applications
Authors: Dah-Jing Jwo;Chi-Shui Chang;Chia-Hsin Lin
Contributors: 國立臺灣海洋大學:通訊與導航工程學系
Date: 2004
Issue Date: 2017-02-06T08:05:59Z
Publisher: IEEE International Conference on
Abstract: Abstract:The Kalman filtering theory plays an important role in the fields of navigation system and receiver tracking loop designs. For obtaining optimal (in the viewpoint of minimum mean square error) estimate of the system state vector, the designers are required to have exact knowledge on both dynamic process and measurement models, in addition to the assumption that both the process and measurement are corrupted by zero mean Gaussian white noises. The neural network can be incorporated into the filtering mechanism as a dynamic model corrector for identifying the real-time nonlinear dynamics modeling error when the modeling uncertainty is considered. The partially unknown part of the dynamics is identified by the neural network and the modeling error is compensated. Applications of the neural network aided adaptive Kalman filter is introduced to the GPS navigation and receiver tracking loop design.
Relation: Systems, Man and Cybernetics, 2004
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40769
Appears in Collections:[通訊與導航工程學系] 演講及研討會

Files in This Item:

File Description SizeFormat
index.html0KbHTML40View/Open


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

 


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback