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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/35706

Title: 基於RBF神經網路之無縫超緊密GPS/INS導航系統設計
Radial Basis Function Neural Network Assisted Ultra-Tighty Coupled GPS/INS Integration for Seamless Navigation
Authors: Chih-Hsun Chuang
莊至勛
Contributors: NTOU:Department of Communications Navigation and Control Engineering
國立臺灣海洋大學:通訊與導航工程學系
Keywords: GPS/INS;超緊密耦聯式整合導航系統;GPS斷訊;類神經網路
GPS/INS;Ultra-tightly coupled;GPS outage;RBFNN
Date: 2012
Issue Date: 2013-10-07T02:58:05Z
Abstract: 超緊密耦聯也稱為深度整合(Deep integration),接收機與慣導系統整合的超緊密耦聯架構有許多優點。如抗干擾和多路徑抑制、提升高動態性能、跟踪微弱信號、提高定位精度、縮短擷取時間、提高鎖相環路帶寬,得到更精確的Doppler頻移和相位等。GPS/INS超緊密耦聯架構目前有兩種主要觀點,一種是把GPS中的I(in-phase)與Q(quadrature)訊號作為整合濾波器之量測值,另一種是整合濾波器所估算出來的衛星速度回授到GPS相關器。而本研究採用的超緊密耦聯架構兩者皆採用。本論文採用放射基底函數神經網路輔助GPS/INS超緊密耦聯架構,斷訊前先行訓練神經網路,斷訊後發揮神經網路之特色,提升GPS斷訊期間導航系統的定位精度,使導航系統定位誤差在斷訊期間抑制其發散之速度。結果顯示在斷訊期間使用類神經網路輔助GPS/INS超緊密耦聯之定位效果較好,斷訊區段裡測試數量不同的神經元,較多的神經元數量提升定位精度之幅度較大。
In GPS/INS integration, the ultra-tightly coupled approach involves the integration of I (in-phase) and Q (quadrature) components from the correlator of a GPS receiver with the INS data. The principal advantages of the Ultra Tightly Couple (UTC) structure is that a Doppler frequency derived from the INS is integrated with the tracking loops to improve the receiver tracking capability. The Doppler frequency shift is calculated and fed to the GPS tracking loops for elimination of the effect of stochastic errors caused by the Doppler frequency. The navigation information from INS can be converted into the Doppler information, which can be integrated with the GPS tracking loops to mitigate the Doppler on the GPS signal, resulting in the threshold improvement, thereby improving the overall system performance. An algorithm for bridging GPS outages using the radial basis function neural network (RBFNN) for providing better prediction of measurement residual between GPS and prediction in order to maintain regular operation of the navigation system. The results demonstrate that the UTC with the assist of neural network can effectively improve the system robustness during GPS outages.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0019967020
http://ntour.ntou.edu.tw/handle/987654321/35706
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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