Fault tolerant fusion approach based on information theory applied on GNSS localization

In this work, we present an informational framework able to guarantee high integrity of data fusion method. The proposed framework is designed using a bank of Information Filters (IF) and information theory metrics in order to develop a monitoring method which able to detect and exclude faulty data. The decision of faults detection and exclusion are examined through a coherence test elaborated using the Conditional Informational Entropy (CIE) metric. The proposed test is directly connected to the convergence of the information filters. Since the Chi-square test is one of the classical used tests in the Faults Detection and Exclusion (FDE) procedure using Kalman Filter (KF), a relationship between the proposed test and the Chi-square one is established. Through real GPS measurements, the performance of the proposed framework is shown.