Greedy Detection and Exclusion of Multiple Faults using Euclidean Distance Matrices

TL;DR

This paper introduces a fast, greedy Euclidean distance matrix-based fault detection and exclusion method for GNSS signals, validated on simulated and real-world datasets, offering comparable accuracy with significantly reduced computation time.

Contribution

The paper presents a novel, simplified greedy EDM FDE algorithm with a new test statistic and exclusion strategy, improving computational efficiency over previous methods.

Findings

Order of magnitude faster computation than residual FDE

Similar fault exclusion accuracy to existing methods

Validated on diverse simulated and real-world datasets

Abstract

Numerous methods have been proposed for global navigation satellite system (GNSS) receivers to detect faulty GNSS signals. One such fault detection and exclusion (FDE) method is based on the mathematical concept of Euclidean distance matrices (EDMs). This paper outlines a greedy approach that uses an improved Euclidean distance matrix-based fault detection and exclusion algorithm. The novel greedy EDM FDE method implements a new fault detection test statistic and fault exclusion strategy that drastically simplifies the complexity of the algorithm over previous work. To validate the novel greedy EDM FDE algorithm, we created a simulated dataset using receiver locations from around the globe. The simulated dataset allows us to verify our results on 2,601 different satellite geometries. Additionally, we tested the greedy EDM FDE algorithm using a real-world dataset from seven different android phones. Across both the simulated and real-world datasets, the Python implementation of the greedy EDM FDE algorithm is shown to be computed an order of magnitude more rapidly than a comparable greedy residual FDE method while obtaining similar fault exclusion accuracy. We provide discussion on the comparative time complexities of greedy EDM FDE, greedy residual FDE, and solution separation. We also explain potential modifications to greedy residual FDE that can be added to alter performance characteristics.