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This article provides a comparative performance analysis of different acquisition and tracking methods of GPS L1 C/A and GPS L5 signals testing their robustness to the presence of scintillations in the propagation environment. This article compares the different acquisition methods in terms of probabilities of detection/false alarm, peak-to-noise floor ratios for the acquired signal and execution time, assessing the performance loss in the presence of scintillations. Moreover, robust tracking architectures that are optimized to operate in a harsh ionospheric environment have been employed. The performance of the carrier tracking methods, namely, traditional phase-locked loop (PLL) and Kalman filter based-PLL, have been compared in terms of the standard deviation of Doppler estimation, phase error, phase lock indicator (PLI), and phase jitter. The article is based on real global navigation satellite systems (GNSS) signals affected by significant phase and amplitude scintillation effects, collected at the South African Antarctic research base (SANAE IV) and Brazilian Centro de Radioastronomia e Astrofisica Mackenzie (CRAAM) monitoring stations. Performance is assessed exploiting a fully software GNSS receiver, which implements the different architectures. The comparative analysis allows to choose the best setting of the acquisition and tracking parameters, in order to allow the operation of signal acquisition and tracking at a required performance level under scintillation conditions.

This paper presents the development of a new metric to improve the performance of the Dispersion of Double Differences (D3) algorithm, which detects GNSS spoofing attacks with a dual-antenna system. The new metric is based on a linear regression applied to the fractional phase double differences. The original D3 algorithm is sometimes prone to false alarms and to missed detections. The idea presented in this paper intends to overcome such limitations by leveraging on the fact that the fractional double differences are characterized by having a piecewise linear trend, with different slopes and intercepts. By evaluating the dispersion of such two parameters instead of the double difference measurements directly, it is possible to design a more robust spoofing detector. The performance of this linear regression-based method is very promising, since no cases of false alarms or of missed detections have been observed in all the performed tests.

Nowadays, the Global Navigation Satellite Systems (GNSS) technology is not the primary means of navigation for civil aviation and Air Traffic Control, but its role is increasing. Consequently, the vulnerabilities of GNSSs to Radio Frequency Interference, including the dangerous intentional sources of interference (i.e., jamming and spoofing), raise concerns and special attention also in the aviation field. This panorama urges for figuring out effective solutions able to cope with GNSS interference and preserve safety of operations. In the frame of a Single European Sky Air traffic management Research (SESAR) Exploratory Research initiative, a novel, effective, and affordable concept of GNSS interference management for civil aviation has been developed. This new interference management concept is able to raise early warnings to the on-board navigation system about the detection of interfering signals and their classification, and then to estimate the Direction of Arrival (DoA) of the source of interference allowing the adoption of appropriate countermeasures against the individuated source. This paper describes the interference management concept and presents the on-field tests which allowed for assessing the reached level of performance and confirmed the applicability of this approach to the aviation applications. publishedVersion

During the last decade, the number of applications for land transportation that depend on systems for accurate positioning has significantly increased. Unfortunately, systems based on low-cost global navigation satellite system (GNSS) components harshly suffer signal impairments due to the environment surrounding the antenna, but new designs based on deeper data fusion and on the combination of different signal processing techniques can overcome limitations without the introduction of expensive components. Supported by a complete mathematical model, this paper presents the design of a real-time positioning system that is based on the tight integration of extremely low-cost sensors and a consumer-grade global positioning system receiver. The design has been validated experimentally through a series of tests carried out in real scenarios. The performance of the new system is compared against a standalone GNSS receiver and survey-grade professional equipment. The results show that a carefully designed and constrained integration of low-cost sensors can have performance comparable to that of an expensive professional equipment.

In the last decades, several positioning and navigation algorithms have been developed to enhance vehicular localization capabilities. Thanks to ad-hoc communication networks, the exchange of navigation data and positioning solutions has been exploited to the purpose. This trend has recently suggested the extension of state-of-the art navigation algorithms to the hybridization of independent heterogeneous measurements within collaborative frameworks. In this paper an integration paradigm based on the combination of Global Navigation Satellite System (GNSS) observable measurements is analysed. In this work, a comparison among legacy Extended Kalman Filter (EKF) and a suboptimal Particle Filter (s-PF) is proposed. First we show that under the same assumptions in non-collaborative framework the s-PF easily overcome EKF performances at the cost of a higher computational cost. On the contrary, by analysing a realistic scenario in which a target agent is aided by a set of collaborating peers we showed that a hybridized EKF implementation allows reaching and overcome PF performance at the only expense of network connectivity among few GNSS receivers, while the proposed integration induces minor benefits for an efficient s-PF.

