학술논문

Invariance Approach to Integrity Monitoring Fault Detectors
Document Type
Periodical
Source
IEEE Signal Processing Letters IEEE Signal Process. Lett. Signal Processing Letters, IEEE. 30:1062-1066 2023
Subject
Signal Processing and Analysis
Computing and Processing
Communication, Networking and Broadcast Technologies
Detectors
Fault detection
Testing
Monitoring
Covariance matrices
Indexes
Global navigation satellite system
GLRT
integrity monitoring
invariant detectors
RAIM
solution separation
Language
ISSN
1070-9908
1558-2361
Abstract
This contribution explores the optimality properties of integrity monitoring fault detectors by exploiting the hypothesis testing invariance theory. The focus is on three fault detectors widely used in GNSS: the Generalized Likelihood Ratio Test (GLRT), the Least Squares (LS) residuals method, and the Solution Separation (SS) test statistics. The GLRT has been shown to be uniformly most powerful invariant for linear Gaussian models, and the single-state SS test statistic has been proven to be the optimal detector which minimizes the so-called worst-case integrity risk, if the LS estimator is used to estimate the unknown state vector. This work aims i) to make the connection between these two optimal detectors within the invariance framework, and ii) to establish the conditions for their equivalence in the case of a single alternative faulty hypothesis.