A Geometric Approach to Passive Localisation

TL;DR

This paper introduces a geometric framework for passive emitter localisation using mobile sensors, focusing on bounding emitter positions without probabilistic models, and evaluates decision strategies within this framework.

Contribution

It presents a novel geometric approach for passive localisation that does not rely on probabilistic models and demonstrates its effectiveness through decision-making strategies.

Findings

Effective boundaries on emitter positions established

Greedy decision strategy minimizes uncertainty

Robustness and emergent behaviour analyzed

Abstract

In this paper, we present a geometric framework for the passive localisation of static emitters. The objective is to localise the position of the emitters in a given area by centralised coordination of mobile passive sensors. This framework uses only the geometry of the problem to minimise the maximal bounds of the emitters' locations without using a belief or probability distribution. This geometric approach provides effective boundaries on the emitters' position. It can also be useful in evaluating different decision-making strategies for coordinating mobile passive sensors and complementing statistical methods during the initialisation process. The effectiveness of the geometric approach is shown by designing and evaluating a greedy decision-making strategy, where a sensor selects its future position by minimising the maximum uncertainty on its next measurement using one of the global objective functions. Finally, we analyse and discuss the emergent behaviour and robustness of the proposed algorithms.