With the advent of new services and the evolution of transportation systems the need of a reliable and accurate knowledge of the position information became of paramount importance. Among the multiple technologies and sensors that might be used for positioning, Global Navigation Satellite System (GNSS) can be considered as the core technology and a superior system capable to provide the user with estimates of his own position in a global reference frame. Unfortunately, received GNSS signals are extremely weak and thus vulnerable to non-intentional and intentional Radio Frequency Interference. In particular, the malicious intentional interference produced by jammers is proliferating and it is becoming a serious threat for GNSS receivers. The integration of GNSS and external sensors with complementary characteristics, is the key for overcoming the weaknesses and enhancing the strengths of each sub-system. In this paper, the design of an ultra-tight hybrid navigation system is proposed with the aim to enhance the robustness of the navigation system in presence of jamming. A GNSS unit has been integrated with external sensors, namely Inertial Navigation Systems, visual sensor and odometer. Exploiting the “record and replay” of real GNSS signal artificially augmented with jamming interference within the L1 GNSS bandwidth, the performance has been assessed in controlled scenarios. The results presented in this paper show that the multi-sensor integrated system can sustain the navigation even in presence of severe jamming, although such a strong interference completely masks the GNSS signal denying the navigation of a GNSS stand-alone system. Moreover, the test procedures suitability of the record and replay approach for the jamming scenario generation and combination with real datasets are discussed and analyzed.

In modern GNSS receivers, using a Kalman filter in each signal tracking loop presents remarkable advantages in terms of accuracy and robustness against malicious noise sources, but poses critical issues in real-time applications due to the high computational cost. For this reason, we propose an efficient method to dramatically reduce the number of operations involved in the execution of the Kalman filter. In particular, the relationship between Kalman gain and noise covariances is analyzed in detail, showing that the gain computation can be greatly simplified by using an appropriately calibrated, small-size lookup table (LUT). The loss of performance of the proposed method, due to its inherent approximations, is shown to be negligible with respect to a traditional implementation upon careful system model and LUT calibration. Furthermore, a very fast signal tracking recovery after an outage is guaranteed. The implementation complexity of the simplified LUT-based method is compared with traditional approaches, proving that the proposed method has a tremendous advantage in terms of computational and storage requirements.

In the modern automotive industry, the wide variety of Intelligent Transport System (ITS) services needs a positioning unit. The core of such unit is a Global Navigation Satellite System (GNSS) receiver hybridized or assisted by other sensors or data. In harsh environments, such as urban scenarios, the testing and performance assessment of these terminals is of paramount importance for ITS applications. In fact such environments are very challenging for the GNSS core unit. This paper proposes some test procedures suitable to assess the performance of GNSS receivers, as part of an hybridyzed positioning unit, in urban scenarios. The benefits of a GNSS receiver based on the Software Defined Radio (SDR) technology is exploited by presenting a set of results obtained on field tests.

Global Navigation Satellite Systems (GNSSs) remain the principal mean of positioning in many applications and systems, but in several types of environment, the performance of standalone receivers is degraded. Although many works show the benefits of the integration between GNSS and Inertial Navigation Systems (INSs), tightly-coupled architectures are mainly implemented in professional devices and are based on high-grade Inertial Measurement Units (IMUs). This paper investigates the performance improvements enabled by the tight integration, using low-cost sensors and a mass-market GNSS receiver. Performance is assessed through a series of tests carried out in real urban scenarios and is compared against commercial modules, operating in standalone mode or featuring loosely-coupled integrations. The paper describes the developed tight-integration algorithms with a terse mathematical model and assesses their efficacy from a practical perspective.

The European Rail Traffic Management System/European Train Control System (ERTMS/ETCS) has been developed by the European Union to enhance safety and efficiency of the railway transportation. So far, the positioning and monitoring of the trains have been based mainly on trackside equipment named balises: the introduction of Global Navigation Satellite Systems (GNSS) to implement an absolute positioning system on trains could lead to a better utilization of the line with a consequent line capacity increase, along with reliability increasing and cost reducing due to the removal of expensive infrastructures. This paper describes the insertion of a state-of-the-art channel model, named Land Mobile Satellite Channel Model (LMSCM) properly adapted to represent railways scenarios, into a hardware-in-the-loop system, where the parameters generated by LMSCM are used to configure an RF GNSS signal generator. The use of the hardware generator eases the simulation of the entire GNSS constellation, while the availability of the RF signal enables the assessment of the effects of rail-domain multipath on commercial receivers. The resulting model, named Rail-Land Mobile Satellite Channel Model (Rail-LMSCM), has been enhanced with the support of different kind of scenarios a train may encounter around the rail track, as well as with the introduction of GNSS outages due to the presence of tunnels. Such enhancements make the Rail-LMSCM a more realistic average representation of the railway environment. The implemented Rail-LMSCM has been used to test in the lab the local propagation effects on the performance of a complete GNSS receiver.