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International Journal of Navigation and Observation
Volume 2014 (2014), Article ID 173818, 11 pages
Research Article

P-RANSAC: An Integrity Monitoring Approach for GNSS Signal Degraded Scenario

Department of Science and Technology, Centro Direzionale di Napoli, Parthenope University of Naples, Isola C4, 80143 Naples, Italy

Received 27 May 2014; Revised 5 September 2014; Accepted 8 September 2014; Published 23 September 2014

Academic Editor: Sandro M. Radicella

Copyright © 2014 Gaetano Castaldo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Satellite navigation is critical in signal-degraded environments where signals are corrupted and GNSS systems do not guarantee an accurate and continuous positioning. In particular measurements in urban scenario are strongly affected by gross errors, degrading navigation solution; hence a quality check on the measurements, defined as RAIM, is important. Classical RAIM techniques work properly in case of single outlier but have to be modified to take into account the simultaneous presence of multiple outliers. This work is focused on the implementation of random sample consensus (RANSAC) algorithm, developed for computer vision tasks, in the GNSS context. This method is capable of detecting multiple satellite failures; it calculates position solutions based on subsets of four satellites and compares them with the pseudoranges of all the satellites not contributing to the solution. In this work, a modification to the original RANSAC method is proposed and an analysis of its performance is conducted, processing data collected in a static test.