GNSS signal tracking under weak signal or high dynamic environment

There is a growing need to continue operating the Global Navigation Satellite Systems (GNSS) receivers under increasingly challenging and stressful conditions, where signal experiences deep fading, blockage, or high platform dynamics. As the most fragile component of the GNSS receiver, the carrier t...

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Main Author: Yang, Rong
Other Authors: Ling Keck Voon
Format: Theses and Dissertations
Language:English
Published: 2017
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Online Access:http://hdl.handle.net/10356/70121
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-701212023-07-04T17:29:10Z GNSS signal tracking under weak signal or high dynamic environment Yang, Rong Ling Keck Voon Poh Eng Kee School of Electrical and Electronic Engineering Satellite Engineering Centre DRNTU::Engineering::Electrical and electronic engineering There is a growing need to continue operating the Global Navigation Satellite Systems (GNSS) receivers under increasingly challenging and stressful conditions, where signal experiences deep fading, blockage, or high platform dynamics. As the most fragile component of the GNSS receiver, the carrier tracking loop must achieve improved tracking capability. The subject of GNSS tracking loop design has been well studied. This thesis takes the control system design perspective, presents tracking loop design as a state feedback/state estimator framework, sheds insight on frequency domain analysis, derives optimal parameters for carrier tracking loop design, and proposes adaptive tracking solutions for challenging environment. Two generalized carrier tracking loops, namely, the generalized phase tracking loop and the generalized frequency tracking loop, are studied using this state space framework. For the generalized phase tracking loop design, three approaches, i.e., proportional integral filter (PIF), Wiener filter (WF), and Kalman filter (KF), are presented in an unified manner from the state feedback/state estimator framework. With the state space framework, analytical equations characterizing the carrier phase tracking loop performance are derived. These equations relate the phase tracking error variance and dynamic stress phase error to the filter design parameters, such as integration time and noise equivalent bandwidth, as well as other parameters, such as thermal noise, oscillator noise, and receiver platform dynamics. From these equations, filter design parameters are optimized under various operating scenarios, such as weak signal or high dynamics. More specifically, the tracking sensitivities of the generalized phase tracking loop with these designs are obtained. Building on this analysis, an adaptive phase tracking scheme with time-varying integration time or loop bandwidth is proposed. A similar approach is applied to frequency tracking loop design. The PIF design is mapped to the state space structure through the equivalent closed-loop transfer function. Traditional KF-based frequency tracking loop design assumes white Gaussian noise. However, the frequency error measurement noise is non-white and so analytical equations for the frequency tracking error variance and dynamic stress frequency error are derived, taking into account the non-white noise characteristic. Frequency tracking error variance is used to evaluate the frequency tracking loop performance under the effects of thermal noise, oscillator noise, and platform dynamics. Using these analytical equations, optimal loop parameters are obtained, and the frequency tracking sensitivity is characterized. Based on these theoretical analysis, an adaptive frequency tracking scheme with loop bandwidth is proposed. Simulation results demonstrate the effectiveness of the proposed adaptive generalized carrier phase/frequency tracking architecture and verify the theoretical prediction. Doctor of Philosophy (EEE) 2017-04-12T01:50:50Z 2017-04-12T01:50:50Z 2017 Thesis Yang, R. (2017). GNSS signal tracking under weak signal or high dynamic environment. Doctoral thesis, Nanyang Technological University, Singapore. http://hdl.handle.net/10356/70121 10.32657/10356/70121 en 140 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Yang, Rong
GNSS signal tracking under weak signal or high dynamic environment
description There is a growing need to continue operating the Global Navigation Satellite Systems (GNSS) receivers under increasingly challenging and stressful conditions, where signal experiences deep fading, blockage, or high platform dynamics. As the most fragile component of the GNSS receiver, the carrier tracking loop must achieve improved tracking capability. The subject of GNSS tracking loop design has been well studied. This thesis takes the control system design perspective, presents tracking loop design as a state feedback/state estimator framework, sheds insight on frequency domain analysis, derives optimal parameters for carrier tracking loop design, and proposes adaptive tracking solutions for challenging environment. Two generalized carrier tracking loops, namely, the generalized phase tracking loop and the generalized frequency tracking loop, are studied using this state space framework. For the generalized phase tracking loop design, three approaches, i.e., proportional integral filter (PIF), Wiener filter (WF), and Kalman filter (KF), are presented in an unified manner from the state feedback/state estimator framework. With the state space framework, analytical equations characterizing the carrier phase tracking loop performance are derived. These equations relate the phase tracking error variance and dynamic stress phase error to the filter design parameters, such as integration time and noise equivalent bandwidth, as well as other parameters, such as thermal noise, oscillator noise, and receiver platform dynamics. From these equations, filter design parameters are optimized under various operating scenarios, such as weak signal or high dynamics. More specifically, the tracking sensitivities of the generalized phase tracking loop with these designs are obtained. Building on this analysis, an adaptive phase tracking scheme with time-varying integration time or loop bandwidth is proposed. A similar approach is applied to frequency tracking loop design. The PIF design is mapped to the state space structure through the equivalent closed-loop transfer function. Traditional KF-based frequency tracking loop design assumes white Gaussian noise. However, the frequency error measurement noise is non-white and so analytical equations for the frequency tracking error variance and dynamic stress frequency error are derived, taking into account the non-white noise characteristic. Frequency tracking error variance is used to evaluate the frequency tracking loop performance under the effects of thermal noise, oscillator noise, and platform dynamics. Using these analytical equations, optimal loop parameters are obtained, and the frequency tracking sensitivity is characterized. Based on these theoretical analysis, an adaptive frequency tracking scheme with loop bandwidth is proposed. Simulation results demonstrate the effectiveness of the proposed adaptive generalized carrier phase/frequency tracking architecture and verify the theoretical prediction.
author2 Ling Keck Voon
author_facet Ling Keck Voon
Yang, Rong
format Theses and Dissertations
author Yang, Rong
author_sort Yang, Rong
title GNSS signal tracking under weak signal or high dynamic environment
title_short GNSS signal tracking under weak signal or high dynamic environment
title_full GNSS signal tracking under weak signal or high dynamic environment
title_fullStr GNSS signal tracking under weak signal or high dynamic environment
title_full_unstemmed GNSS signal tracking under weak signal or high dynamic environment
title_sort gnss signal tracking under weak signal or high dynamic environment
publishDate 2017
url http://hdl.handle.net/10356/70121
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