Cooperative Magneto-Inductive Localization
Henry Schulten, Gregor Dumphart, Antonios Koskinas, Armin Wittneben

TL;DR
This paper introduces a cooperative magneto-inductive localization method for wireless sensor networks, significantly improving accuracy by jointly estimating multiple agent positions using a novel high-dimensional least-squares approach.
Contribution
It presents the first study of cooperative localization in magneto-inductive networks, including new closed-form MLE formulas and an algorithm to reliably compute high-accuracy position estimates.
Findings
Achieved a factor of 3 accuracy improvement with 10 agents.
Derived the Cramér-Rao lower bound for this localization problem.
Proposed an algorithm that reliably finds the MLE in high-dimensional space.
Abstract
Wireless localization is a key requirement for many applications. It concerns position estimation of mobile nodes (agents) relative to fixed nodes (anchors) from wireless channel measurements. Cooperative localization is an advanced concept that considers the joint estimation of multiple agent positions based on channel measurements of all agent-anchor links together with all agent-agent links. In this paper we present the first study of cooperative localization for magneto-inductive wireless sensor networks, which are of technological interest due to good material penetration and channel predictability. We demonstrate significant accuracy improvements (a factor of 3 for 10 cooperating agents) over the non-cooperative scheme. The evaluation uses the Cram\'er-Rao lower bound on the cooperative position estimation error, which is derived herein. To realize this accuracy, the…
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