Maximum likelihood estimator for magneto-acoustic localisation

This paper is devoted to the localization of magneto-acoustic sources moving in a straight line at a constant speed. Our technique is based on the association of narrow band acoustic signals and magnetostatic measurements. First of all, we describe features that make possible the association of magnetic and acoustic data, secondly, we show that the positioning accuracy is much improved by this association. We focus on solving the problem with as few sensors as possible. A geometric discussion of identifiability is proposed, as well as a batch maximum likelihood estimator whose covariance matrix asymptotically achieves Cramer Rao lower bounds (CRLB)