Abstract-In this paper, we consider a novel and robust maximum likelihood approach to localizing radiation sources with unknown statistics of the source signal strength. The result utilizes the smallest number of sensors required theoretically to localize the source. It is shown, that should the source lie in the open convex hull of the sensors, precisely N + 1 are required in R N , N ∈ {1, · · · , 3}. It is further shown that the region of interest, the open convex hull of the sensors, is entirely devoid of false stationary points. An augmented gradient ascent algorithm with random projections should an estimate escape the convex hull is presented.
REF uses a ML-localization framework for the localization of a source with unknown intensity, guaranteeing no false stationary points as long as the source lies in the open convex hull formed by the sensors.
Maximum Likelihood Localization of Radiation Sources with unknown Source Intensity
arXiv: Optimization and Control
Mathematics Physics