Cooperative fault detection and recovery in the GNSS positioning of mobile agent swarms based on relative distance measurements

Abstract

Relative measurements are exploited to cooperatively detect and recover faults in the positioning of Mobile Agent (MA) Swarms (MASs). First, a network vertex fault detection method based on edge testing is proposed. For each edge, a property that has a functional relationship with the properties of its two vertices is measured and tested. Based on the edge testing results of the network, the maximum likelihood principle is used to identify the vertex fault sources. Second, an edge distance testing method based on the noncentral chi-square distribution is developed for detecting faults in the Global Navigation Satellite System (GNSS) positioning of MASs. Third, a recovery strategy for faults in the positioning of MASs based on distance measurement is provided. The effectiveness of the proposed methods is validated by a simulation case in which an MAS passes through a GNSS spoofing zone. The proposed methods are conducive to increasing the robustness of the positioning of MASs in complex environments. The main novelties include the following: (A) network vertex fault detection is based on concrete probability analysis rather than simple majority voting, and (B) the relation of detectability and recoverability of MAS positioning faults with the structure of the relative measurement network is first disclosed.