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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements

Authors :
Xu, Gehui
Chen, Guanpu
Fidan, Baris
Hong, Yiguang
Qi, Hongsheng
Parisini, Thomas
Johansson, Karl H.
Publication Year :
2024

Abstract

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multi-player non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies.<br />Comment: arXiv admin note: text overlap with arXiv:2311.03326, arXiv:2401.02471

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2407.04608
Document Type :
Working Paper