Performances of a GNSS receiver for space-based applications

Space Vehicle (SV) life span depends on its station keeping capability. Station keeping is the ability of the vehicle to maintain position and orientation. Due to external perturbations, the trajectory of the SV derives from the ideal orbit. Actual positioning systems for satellites are mainly based on ground equipment, which means heavy infrastructures. Autonomous positioning and navigation systems using Global Navigation Satellite Systems (GNSS) can then represent a great reduction in platform design and operating costs. Studies have been carried out and the first operational systems, based on GPS receivers, become available. But better availability of service could be obtained considering a receiver able to process GPS and Galileo signals. Indeed Galileo system will be compatible with the current and the modernized GPS system in terms of signals representation and navigation data. The greater availability obtained with such a receiver would allow significant increase of the number of point solutions and performance enhancement. For a mid-term perspective Thales Alenia Space finances a PhD to develop the concept of a reconfigurable receiver able to deal with both the GPS system and the future Galileo system. In this context, the aim of this paper is to assess the performances of a receiver designed for Geosynchronous Earth Orbit (GEO) applications. It is shown that high improvements are obtained with a receiver designed to track both GPS and Galileo satellites. The performance assessments have been used to define the specifications of the future satellite GNSS receiver

Avionics architecture studies for the entry research vehicle

This report is the culmination of a year-long investigation of the avionics architecture for NASA's Entry Research Vehicle (ERV). The Entry Research Vehicle is conceived to be an unmanned, autonomous spacecraft to be deployed from the Shuttle. It will perform various aerodynamic and propulsive maneuvers in orbit and land at Edwards AFB after a 5 to 10 hour mission. The design and analysis of the vehicle's avionics architecture are detailed here. The architecture consists of a central triply redundant ultra-reliable fault tolerant processor attached to three replicated and distributed MIL-STD-1553 buses for input and output. The reliability analysis is detailed here. The architecture was found to be sufficiently reliable for the ERV mission plan

A GNSS Signal Simulator and Processor for Evaluating Acquisition and Tracking of GPS-like Signals From Satellites in LEO

Global navigation satellite systems (GNSS) have enabled accurate position, navigation, and timing (PNT) to both civilian and military users for a variety of applications. Since it has become a critical part of today's infrastructure, it is important to investigate ways to enhance or replace this service in challenging environments. These include urban canyons and indoor environments, as well as nefarious attacks, such as jamming and spoofing. Emerging low Earth orbiting (LEO) mega-constellations can be used to augment GNSS. These constellations contain a large number of satellites in order to provide global internet coverage. Although they are not optimized for PNT and use unknown signal structures, several research groups have already demonstrated the ability to track these signals and obtain position and time estimates. This thesis presents LEO signal simulation, acquisition and tracking using an in-house, Julia-language-based package, called GNSSTools. Topics included are an overview of GNSS, signal simulation and processing methods, and evaluation. Evaluations demonstrate the self-consistency of GNSSTools, and show its ability to process GPS L1 C/A and L5 simulated signals and data samples. Additionally, GPS signals are simulated with Doppler effects similar to signals observed from satellites in LEO to determine their effect on standard acquisition and tracking methods.</p

High Fidelity Satellite Navigation Receiver Front-End for Advanced Signal Quality Monitoring and Authentication

Over the last several years, interest in utilizing foreign satellite timing and navigation (satnav) signals to augment GPS has grown. Doing so is not without risks; foreign satnav signals must be vetted and determined to be trustworthy before use in military applications. Advanced signal quality monitoring methods can help to ensure that only authentic and reliable satnav signals are utilized. To effectively monitor and authenticate signals, the front-end must impress as little distortions upon the received signal as possible. The purpose of this study is to design, fabricate, and test the performance of a high-fidelity satnav receiver front-end for advanced monitoring of foreign and domestic space vehicle signals

Multipath Mitigation Techniques for Satellite-Based Positioning Applications

This chapter addressed the challenges encountered by a GNSS signal due to multipath propagation. A wide range of correlation-based multipath mitigation techniques were discussed and the performance of some of these techniques were evaluated in terms of running average error and root-mean-square error. Among the analyzed multipath mitigation techniques, RSSML, in general, achieved the best multipath mitigation performance in moderate-to-high C/N0 scenarios (for example, 30 dB-Hz and onwards). The other techniques, such as PT(Diff2) and HRC showed good multipath mitigation performance only in high C/N0 scenarios (for example, 40 dB-Hz and onwards). The other new technique SBME offered slightly better multipath mitigation performance to the well-known nEML DLL at the cost of an additional correlator. However, as the GNSS research area is fast evolving with many potential applications, it remains a challenging topic for future research to investigate the feasibility of these multipath mitigation techniques with the multitude of signal modulations, spreading codes, and spectrum placements that are (or are to be) proposed.publishedVersionPeer reviewe

