A Standalone Approach for High-Sensitivity GNSS Receivers
Creators: name: Ren, Tiantong
Publisher: name: Graduate Studies
Year: 2014
Subjects: subject: Computer Science
subject: Engineering--Electronics and Electrical
subject: Geotechnology
subject: High-Sensitivity GNSS Receiver
subject: Bit Wipe-Off
subject: Extend Coherent Integration Time
subject: Vector Tracking
subject: Ultra-Tight Integration
subject: Inertial Sensors
subject: Weak GNSS Signals
subject: Multipath
subject: Bit Synchronization
subject: Bit Decoding

description: Global Navigation Satellite Systems (GNSS) such as the Global Positioning System (GPS) can provide users with accurate navigation and timing services worldwide. Recently, processing weak GNSS signals has been receiving growing attention because of the increased demand for navigation in signal challenged environments, e.g., indoors, under dense foliage canopies, in urban canyons, etc. High-sensitivity GNSS receivers are preferred for the improved acquisition and tracking capabilities under degraded signal environments. The current mainstream high-sensitivity GNSS receiver design utilizes assisted-GNSS to maximize performance. However, the assistance source is not always available and the cost of additional communication channels is often a requisite concern. In light of this, the standalone performance of high-sensitivity GNSS receivers is addressed in this thesis. In order to achieve bit wipe-off and extend coherent integration time, a newly proposed standalone high-sensitivity GNSS receiver uses Maximum-Likelihood (ML) bit synchronization and ML bit decoding algorithms to estimate the location of bit boundaries and the bit values from GNSS signals. A systematic performance analysis of ML bit synchronization and ML bit decoding is achieved. The theoretical performance models of ML bit synchronization and ML bit decoding are developed based on statistical theory. In order to further improve the performance of ML bit decoding, the benefits of using the advanced tracking algorithms in standalone mode to improve ML bit decoding are analyzed using a software GNSS receiver. Those advanced tracking algorithms include: vector tracking, ultra-tightly coupled architecture and open-loop tracking. Finally the estimated data bit values are used to extend coherent integration via the ML-based bit wipe-off, and the accuracy and reliability of the whole system are assessed in the navigation domain. The results of the vehicular field tests in dense foliage and urban canyon environments show the advanced tracking algorithms can improve the successful decoding rate (SDR) of bit values about 2% to 30% depending on signal power. Meanwhile, by extending coherent integration time from 20 ms to 100 ms using ML-based bit wipe-off in the standalone approach, the position and velocity accuracy has been shown to be improved about 50% in the vehicular field tests. In this thesis, two innovative strategies are proposed to mitigate the high bit error rate (BER) problem in ML-based bit wipe-off, and an innovative signal power based multipath mitigating algorithm is proposed. Finally, in order to improve the performance of ML bit synchronization, an innovative collective bit synchronization approach for weak GNSS signals using multiple satellites is proposed. The benefits of using collective bit synchronization to improve the detection rate of bit boundary positions are analyzed using a software GNSS receiver.