Towards a set-based detector for GNSS integrity monitoring

authored by: Jingyao Su, Steffen Schön, Mathieu Joerger
Abstract: This paper aims to evaluate the performance of the set-based fault detection. This approach differs from probabilistic residual-based (RB) or solution separation (SS) fault detection and exclusion methods utilized in the Receiver Autonomous Integrity Monitoring (RAIM) and Advanced RAIM. In the basic positioning model, measurement-level intervals are constructed based on the investigated error models and propagated in a linear manner using interval mathematics and set theory. Convex polytope solutions provide a measure of observation consistency formulated as a constraint satisfaction problem. Consistency checks performed using set operations facilitate multiple-fault detection. Choosing set-emptiness as the detection criterion can alleviate the need for multiple test statistics. In this paper, we formulate the fault detection problem in the context of measurement intervals and propose a framework of integrity monitoring for the set-based detection. Considering a probabilistic error model, we implement the set-based detection methods and assess its integrity performance using Monte Carlo simulations. These evaluations will serve as a basis for further development of efficient estimators and integrity monitors.
Organisation(s): Institute of Geodesy
Graduiertenkolleg 2159: Integrität und Kollaboration in dynamischen Sensornetzen
Leibniz Research Centre FZ:GEO
External Organisation(s): Virginia Polytechnic Institute and State University (Virginia Tech)
Type: Conference contribution
Pages: 421-429
No. of pages: 9
Publication date: 2023
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Electronic, Optical and Magnetic Materials, Control and Optimization, Aerospace Engineering, Instrumentation, Electrical and Electronic Engineering, Automotive Engineering
Research Area (based on ÖFOS 2012): Navigation systems, Mathematical statistics, Satellite geodesy
Electronic version(s): https://doi.org/10.1109/PLANS53410.2023.10139987 (Access: Closed)
: Details in the research portal "Research@Leibniz University"

BibTeX

@inproceedings{8e88f8a7af02426f8921d3062966a149,
title = "Towards a set-based detector for GNSS integrity monitoring",
abstract = "This paper aims to evaluate the performance of the set-based fault detection. This approach differs from probabilistic residual-based (RB) or solution separation (SS) fault detection and exclusion methods utilized in the Receiver Autonomous Integrity Monitoring (RAIM) and Advanced RAIM. In the basic positioning model, measurement-level intervals are constructed based on the investigated error models and propagated in a linear manner using interval mathematics and set theory. Convex polytope solutions provide a measure of observation consistency formulated as a constraint satisfaction problem. Consistency checks performed using set operations facilitate multiple-fault detection. Choosing set-emptiness as the detection criterion can alleviate the need for multiple test statistics. In this paper, we formulate the fault detection problem in the context of measurement intervals and propose a framework of integrity monitoring for the set-based detection. Considering a probabilistic error model, we implement the set-based detection methods and assess its integrity performance using Monte Carlo simulations. These evaluations will serve as a basis for further development of efficient estimators and integrity monitors.",
keywords = "error modeling, fault detection, GNSS integrity, interval mathematics, set theory",
author = "Jingyao Su and Steffen Sch{\"o}n and Mathieu Joerger",
note = "Funding Information: This work was supported by the German Research Foundation as part of the Research Training Group 2159: Integrity and Collaboration in Dynamic Sensor Networks (i.c.sens).; 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), PLANS 2023 ; Conference date: 24-04-2023 Through 27-04-2023",
year = "2023",
doi = "10.1109/PLANS53410.2023.10139987",
language = "English",
isbn = "978-1-6654-1773-0",
series = "IEEE/ION Position Location and Navigation Symposium",
publisher = "IEEE",
pages = "421--429",
booktitle = "2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)",
url = "https://www.ion.org/plans/",
}