Forward and Inverse Modeling of GPS Multipath for Snow Monitoring

Snowpacks provide reservoirs of freshwater, storing solid precipitation and delaying runoff to be released later in the spring and summer when it is most needed. The goal of this dissertation is to develop the technique of GPS multipath reflectometry (GPS-MR) for ground-based measurement of snow depth. The phenomenon of multipath in GPS constitutes the reception of reflected signals in conjunction with the direct signal from a satellite. As these coherent direct and reflected signals go in and out of phase, signal-to-noise ratio (SNR) exhibits peaks and troughs that can be related to land surface characteristics. In contrast to other GPS reflectometry modes, in GPS-MR the poorly separated composite signal is collected utilizing a single antenna and correlated against a single replica. SNR observations derived from the newer L2-frequency civilian GPS signal (L2C) are used, as recorded by commercial off-the-shelf receivers and geodetic-quality antennas in existing GPS sites. I developed a forward/inverse approach for modeling GPS multipath present in SNR observations. The model here is unique in that it capitalizes on known information about the antenna response and the physics of surface scattering to aid in retrieving the unknown snow conditions in the antenna surroundings. This physically-based forward model is utilized to simulate the surface and antenna coupling. The statistically-rigorous inverse model is considered in two parts. Part I (theory) explains how the snow characteristics are parameterized; the observation/parameter sensitivity; inversion errors; and parameter uncertainty, which serves to indicate the sensing footprint where the reflection originates. Part II (practice) applies the multipath model to SNR observations and validates the resulting GPS retrievals against independent in situ measurements during a 1-3 year period in three different environments - grasslands, alpine, and forested. The assessment yields a correlation of 0.98 and an RMS error of 6-8 cm, with the GPS under-estimating in situ snow depth by approximately 15%. GPS daily site averages were found effective in mitigating random noise without unduly smoothing the sharp transitions as captured in new snow events. This work corroborates the readiness of quality-controlled GPS-MR for snow depth monitoring, reinforcing its maturity for operational usage

Development of a Model and Localization Algorithm for Received Signal Strength-Based Geolocation

Location-Based Services (LBS), also called geolocation, have become increasingly popular in the past decades. They have several uses ranging from assisting emergency personnel, military reconnaissance and applications in social media. In geolocation a group of sensors estimate the location of transmitters using position and Radio Frequency (RF) information. A review of the literature revealed that a majority of the Received Signal Strength (RSS) techniques used made erroneous assumptions about the distribution or ignored effects of multiple transmitters, noise and multiple antennas. Further, the corresponding algorithms are often mathematically complex and computationally expensive. To address the issues this dissertation focused on RSS models which account for external factors effects and algorithms that are more efficient and accurate

RIS-Enabled NLoS Near-Field Joint Position and Velocity Estimation under User Mobility

In the context of single-base station (BS) non-line-of-sight (NLoS) single-epoch localization with the aid of a reflective reconfigurable intelligent surface (RIS), this paper introduces a novel three-step algorithm that jointly estimates the position and velocity of a mobile user equipment (UE), while compensating for the Doppler effects observed in near-field (NF) at the RIS elements over the short transmission duration of a sequence of downlink (DL) pilot symbols. First, a low-complexity initialization procedure is proposed, relying in part on far-field (FF) approximation and a static user assumption. Then, an alternating optimization procedure is designed to iteratively refine the velocity and position estimates, as well as the channel gain. The refinement routines leverage small angle approximations and the linearization of the RIS response, accounting for both NF and mobility effects. We evaluate the performance of the proposed algorithm through extensive simulations under diverse operating conditions with regard to signal-to-noise ratio (SNR), UE mobility, uncontrolled multipath and RIS-UE distance. Our results reveal remarkable performance improvements over the state-of-the-art (SoTA) mobility-agnostic benchmark algorithm, while indicating convergence of the proposed algorithm to respective theoretical bounds on position and velocity estimation.Comment: 11 pages, 9 figures, journa

Localization error bounds for 5G mm-wave systems under hardware impairments

Localization and location aware systems are expected to be counted as one of the main services of 5G millimeter wave (mmWave) communication systems. mmWave communication systems are offering a large bandwidth from 30-300 GHz frequency band along with low latency communications. Although, they use massive number of antennas at their transmitters and receivers, their transceivers occupy a very small area, in order of centimeters. These features make 5G mmWave communication systems an exceptional candidate for the localization services. However, mmWave suffers from some limitations such as high vulnerability to the environment and hardware deficiency. The hardware used in mmWave system’s transceivers including power amplifiers and analog/digital converters, cannot be manufactured perfectly as of high costs. Therefore, it is highly probabilistic to see a non-linear behavior coming out of the mmWave transceivers, known as hardware impairments (HWIs). HWIs is generally caused as a result of nonlinearity of transmitter power amplifier and receiver low noise amplifier (LNA) as well as analog to digital (ADC) and digital to analog converters (DAC). Moreover, HWIs is the general form of phase noise and In/Quadrature phase (I/Q) imbalance. Because of the mmWave’s nature, even a slight shortcoming can cause severe effects on its performance. This thesis investigates the possible effects of HWIs on the user localization error bounds. Towards that and focusing on line-of-sight (LOS) path, we derive the Cramer-Rao Lower Bound (CRLB) for the user equipment (UE)’s location and orientation by starting with a conventional two dimension (2D) scenario and then, we extend it to the realistic three dimensional (3D) scenario. [...

