Under-ranked localization of acoustically tagged mobile marine animals

We consider the challenge of localizing and tracking of underwater acoustically tagged mobile marine fauna by a sparse set of receiving anchors. Due to sea conditions and the low power of the tags, often the tags' emissions are received by less than three receivers, and localization ambiguities arise. Moreover, the transmitter-only tags cannot be assumed time synchronize with the set of receivers. Our solution is based on the concept of time-difference of arrival. To solve the localization ambiguities, we propagate prior solutions while constraining the expected motion of the mobile animal. Specifically, we model the position states as a Hidden Markov Model, and solve the remaining ambiguities based on the Forward-Backward algorithm. Numerical results show that the proposed method provides accurate localization performance that can greatly increase the geographical localization and tracking area.