UC Irvine

Global Navigation Satellite Systems (GNSSs) have long been the cornerstone for positioning, navigation, and timing. Despite their widespread use, GNSS signals face vulnerabilities such as jamming, spoofing, and unreliable coverage in various environments like urban canyons, indoors, tunnels, and parking structures. These limitations make exclusive reliance on GNSS inadequate for the rigorous demands of future applications, including autonomous vehicles (AVs), intelligent transportation systems, and location-based services.

To enhance GNSS performance in challenging settings, traditional methods have typically incorporated dead-reckoning sensors like inertial measurement units, lidars, or cameras. These sensors, however, accumulate errors over time and only offer navigation solutions within a local frame, relative to the user equipment’s (UE) initial position. In contrast, alternative signal-based approaches, known as signals of opportunity (SOPs) – encompassing AM/FM radio, satellite communication signals, digital television signals, Wi-Fi, and cellular – hold considerable promise as global navigation sources in GNSS-challenged environments. Among SOPs, cellular signals, particularly from third-generation (3G, code-division multiple access (CDMA)), fourth-generation (4G, long-term evolution (LTE)), and fifth-generation (5G, new radio (NR)) networks, stand out as potential navigation aids. Their navigation-friendly characteristics include ubiquity, geometric diversity, high carrier frequencies, spectral diversity, spatial diversity, broad bandwidth, strong signal strength, and free accessibility.

Nevertheless, as SOPs are primarily designed for communication rather than navigation, utilizing cellular signals for navigational purposes presents several challenges. These include (1) the lack of specific low-level signal and error models for optimal state and parameter extraction for positioning and timing, (2) the absence of published robust, efficient, and reliable receiver architectures to generate navigation observables, (3) continual updates and changes in cellular protocols, and (4) the scarcity of frameworks for high-accuracy navigation using such signals.

This dissertation addresses these challenges, focusing on cellular signals from 4G and 5G networks, with potential extensions to future cellular systems. The foundational contributions of this work are empirically validated on various platforms including ground vehicles (GVs), unmanned aerial vehicles (UAVs), and high-altitude aircraft, demonstrating GNSS-level navigation accuracy.