This dissertation investigates robust signal processing and machine learning techniques, with the objective of improving the robustness of two applications against various threats, namely Global Navigation Satellite System (GNSS) based positioning and satellite imaging. GNSS technology is widely used in different fields, such as autonomous navigation, asset tracking, or smartphone positioning, while the satellite imaging plays a central role in monitoring, detecting and estimating the intensity of key natural phenomena, such as flooding prediction and earthquake detection. Considering the use of both GNSS positioning and satellite imaging in critical and safety-of-life applications, it is necessary to protect those two technologies from either intentional or unintentional threats. In the real world, the common threats to GNSS technology include multipath propagation and intentional/unintentional interferences. This thesis investigates methods to mitigate the influence of such sources of error, with the final objective of ...

Navigation information is an essential element for the functioning of robotic platforms and intelligent transportation systems. Among the existing technologies, Global Navigation Satellite Systems (GNSS) have established as the cornerstone for outdoor navigation, allowing for all-weather, all-time positioning and timing at a worldwide scale. GNSS is the generic term for referring to a constellation of satellites which transmit radio signals used primarily for ranging information. Therefore, the successful operation and deployment of prospective autonomous systems is subject to our capabilities to support GNSS in the provision of robust and precise navigational estimates. GNSS signals enable two types of ranging observations: --code pseudorange, which is a measure of the time difference between the signal's emission and reception at the satellite and receiver, respectively, scaled by the speed of light; --carrier phase pseudorange, which measures the beat of the carrier signal and ...

This Dissertation addresses the synchronization problem using an array of antennas in the general framework of Global Navigation Satellite Systems (GNSS) receivers. Positioning systems are based on time delay and frequency-shift estimation of the incoming signals in the receiver side, in order to compute the user's location. Sources of accuracy degradation in satellite-based navigation systems are well-known, and their mitigation has deserved the attention of a number of researchers in latter times. While atmospheric-dependant sources (delays that depend on the ionosphere and troposphere conditions) can be greatly mitigated by differential systems external to the receiver's operation, the multipath effect is location-dependant and remains as the most important cause of accuracy degradation in time delay estimation, and consequently in position estimation, becoming a signal processing challenge. Traditional approaches to time delay estimation are often embodied in a communication systems framework. Indeed, ...

The multi-frequency Global Navigation Satellite System (GNSS) signals are designed to overcome the inherent performance limitations of single-frequency receivers. However, the processing of multiple frequency signals in a time-varying GNSS signal environment which are potentially affected by multipath, ionosphere scintillation, blockage, and interference is quite challenging, as each signal is influenced differently by channel effects according to its Radio Frequency (RF). In order to get the benefit of synchronously/coherently generated multiple frequency signals, advanced receiver signal processing techniques need to be developed. The aim of this research thesis is to extract the best performance benefits out of multifrequency GNSS signals in a time-varying GNSS signal environment. To accomplish this objective, it is necessary to analyze the multi-frequency signal characteristics and to investigate suitable signal processing algorithms in order to enable the best performance of each signal. The GNSS receiver position ...

Global Navigation Satellite Systems (GNSS) is the de facto technology for Position, Navigation, and Timing (PNT) applications when it is available. GNSS relies on one or more satellite constellations that transmit ranging signals, which a receiver can use to self-localize. Signal acquisition is a crucial step in GNSS receivers, which is typically solved by maximizing the so-called Cross Ambiguity Function (CAF) resulting from a hypothesis testing problem. The CAF is a two-dimensional function that is related to the correlation between the received signal and a local code replica for every possible delay/Doppler pair, which is then maximized for signal detection and coarse synchronization. The outcome of this statistical process decides whether the signal from a particular satellite is present or absent in the received signal, as well as provides a rough estimate of its associated code delay and Doppler frequency, ...

This Dissertation addresses the signal acquisition problem using antenna arrays in the general framework of Global Navigation Satellite Systems (GNSS) receivers. GNSSs provide the necessary infrastructures for a myriad of applications and services that demand a robust and accurate positioning service. GNSS ranging signals are received with very low signal-to-noise ratio. Despite that the GNSS CDMA modulation offers limited protection against Radio Frequency Interferences (RFI), an interference that exceeds the processing gain can easily degrade receivers' performance or even deny completely the GNSS service. A growing concern of this problem has appeared in recent times. A single-antenna receiver can make use of time and frequency diversity to mitigate interferences, even though the performance of these techniques is compromised in the presence of wideband interferences. Antenna arrays receivers can benefit from spatial-domain processing, and thus mitigate the effects of interfering signals. ...

Global Navigation Satellite Systems (GNSS) signals are broadly used for positioning, navigation and timing (PNT) in many different applications and use cases. Although different PNT technologies are available, GNSS is expected to be a key player in the derivation of positioning and timing for many future applications, including those in the context of the Internet of Things (IoT) or autonomous vehicles, since it has the important advantage of being open access and worldwide available. Indeed, GNSS is performing very well in mild propagation conditions, achieving position and time synchronization accuracies down to the cm and ns levels, respectively. Nevertheless, the exploitation of GNSS in harsh propagation conditions typical of urban and indoor scenarios is very challenging, resulting in position errors of up to tens or even hundreds of meters, and timing accuracies of hundreds of ns. This thesis deals with ...

