Proceedings ArticleDOI
A Rényi Divergence Based Approach to Fault Detection and Exclusion for Tightly Coupled GNSS/INS System
Changwei Chen,Solmaz S. Kia +1 more
- pp 674-687
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TLDR
A residual-based fault detection and exclusion (FDE) algorithm is developed to enhance the performance of the tightly coupled Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) system using Renyi divergence and its modification as the measure to evaluate whether there exists a fault in the system.Abstract:
In this paper, a residual-based fault detection and exclusion (FDE) algorithm is developed to enhance the performance of the tightly coupled Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) system. Specifically, Renyi divergence (RD) and its modification are introduced as the measure to evaluate the distance/divergence between the state estimate of propagation and update steps to indicate whether there exists a fault in the system. The properties of this indicator mechanism are discussed analytically in detail. An FDE algorithm is constructed based on this divergence measure. Appropriate methods to select the parameters of the proposed divergence measure to increase the probability of the fault detection and decrease the false alarm rate of the FDE algorithm are proposed. The results are demonstrated and validated in the Computer Aided Design of Aerospace Concepts (CADAC++) flight simulation platform.read more
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A state-domain robust autonomous integrity monitoring with an extrapolation method for single receiver positioning in the presence of slowly growing fault
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References
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Journal ArticleDOI
Rényi divergence measures for commonly used univariate continuous distributions
TL;DR: Close-form expressions for the Renyi and Kullback–Leibler divergences for nineteen commonly used univariate continuous distributions as well as those for multivariate Gaussian and Dirichlet distributions are presented.
Journal ArticleDOI
An optimal fault detection threshold for early detection using Kullback-Leibler Divergence for unknown distribution data
TL;DR: An incipient fault detection method that does not need any a priori information on the signals distribution or the changed parameters is proposed and an analytical model of the fault detection performances (False Alarm Probability and Missed Detection Probability) is developed.
Journal ArticleDOI
An information theoretic approach to the distributed detection problem
TL;DR: In this article, the authors considered the distributed detection problem from an information-theoretic point of view, and an entropy-based cost function was used for system optimization, which maximizes the amount of information transfer between the input and the output.
Proceedings Article
An information theoretic approach to the distributed detection problem
TL;DR: The distributed detection problem is considered from an information-theoretic point of view, and an entropy-based cost function is used for system optimization.
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