Source Localisation Using Binary Measurements

This paper considers the problem of localising a signal source using a team of mobile agents that can only detect the presence or absence of the signal. Background false detection rates and missed detection probabilities are incorporated into the framework. A Bayesian estimation algorithm is proposed that discretises the search environment into cells, 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. The behaviour of the algorithm under incomplete knowledge of this function is also analysed. Finally, simulation results are presented to demonstrate the effectiveness of the algorithm.

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