Journal Article10.1109/TAES.2017.2705338
GNSS Multireceiver Vector Tracking
Yuting Ng,Grace Xingxin Gao +1 more
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TL;DR: A deeply coupled multireceiver vector tracking (MRVT) architecture that improves the reliability and robustness of GPS signal tracking and position estimation and is more robust to equipment malfunctions than the single GPS receiver is presented.
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Abstract: Accurate, reliable, and robust global positioning system (GPS) localization is desirable for many navigation applications. Unfortunately, it is challenging for a single GPS receiver to always provide accurate positioning solutions. In urban environments, intermittent signal availability leads to degraded GPS signal tracking and position estimation of the single GPS receiver. In addition, equipment malfunction of the single GPS receiver results in inaccurate navigation solutions. This paper presents a deeply coupled multireceiver vector tracking (MRVT) architecture that improves the reliability and robustness of GPS signal tracking and position estimation. MRVT jointly tracks GPS signals received by multiple GPS receivers, mitigating GPS signal tracking disruptions, improving the reliability of GPS localization in periods of intermittent signal availability. In addition, the MRVT receiver is more robust to equipment malfunctions than the single GPS receiver. We implemented an MRVT receiver using commercial radio frequency front ends and our PyGNSS software. We experimentally validated the reliability of our MRVT receiver in periods of intermittent GPS availability experienced in downtown San Francisco. Our MRVT receiver exhibited consistent GPS signal tracking and position estimation as compared to vector tracking. In addition, we experimentally validated the robustness of our MRVT receiver to the failure of a single GPS receiver.
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Citations
Performance Analysis of a Deep Simple Recurrent Unit Recurrent Neural Network (SRU-RNN) in MEMS Gyroscope De-Noising.
TL;DR: A deep learning method was introduced to MEMS gyroscope de-noising using a recently popular Recurrent Neural Networks (RNN) variant Simple Recurrent Unit (SRU-RNN), and the results surely demonstrated the effectiveness of the employed SRU in this application.
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Software-Defined Radio GNSS Instrumentation for Spoofing Mitigation: A Review and a Case Study
TL;DR: In this paper, the authors present a case study of software-defined radio (SDR) implementations of a GPS receiver with both conventional and spoofing mitigation modes for GNSS signal processing.
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GNSS User Technology: State-of-the-Art and Future Trends
01 Jan 2022
TL;DR: In this paper , the authors provide a unified reference for current GNSS receiver technologies and solutions and its expected evolution in the next decade, considering receiver concepts, antennae, RF front ends, digital signal processing, and positioning algorithms.
Software-Defined Radio GNSS Instrumentation for Spoofing Mitigation: A Review and a Case Study
TL;DR: In this article, the authors review reported SDRs in the context of instrumentation capabilities for both conventional and spoofing mitigation modes, and show that significantly increased computational loads when operating in the spoofing domain are required.
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•Posted Content
Time-correlated Window Carrier-phase Aided GNSS Positioning Using Factor Graph Optimization for Urban Positioning.
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TL;DR: In this article, the carrier-phase measurements inside a window, the so-called window carrier phase (WCP), are employed to constrain the states inside a factor graph.
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