Visible light positioning systems under imperfect synchronization and signal-dependant noise

Optical Wireless Communication (OWC) is an enabling technology for sixth-generation (6G) and beyond communication networks. Visible light communication (VLC) is a crucial branch of OWC technology expected to meet 6G communication system requirements. The VLC system can facilitate multiple functionalities simultaneously including illumination, ultra-high data rate communications, positioning such as location and navigation services. In VLC systems, a light-emitting diode (LED) functions as a transmitter. A photodetector or imaging sensor acts as a receiver and the visible light is used as the transmission medium. Researchers have shown a great deal of interest in VLC based positing and localization techniques, as visible light positioning (VLP) systems have shown better localization accuracy than radio frequency (RF) based positioning or global positioning system (GPS). This thesis considers the problem of position estimation accuracy in VLC systems in the presence of signal-dependent shot noise (SDSN). We investigate distance and 3D position estimation approaches in different scenarios, focusing on error estimation performance bounds. Additionally, this work attempts to resolve the synchronization problem found in VLP systems

The Effects of Cognitive Jamming on Wireless Sensor Networks used for Geolocation

The increased use of Wireless Sensor Networks (WSN) for geolocation has led to an increased reliance on this technology. Jamming, protecting jamming, and detecting jamming in a WSN are areas of study that have greatly increased in interest. This research uses simulations and data collected from hardware experiments to test the effects of jamming on a WSN. Hardware jamming was tested using a Universal Software Radio Peripheral (USRP) Version 2 to assess the effects of jamming on a cooperative network of Java Sun SPOTs. The research combines simulations and data collected from the hardware experiments to see the effects of jamming on cooperative and noncooperative geolocation

Exploring Strategies for the Combination of Multiple Space-geodetic Techniques

Space-geodetic techniques are based on signal acquisition from extraterrestrial radio sources that can be used to infer geodetic positioning and define Earth-fixed and inertial reference systems. These techniques, which include Very Long Baseline Interferometry (VLBI) and Global Navigation Satellite Systems (GNSS) among others, exhibit different strengths and weaknesses in recovering parameters of interest. VLBI, for example, has access to all parameters linking Earth-fixed and inertial reference systems, so-called Earth Orientation Parameters (EOP), while GNSS is superior at determining in one of the EOP, Polar Motion (PM), due to the ubiquity and global distribution of the GNSS network of permanent receivers. The combination of different space-geodetic techniques shows promise in suppressing technique-specific biases and determining parameters with greater precision. This thesis presents the principles of VLBI and GNSS, and then explores the different combination strategies that can be used in the aim of generating of high-quality space-geodetic products

Towards the Next Generation of Location-Aware Communications

This thesis is motivated by the expected implementation of the next generation mobile networks (5G) from 2020, which is being designed with a radical paradigm shift towards millimeter-wave technology (mmWave). Operating in 30--300 GHz frequency band (1--10 mm wavelengths), massive antenna arrays that provide a high angular resolution, while being packed on a small area will be used. Moreover, since the abundant mmWave spectrum is barely occupied, large bandwidth allocation is possible and will enable low-error time estimation. With this high spatiotemporal resolution, mmWave technology readily lends itself to extremely accurate localization that can be harnessed in the network design and optimization, as well as utilized in many modern applications. Localization in 5G is still in early stages, and very little is known about its performance and feasibility. In this thesis, we contribute to the understanding of 5G mmWave localization by focusing on challenges pertaining to this emerging technology. Towards that, we start by considering a conventional cellular system and propose a positioning method under outdoor LOS/NLOS conditions that, although approaches the Cram\'er-Rao lower bound (CRLB), provides accuracy in the order of meters. This shows that conventional systems have limited range of location-aware applications. Next, we focus on mmWave localization in three stages. Firstly, we tackle the initial access (IA) problem, whereby user equipment (UE) attempts to establish a link with a base station (BS). The challenge in this problem stems from the high directivity of mmWave. We investigate two beamforming schemes: directional and random. Subsequently, we address 3D localization beyond IA phase. Devices nowadays have higher computational capabilities and may perform localization in the downlink. However, beamforming on the UE side is sensitive to the device orientation. Thus, we study localization in both the uplink and downlink under multipath propagation and derive the position (PEB) and orientation error bounds (OEB). We also investigate the impact of the number of antennas and the number of beams on these bounds. Finally, the above components assume that the system is synchronized. However, synchronization in communication systems is not usually tight enough for localization. Therefore, we study two-way localization as a means to alleviate the synchronization requirement and investigate two protocols: distributed (DLP) and centralized (CLP). Our results show that random-phase beamforming is more appropriate IA approach in the studied scenarios. We also observe that the uplink and downlink are not equivalent, in that the error bounds scale differently with the number of antennas, and that uplink localization is sensitive to the UE orientation, while downlink is not. Furthermore, we find that NLOS paths generally boost localization. The investigation of the two-way protocols shows that CLP outperforms DLP by a significant margin. We also observe that mmWave localization is mainly limited by angular rather than temporal estimation. In conclusion, we show that mmWave systems are capable of localizing a UE with sub-meter position error, and sub-degree orientation error, which asserts that mmWave will play a central role in communication network optimization and unlock opportunities that were not available in the previous generation