English  |  正體中文  |  简体中文  |  Items with full text/Total items : 27329/39174
Visitors : 2479486      Online Users : 38
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/18991

Title: 使用微分代數方程式理論進行GNSS定位演算法設計與改善---使用行為模式法
Design and Improvement of GNSS Positioning Algorithm Using DAE and Behavioral Approach
Authors: 王和盛
Contributors: NTOU:Department of Communications Navigation and Control Engineering
abstract:The main objective of this paper is to study the characteristic of the total least squares (TLS) algorithm and its applications in GPS navigation. TLS algorithm will be used to improve the result of standard GPS position problem, while the structured TLS algorithm will be used to identity the model of a dynamical trajectory. The advantage of TLS algorithm lies in that, while the traditional LS estimation algorithm is able to filter out the noise (disturbance) in the measurement signal, the TLS algorithm is capable of removing the implicit positioning errors in both the data matrix and the measurement variable. However only one single time epoch is considered in both the LS and TLS algorithm (snapshot algorithm). The correleation between consecutive time epochs is not able to be included in both algorithms. In this paper, we adopt a behavioral approach (Willem, 86) to model a dynamical system in a kernel representation and then the kernel representation is transformed to an equivalent structured TLS problem, which can then be solved by a structured TLS algorithm. A system identification problem for a flight dynamical trajectory is served as an example to illustrate the idea. After a dynamical system (in kernel representation) is identified by the structured TLS method, we can then use the derived model to predict the trajectory in arbitrary time epoch.
Keywords: GPS定位演算法;行為模式法;最小平方法;資料矩陣最小平方法;總體最小平方法;混合最小平方與總體最小平方法;加權總體最小平方法;結構化總體最小平方法;廣域差分修正定位
GPS positioning;Behavioral Approach;Least-Squares Method;Data Least-Squares Method;Total Least-Squares Method;Mix Least Squares – Total Least Squares Method;Weight Total Least-Squares Method;Structured Total Least-Squares Method;Wide-Area Differential GPS
Date: 2008-08
Issue Date: 2011-08-17T07:05:54Z
Publisher: 行政院國家科學委員會
Abstract: 摘要:本計劃使用總體最小平方法的方式,分別針對GPS定位演算法作改進,以及利用結構化總體最小平方法對GPS軌道估測進行系統鑑別。 傳統的最小平方估測演算法,僅能排除量度變數中的外界雜訊,而使用總體最小平方法於GPS定位演算法的好處,是可以同時排除資料矩陣及量度變數內隱含的定位誤差,以獲得更加準確的定位結果。 而無論是最小平方法或總體最小平方法,均僅能針對單一時間點估測,並未考量各時間點之相關性。在本計劃中,我們用文獻上一種新的動態系統概念,稱為行為模式法(behavioral approach),將動態系統以核表示來描述,並將核表示轉換成一等效的結構化總體最小平方法的問題,最後將使用結構化總體最小平方法於GPS軌道估測做系統鑑別,其目的在於透過結構化總體最小平方法鑑別出的系統模型,我們可以預測出GPS衛星軌道上每個時間點的飛行軌跡位置。
Relation: NSC97-2221-E019-010
URI: http://ntour.ntou.edu.tw/handle/987654321/18991
Appears in Collections:[通訊與導航工程學系] 研究計畫

Files in This Item:

There are no files associated with this item.

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