People nowadays spend a tremendous amount of time in indoor structures, causing them to be known as the “indoor generation.” For example, Americans spend, on average, 90% of their time indoors. In light of this, the demand for accurate indoor navigation and localization systems has been more than ever before. Not only accurate indoor navigation enables emerging applications, e.g., location-based services (LBS), it is vital for public safety, e.g., first responders. Numerous competing approaches have been proposed over the past couple of decades for indoor navigation and localization; however, there is no single technology that has emerged as a clear winner in solving this problem.

Among all approaches, cellular long-term evolution (LTE)-based approaches are particularly attractive as they are infrastructure-free, and if properly exploited, can lead to a practical, affordable, and accurate localization system. This is due to the inherent desirable characteristics of LTE signals: abundance, geometric diversity, high bandwidth (up to 20 MHz), high received power (carrier-to-noise ratio (CNR) ranges between 50 and 80 dB-Hz in different indoor conditions), and some of their downlink signals are free to use. Exploiting LTE-based signals for indoor localization comes with several challenges: (i) specialized receivers to opportunistically extract navigation observables from received LTE signals must be designed, and (ii) the clock biases of LTE base stations (also known as evolved Node Bs or eNodeBs) must be removed or estimated, and (iii) errors resulting from short-delay multipath must be mitigated. This Thesis addresses the aforementioned challenges. The foundational contributions of this thesis are demonstrated in showing meter-level accurate indoor navigation.

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.

Rechargeable batteries based on multivalent ions (Mg2+, Ca2+, Al3+) can have far-reaching applications such as portable electronics, electric vehicles, and grid storage. As the most abundant metal in the Earth’s crust, Al is an ideal candidate. Metallic Al anodes can, in theory, provide exceptionally high charge capacities. However, the lack of non-corrosive electrolytes has been a bottleneck in the advancement of a practical rechargeable battery. This dissertation discusses the author’s efforts to develop and understand organic electrolytes based on aluminum trifluoromethanesulfonate (referred to herein as Al-triflate or Al(OTF)3), an active-halide-free and commercially available Al salt. To investigate these systems, a wide range of computational and experimental techniques have been utilized, including density functional theory (DFT) calculations, Fourier transform infrared spectroscopy (FTIR), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). From these, insights into Al-ion speciation and electrochemistry are brough to light, and Al electrodeposition is successfully achieved from several electrolyte systems. Ultimately, the work presented in this dissertation successfully tackles reversible Al electrodeposition from chloride-free organic electrolytes, a major hurdle that has prevented the incorporation of these systems in rechargeable Al batteries. Chapter one includes a detailed review of historic and most recent developments in non-aqueous electrolyte chemistries for rechargeable aluminum batteries, including chloroaluminate ionic liquids and organic solutions. Chapter two reports the results of research on an Al(OTF)3 in tetrahydrofuran (THF) electrolyte. Computational modelling by means of DFT and a variety of experimental techniques have revealed the predicted and measured spectroscopic and electrochemical features of aluminum ions in this electrolyte. Aluminum was found to be electrochemically active, in addition to the presence of two concentration dependent ionic environments for triflate anions (OTF-). This work also introduces a method that provides a rationale for understanding redox potentials of Al-ions by comparing DFT calculations with cyclic voltammetry experiments. Chapter three discusses the effect of lithium chloride (LiCl) as an additive to the Al(OTF)3 in THF electrolyte to investigate the role of chloride ions on speciation and the electrochemical behavior of aluminum. Successful electrodeposition of aluminum was carried out from chloride (Cl-)-free (non-corrosive) and Cl--rich (highly-corrosive) Al electrolytes at room temperature, and a method to probe the progress of the reactions involving Al(OTF)3 and LiCl by utilizing the DFT-derived and FTIR-measured vibrational frequencies of the OTF- was introduced. Chapter four discusses the effect of hydrides (H-) on Al speciation and electrochemistry by employing a LiAlH4 additive to the Al(OTF)3/THF electrolyte. Reversible room-temperature Al electrodeposition is demonstrated and compared to the chloride-based electrolyte. Using the method developed in chapter 3, and from DFT and FTIR analyses, Al-hydride speciation in these systems is explored, and a mechanism for reversible Al electrodeposition in OTF--based electrolyte is proposed. Insight into the chemical composition of the Al deposits from the OTF-- and Cl--based electrolyte is revealed using depth-profile XPS analyses.