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Global navigation satellite systems (GNSS) have been the main technology used in aerial and ground vehicle navigation systems. As vehicles approach full autonomy, the requirements on the accuracy, reliability, and availability of their navigation systems become very stringent. Due to the limitations of GNSS, namely severe attenuation in deep urban canyons and susceptibility to interference, jamming, and spoofing, alternative sensors and signals are sought. The most common approach to address the limitations of GNSS-based navigation in urban environments is to fuse GNSS receivers with inertial navigation systems (INSs), lidars, cameras, and map matching algorithms. An alternative approach has emerged over the past decade, which is to exploit ambient signals of opportunity (SOPs), such as cellular, digital television, AM/FM, WiFi, and low Earth orbit (LEO) satellite signals.
Among SOPs, cellular signals have attracted significant attention due to their inherently desirable attributes, including: abundance, geometric diversity, high received power, and large transmission bandwidth. Cellular systems have gone through five generations. Long-term-evolution (LTE) and new radio (NR) are the standards of the last two generations of wireless technology, namely 4th generation (4G) and 5th generation (5G), respectively. LTE has been developed and standardized in most countries over the past few years and currently has more than four billion users. The structure of NR signals has been finalized in 2019 and since then cellular providers have started rolling 5G out in major cities around the world.
Cellular signals are not designed for navigation. In order to exploit cellular signals for navigation purposes, several challenges must be addressed: (1) specialized receivers are required to extract navigation observables from cellular signals, (2) cellular towers typically transmit from low elevation angles, causing multipath signals to be received alongside line-of-sight signals. Multipath can introduce error on the estimated navigation observables, which must be alleviated, (3) the achievable ranging accuracy in multipath-free and multipath-rich environments must be characterized, (4) navigation framework must be developed to localize the receiver using the derived navigation observables, and (5) cellular signals base stations' clock biases must be estimated, since they are not available to the receiver.
This dissertation aims to address all of the above challenges for cellular LTE and NR signals. In particular, for LTE, first, a software-defined receiver (SDR) is proposed that is capable of (1) extracting the essential parameters for navigation from received LTE signals, (2) acquiring and tracking LTE signals transmitted from multiple eNodeBs, and (3) producing navigation observables from LTE signals including code and carrier phase and Doppler frequency measurements. Second, the accuracy of the produced measurements are derived as a function of carrier-to-noise ratio and signal transmission bandwidth. It is shown that LTE cell-specific reference signal (CRS) can provide higher precision compared to the LTE secondary synchronization signal (SSS) due to its high transmission bandwidth. Third, standalone and non-standalone navigation frameworks are proposed to localize the receiver using the generated navigation observables. Fourth, it is proposed to exploit the received LTE signal's time-of-arrival (TOA) and direction-of-arrival (DOA) to produce a navigation solution in cold-start applications, where there is no estimate of the receiver's initial state. For this purpose, an SDR is designed to jointly acquire and track TOA and DOA of LTE signals.
For NR, first, an SDR is proposed that is capable of (1) acquiring synchronization signal (SS), physical broadcast channel (PBCH) signal, and its associated demodulation reference signal (DM-RS), which are transmitted on a block called SS/PBCH block and (2) tracking SS/PBCH block to produce code and carrier phase and Doppler frequency measurements from NR signals. Second, the precision of the derived code and carrier phase measurements are analyzed as a function of carrier-to-noise ratio and NR numerology.
Finally, the statistics of the NR position estimation error are derived for different propagation channels.
Throughout the dissertation, numerical and experimental results are provided to validate the theoretical contributions.
Advisor's name and contact information:
Zak M. Kassas, Ph.D.
Director, US DOT Center for Automated Vehicles Research with Multimodal
AssurEd Navigation (CARMEN)
Mechanical & Aerospace Engineering | Electrical Engineering & Computer Science
University of California, Irvine
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