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.