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arXiv · 1711.10153

Source Localisation Using Binary Measurements

Daniel D. Selvaratnam·Iman Shames·Jonathan H. Manton·Branko Ristic
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Abstract

This paper considers the problem of localising a stationary signal source using a team of mobile agents which only take binary measurements. Background false detection rates and missed detection probabilities are incorporated into the framework. A Bayesian estimation algorithm that discretises the search environment is employed, and analytical convergence and consistency results for this are derived. Fisher Information is then used as a metric for the design of optimal agent geometries. Knowledge of the probability of detection as a function of the source and agent locations is assumed in the analysis, with special attention given to range-dependent functions. The behaviour of the algorithm under inexact knowledge of the probability of detection is also analysed. Finally, simulation results are presented to demonstrate the effectiveness of the algorithm.

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Daniel D. Selvaratnam, Iman Shames, Jonathan H. Manton, Branko Ristic. 2018-09-12. Source Localisation Using Binary Measurements. https://arxiv.org/abs/1711.10153

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