Multipath remains a dominant source of ranging errors in any Global Navigation Satellite System (GNSS), such as the Global Positioning System (GPS) or the developing European satellite navigation system Galileo. Multipath is undesirable in the context of GNSS, since the reception of multipath can create significant distortion to the shape of the correlation function used in the time delay estimate of a Delay Locked Loop (DLL) of a navigation receiver, leading to an error in the receiver's position estimate. Therefore, in order to mitigate the impact of multipath on a navigation receiver, the multipath problem has been approached from several directions, including the development of novel signal processing techniques. Many of these techniques rely on modifying the tracking loop discriminator (i.e., the DLL and its enhanced variants) in order to make it resistant to multipath, but their performance in severe ...

The ability to reliably and cheaply localize mobile terminals will allow users to understand and utilize the what, where and when of the surrounding physical world. Therefore, mobile terminal location information will open novel application opportunities in many areas. The mobile terminal positioning problem is categorized into three different types according to the availability of (1) initial accurate location information and (2) motion measurement data. Location estimation refers to the mobile positioning problem when both the initial location and motion measurement data are not available. If both are available, the positioning problem is referred to as position tracking. When only motion measurements are available the problem is known as global localization. These positioning problems were solved within the Bayesian filtering framework in order to work under a common theoretical context. Filter derivation and implementation algorithms are provided with emphasis on ...

This work deals with the problem of calculating the Cramer-Rao lower bounds (CRLBs) for bistatic radar channels. To this purpose we exploited the relation between the Ambiguity Function (AF) and the CRLB. The bistatic CRLBs are analyzed and compared to the monostatic counterparts as a function of the bistatic geometric parameters. In the bistatic case both geometry factors and transmitted waveforms play an important role in the shape of the AF, and therefore in the estimation accuracy of the target range and velocity. In particular, the CRLBs depend on the target direction of arrival, the bistatic baseline length, and the distance between the target and the receiver. The CRLBs are then used to select the optimum bistatic channel (or set of channels) for the tracking of a radar target moving along a trajectory in a multistatic scenario and for design ...

The provision of accurate positioning is becoming essential to our modern society. One of the main reasons is the great success and ease of use of Global Navigation Satellite Systems (GNSSs), which has led to an unprecedented amount of GNSS-based applications. In particular, the current trend shows that a new era of GNSS-based applications and services is emerging. These applications are the so-called critical applications, in which the physical safety of users may be in danger due to a miss-performance of the positioning system. These applications have very stringent requirements in terms of integrity. Integrity is a measure of reliability and trust that can be placed on the information provided by the system. Integrity algorithms were originally designed for civil aviation in the 1980s. Unfortunately, GNSS-based critical applications are often associated with terrestrial environments and original integrity algorithms usually fail. ...

Applications for the new generations of Global Navigation Satellite Systems (GNSS) are developing rapidly and attract a great interest. Both US Global Positioning System (GPS) and European Galileo signals use Direct Sequence-Code Division Multiple Access (DS-CDMA) technology, where code and frequency synchronization are important stages at the receiver. The GNSS receivers estimate jointly the code phase and the Doppler spread through a two-dimensional searching process in time-frequency plane. Since both GPS and Galileo systems will send several signals on the same carriers, a new modulation type - the Binary Offset Carrier (BOC) modulation, has been selected. The main target of this modulation is to provide a better spectral separation with the existing BPSK-modulated GPS signals, while allowing optimal usage of the available bandwidth for different GNSS signals. The BOC modulation family includes several BOC variants, such as sine BOC (SinBOC), ...

In this study, the respiratory system are modelled by three linear and one non-linear lumped parameter respiratory model, the equations of the models are driven and the parameters are estimated by using statistical signal processing methods. Linear RIC, Viscoelastic and Mead models and proposed basic non-linear RC model are used to resemble the respiratory system of the patient with Chronic Obstructive Pulmonary Disease (COPD) under non-invasive ventilation. Statistical signal processing methods such as Minimum Variance Unbiased Estimation (MVUE), Maximum Likelihood Estimation (MLE), Kalman Filter (KF), Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) are very powerful methods to estimate the parameters of the systems embedded in the unknown noise. In the first part of this thesis, artificial respiratory signals (airway flow and airway pressure) are used for the performance measurement criteria. Posterior Cramer Rao Lower Bound (PCRLB) is computed ...

This thesis comprises two parts. The first part deals with single carrier and multiple-carrier based frequency estimation. The second part is concerned with the application of ultrasound using the proposed estimators and introduces a novel efficient implementation of a subspace tracking technique. In the first part, the problem of single frequency estimation is initially examined, and a hybrid single tone estimator is proposed, comprising both coarse and refined estimates. The coarse estimate of the unknown frequency is obtained using the unweighted linear prediction method, and is used to remove the frequency dependence of the signal-to-noise ratio (SNR) threshold. The SNR threshold is then further reduced via a combination of using an averaging filter and an outlier removal scheme. Finally, a refined frequency estimate is formed using a weighted phase average technique. The hybrid estimator outperforms other recently developed estimators and ...

The characterization of Clock and Ephemeris error of the Global Navigation Satellite Systems is a key element to validate the assumptions for the integrity analysis of GNSS Safety of Life (SoL) applications. Specifically, the performance metrics of SoL applications require the characterization of the nominal User Range Errors (UREs) as well as the knowledge of the probability of a satellite, Psat or a constellation fault, Pconst, i.e. when one or more satellites are not in the nominal mode. We will focus on Advanced Autonomous Integrity Monitoring (ARAIM). The present dissertation carries-out an end-to-end characterization and analysis of Galileo and GPS satellites for ARAIM. It involves two main targets. First, the characterization of Galileo and GPS broadcast ephemeris and clock errors, to determine the fault probabilities Psat and Pconst, and the determination on an upper bound of the nominal satellite ranging ...