Abstract
A global navigation satellite system (GNSS)-based navigation is a challenging task in a signal-degraded environments where GNSS signals are distorted by multipath and attenuated by fading effects: the navigation solution may be inaccurate or unavailable. A possible approach to improve accuracy and availability is the joint use of measurements from different GNSSs and quality check algorithms; this approach is investigated here using live GPS and Galileo signals. A modified receiver autonomous integrity monitoring (RAIM) algorithm, including geometry and separability checks, is proposed to detect and exclude erroneous measurements: the multi-constellation approach provides redundant measurements, and RAIM exploits them to exclude distorted observations. The synergy between combined GPS/Galileo navigation and RAIM is analyzed using live data; the performance is compared to the accuracy and availability of a GPS-only solution. The tests performed demonstrate that the methods developed are effective techniques for GNSS-based navigation in signal-degraded environments. The joint use of the multi-constellation approach and of modified RAIM algorithms improves the performance of the navigation system in terms of both accuracy and availability.
Highlights
Geolocation, i.e., the process of identifying the position of a given object, is present in everyday life; for example, mobile devices, be they smart phones or tablets, are generally equipped with a GPS receiver and cameras, so a user can geo-localize a picture taken with the device
The first one is the time percentage when the solution is computed: this parameter is used for the configuration without receiver autonomous integrity monitoring (RAIM); whereas the reliable availability (RA) is the percentage of time when the solution is computed and declared reliable: this parameter is used when the RAIM algorithms are performed
The integrity flag related to the velocity solutions is plotted as a function of time in in the velocity domain, data are characterized by a high solution availability (SA), which is 95% in the case of GPS only: the inclusion of the Galileo measurements improves the SA by about 5%
Summary
Geolocation, i.e., the process of identifying the position of a given object, is present in everyday life; for example, mobile devices, be they smart phones or tablets, are generally equipped with a GPS receiver and cameras, so a user can geo-localize a picture taken with the device. Measurements can be affected by gross errors induced by signal attenuation, multipath and fading effects In this case, the redundancy provided by the multi-constellation approach has to be exploited to isolate and exclude distorted observations. RAIM is a technique that exploits only the information available using a GNSS receiver; RAIM algorithms may detect user-level errors [1] Such techniques are used for quality monitoring to identify, and eventually exclude, observables affected by gross errors [11]. The proposed algorithm provides improved performance with respect to the classical FB algorithm exploiting the introduction of a preliminary check to verify the geometry conditions Such a test has been adopted since the capabilities of detecting outliers is highly dependent on the measurement redundancy.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