ItsBlue: A Distributed Bluetooth-Based Framework for Intelligent Transportation Systems

Inefficiency in transportation networks is having an expanding impact, at a variety of levels. Transportation authorities expect increases in delay hours and in fuel consumption and, consequently, the total cost of congestion. Nowadays, Intelligent Transportation Systems (ITS) have become a necessity in order to alleviate the expensive consequences of the rapid demand on transportation networks. Since the middle of last century, ITS have played a significant role in road safety and comfort enhancements. However, the majority of state of the art ITS are suffering from several drawbacks, among them high deployment costs and complexity of maintenance. Over the last decade, wireless technologies have reached a wide range of daily users. Today\u27s Mobile devices and vehicles are now heavily equipped with wireless communication technologies. Bluetooth is one of the most widely spread wireless technologies in current use. Bluetooth technology has been well studied and is broadly employed to address a variety of challenges due to its cost-effectiveness, data richness, and privacy perverseness, yet Bluetooth utilization in ITS is limited to certain applications. However, Bluetooth technology has a potential far beyond today\u27s ITS applications. In this dissertation, we introduce itsBlue, a novel Bluetooth-based framework that can be used to provide ITS researchers and engineers with desired information. In the itsBlue framework, we utilize Bluetooth technology advantages to collect road user data from unmodified Bluetooth devices, and we extract a variety of traffic statistics and information to satisfy ITS application requirements in an efficient and cost-effective way. The itsBlue framework consists of data collection units and a central computing unit. The itsBlue data collection unit features a compact design that allows for stationary or mobile deployment in order to extend the data collection area. Central computing units aggregate obtained road user data and extract a number of Bluetooth spatial and temporal features. Road users’ Bluetooth features are utilized in a novel way to determine traffic-related information, such as road user context, appearance time, vehicle location and direction, etc. Extracted information is provided to ITS applications to generate the desired transportation services. Applying such a passive approach involves addressing several challenges, like discovering on-board devices, filtering out data received from vehicles out of the target location, or revealing vehicle status and direction. Traffic information provided by the itsBlue framework opens a wide to the development of a wide range of ITS applications. Hence, on top of the itsBlue framework, we develop a pack of intersection management applications that includes pedestrians’ volume and waiting times, as well as vehicle queue lengths and waiting times. Also, we develop a vehicle trajectory reconstruction application. The itsBlue framework and applications are thoroughly evaluated by experiments and simulations. In order to evaluate our work, we develop an enhanced version of the UCBT Network Simulator 2 (NS-2). According to evaluation outcomes, itsBlue framework and applications evaluations show promising results. For instance, the evaluation results show that the itsBlue framework has the ability to reveal road user context with accuracy exceeding 95% in 25s

Survey on Signal Processing for GNSS under Ionospheric Scintillation: Detection, Monitoring, and Mitigation

Ionospheric scintillation is the physical phenomena affecting radio waves coming from the space through the ionosphere. Such disturbance is caused by ionospheric electron density irregularities and is a major threat in Global Navigation Satellite Systems (GNSS). From a signal processing perspective, scintillation is one of the most challenging propagation scenarios, particularly affecting high-precision GNSS receivers and safety critical applications where accuracy, availability, continuity and integrity are mandatory. Under scintillation, GNSS signals are affected by amplitude and phase variations, which mainly compromise the synchronization stage of the receiver. To counteract these effects, one must resort to advanced signal processing techniques such as adaptive/robust methods, machine learning or parameter estimation. This contribution reviews the signal processing landscape in GNSS receivers, with emphasis on different detection, monitoring and mitigation problems. New results using real data are provided to support the discussion. To conclude, future perspectives of interest to the GNSS community are discussed

Satellite Selection Methodology for Horizontal Navigation and Integrity Algorithms

With the new upcoming GNSS constellation in the future it might no longer be possible to use all satellites in view for navigation due to limited tracking channels. This is in particular true in the context of Advanced Receiver Autonomous Integrity Monitoring (ARAIM), where the use of dual frequency is favorable to mitigate ionospheric disturbances. To address the issues of limited channels we propose two different satellites selection strategies adapted for Horizontal ARAIM in this paper. First a bare geometric approach which comes with almost no additional computation effort at the cost of less stable results. And second a heuristic optimization which improves selection results significantly while adding additional computational effort. Both approaches are compared to brute force selected best sets in terms of resulting protection levels, computational cost and achieved ARAIM availability. Results show the general applicability of both presented selection methods in Horizontal ARAIM. Using limited sets instead of all satellites in view can still provide global availability. Depending on the method more or less satellites are necessary to ensure sufficiently small and stable protection levels