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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/53981

Title: 基於熵理論非線性濾波器於GPS多路徑環境下之設計
Entropy Based Nonlinear Filters for GPS Multipath Mitigation
Authors: Lai, Jen-Hsien
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Keywords: 最小誤差熵;最大相關熵;交互多模型;多路徑效應
minimum error entropy;maximum correntropy;Interacting Multiple Model;Multipath
Date: 2019
Issue Date: 2020-07-09T02:52:29Z
Abstract: 本論文探討熵原理運用於卡爾曼濾波器中,主要分為兩大主題,主題一為最大相關熵卡爾曼濾波器抑制多路徑誤差之影響。主題二為最小誤差熵卡爾曼濾波器於GPS多路徑之參數估計。 多路徑效應為影響GPS定位性能的眾多干擾源之一,尤其容易發生在具有反射物體的地方,如都市中的高樓大廈,橋梁等等的建築物就是反射物體的一種。通常接收機在反射物體旁時,容易會有反射訊號干擾,進而影響後續的定位解算。 本論文第一個主題為最大相關熵卡爾曼濾波器抑制多路徑誤差之影響。在探討實際工程應用中,要建立出準確的系統雜訊和量測雜訊的統計特性是非常困難的,更以突如其來的多路徑影響使得卡爾曼濾波器發散,為了解決雜訊不確定性問題,引進最大相關熵及交互多模型達到自適應的功能。 本論文第二個主題為最小誤差熵卡爾曼濾波器於GPS多路徑之參數估計。將包含多路徑影響的觀測訊號,以積分相關器之同相I (in-phase)與正交Q (quadrature)訊號作為觀測量輸出至最小誤差熵卡爾曼濾波器估測直接訊號及多路徑訊號之參數,如振幅、碼延遲、相位及頻率。
This thesis investigates the application of entropy principle to Global Position System (GPS) Navigation filter design, The research work covers two parts : (1) the application of the maximum correntropy Kalman filter for multipath mitigation; and (2) parameter estimation based on minimum error entropy Kalman filter for GPS multipath. Multipath effect is one of the many interference sources that degrades GPS positioning performance. It is particularly prone to occur in places with reflective objects, such as high-rise buildings, Bridges and other buildings in the city. Usually, when the receiver is next to the reflected object, there will be interference of reflected signal, which will affect the subsequent positioning solution. The first topic of this thesis is the effect of maximum correntropy Kalman filters on mitigating multipath errors. In practical engineering applications, it is very difficult to establish accurate system noise and measure the statistical characteristics of noise, especially for the outlier types of multipath errors for the GPS navigation processing. In order to solve the problem of noise uncertainty, maximum correntropy principle and interacting multiple model (IMM) are introduced for adaptation purpose. The second topic of this thesis is the GPS multipath parameter estimation using the minimum error entropy Kalman filter. The scheme is designed by introducing an additional term, which and is tuned according to the higher order moment of the estimation error. The algorithm has a high accuracy in estimation because entropy can characterize all the randomness of the residual. Observation signals with multipath influence are output to the minimum error entropy Kalman filter with I (in-phase) and Q (quadrature) signals of integral correlator to estimate parameters of direct signal and multipath signal, such as amplitude, code delay, phase and frequency.
URI: http://ethesys.lib.ntou.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=G0010667006.id
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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