Analysis and Detection of Outliers in GNSS Measurements by Means of Machine Learning Algorithms

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GPS Receiver Simplification for Low cost Applications and Multipath Mitigation Analysis on SDR based Re configurable Software Receiver

Many modern position-based applications rely heavily on the Global Navigation Satellite System (GNSS). Most applications require precise position data obtained through sophisticated hardware with a high computational capacity in the receiver. Some cost-effective applications may not require precise position data and require less complex signal processing. The use of efficient hardware and signal processing techniques to reduce the overall cost of a GNSS receiver is an active research topic. This paper considers Global Positioning System (GPS) constellation and proposes two factors to reduce the receiver complexity: sampling frequency and the number of tracking channels. A Keysight GNSS signal generator to record GPS signals, a Software Defined Radio board and a software-based GPS receiver are used in the experimentation. The sampling frequencies are 40, 20, 10 and 5 MHz considered, and tracking channels are reduced from 12 to 6 and then 4. The increase of error in the receiver position with 6 and 4 satellites is considerably small, but the number of tracking channels and signal processing requirements are reduced considerably. The GPS signals are affected by many errors; one of the significant sources of error is multipath propagation. Three distinct GPS multipath scenarios are generated for four satellite signal combinations with the GNSS simulator for the receiver performance analysis. Three multipath mitigation techniques, namely Early Minus Late (EML), Narrow correlator (NC) and strobe correlator (SC) methods, are considered because of their simple structure and fewer signal processing requirements. The error reductions of three multipath scenarios are compared, and the SC method performs better in all three multipath scenarios

GNSS Vulnerabilities and Existing Solutions:A Review of the Literature

This literature review paper focuses on existing vulnerabilities associated with global navigation satellite systems (GNSSs). With respect to the civilian/non encrypted GNSSs, they are employed for proving positioning, navigation and timing (PNT) solutions across a wide range of industries. Some of these include electric power grids, stock exchange systems, cellular communications, agriculture, unmanned aerial systems and intelligent transportation systems. In this survey paper, physical degradations, existing threats and solutions adopted in academia and industry are presented. In regards to GNSS threats, jamming and spoofing attacks as well as detection techniques adopted in the literature are surveyed and summarized. Also discussed are multipath propagation in GNSS and non line-of-sight (NLoS) detection techniques. The review also identifies and discusses open research areas and techniques which can be investigated for the purpose of enhancing the robustness of GNSS

Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS) or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellite-receiver transit time offset of the Line-Of-Sight (LOS) signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML) delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s), phase(s), and delay(s) of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK-) and Sine Binary Offset Carrier- (SinBOC-) modulated signals is also analyzed in closed loop model with the new Composite BOC (CBOC) modulation chosen for Galileo E1 signal. The simulation results show that the RSSML achieves the best multipath mitigation performance in a uniformly distributed two-to-four paths Rayleigh fading channel model for all three modulated signals

The Global Navigation System Scope (GNSScope): a toolbox for the end-to-end modelling simulation and analysis of GNSS

The thesis provides a detailed overview of the work carried out by the author over the course of the research for the award of the degree of Doctor of Philosophy at the University of Westminster, and the performance results of the novel techniques introduced into the literature. The outcome of the work is collectively referred to as the Global Navigation System Scope (GNSScope) Toolbox, offering a complete, fully reconfigurable platform for the end-to-end modeling, simulation and analysis of satellite navigation signals and systems, covering the signal acquisition, tracking, and range processing operations that take place in a generic Global Navigation Satellite System (GNSS) receiver, accompanied by a Graphical User Interface (GUI) providing access to all the techniques available in the toolbox. Designed and implemented entirely in the MATLAB mathematical programming environment using Software Defined Radio (SDR) receiver techniques, the toolbox offers a novel new acquisition algorithm capable of handling all Phase-Shift Keying (PSK) type modulations used on all frequency bands in currently available satellite navigation signals, including all sub-classes of the Binary Offset Carrier (BOC) modulated signals. In order to be able to process all these signals identified by the acquisition search, a novel tracking algorithm was also designed and implemented into the toolbox to track and decode all acquired satellite signals, including those currently intended to be used in future navigation systems, such as the Galileo test signals transmitted by the GIOVE satellites orbiting the Earth. In addition to the developed receiver toolbox, three novel algorithms were also designed to handle weak signals, multipath, and multiple access interference in GNSScope. The Mirrored Channel Mitigation Technique, based on the successive and parallel interference cancellation techniques, reduces the hardware complexity of the interference mitigation process by utilizing the local code and carrier replicas generated in the tracking channels, resulting in a reduction in hardware resources proportional to the number of received strong signals. The Trigonometric Interference Cancellation Technique, used in cross-correlation interference mitigation, exploits the underlying mathematical expressions to simplify the interference removal process, resulting in reduced complexity and execution times by reducing the number of operations by 25% per tracking channel. The Split Chip Summation Technique, based on the binary valued signal modulation compression technique, enhances the amount of information captured from compressing the signal to reveal specific filtering effects on the positive and negative polarity chips of the spreading code. Simulation case studies generated entirely using the GNSScope toolbox will be used throughout the thesis to demonstrate the effectiveness of the novel techniques developed over the course of the research, and the results will be compared to those obtained from other techniques reported in the literature

Reduction of initial convergence period in GPS PPP data processing

Precise Point Positioning (PPP) has become a popular technique to process data from GPS receivers by applying precise satellite orbit and clock information, along with other minor corrections to produce cm to dm-level positioning. Although PPP presents definite advantages such as operational flexibility and cost effectiveness for users, it requires 15-25 minutes initialization period as carrier-phase ambiguities converge to constant values and the solution reaches its optimal precision. Pseudorange multipath and noise are the largest remaining unmanaged errors source in PPP. It is proposed that by reducing these effects carrier-phase ambiguities will reach the correct steady state at an earlier time, thus reducing the convergence period of PPP. Given this problem, this study seeks to improve management of these pseudorange errors. The well-known multipath linear combination was used in two distinct ways: 1) to directly correct the raw pseudorange observables, and 2) to stochastically de-weight the pseudorange observables. Corrections to the observables were made in real-time using data from the day before, and post-processed using data from the same day. Post-processing has shown 4 7% improvement in the rate of convergence, as the pseudorange multipath and noise were effectively mitigated. A 36% improvement in the rate of convergence was noted when the pseudorange measurements were stochastically de-weighting using the multipath observable. The strength of this model is that it allows for real-time compensation of the effects of the pseudorange multipath and noise in the stochastic model

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors

Indoor Positioning with GNSS-Like Local Signal Transmitters

Not all the techniques proposed have, of course, been based on radio techniques, but they are the most important ones for two main reasons: their level of development and maturity on the one hand and their ability to "cross" or to "get around" obstacles such as walls, furniture or people on the other hand. Optical based techniques, like laser based distance measurements or vision based (camera) scene analysis systems present some real advantages in terms of measurement accuracy (a few millimetres for the former) or orientation determination (very useful for any guidance system, available for the latter). Unfortunately, the foreseen use of positioning devices being mainly dedicated to pedestrians in urban environments, optical obstacles are numerous. These latter techniques are then considered as potential hybridisation candidates. Many types of sensors have also been studied for positioning, such as infrared or ultrasound. Once again, although accuracy can reach centimetre values, the environmental constraints are not compatible with the ubiquitous systems being sought. Another category is, of course, inertial systems which could be a valuable alternative to radio systems: time and distance associated position drifts are not yet sufficiently mastered and the given positioning is relative , which means the need for "something else" in order to provide the user with an absolute location. The object of this section is to focus on radio based approaches