Practical DOA Estimation via a Network of DOA-Blind Sensors

We consider the problem of DOA (direction of arrival) estimation of an acoustic wavefront by a wireless sensor network (WSN) within the SENMA architecture (a mobile agent (MA) repeatedly polls the sensors lying inside its field of view). The sensors, which are random in number and location, are DOA-blind and simply emit a pulse train synchronized to the acoustic event\´s passage; taken in aggregate, however, the MA can exploit its non-isotropic field of view (FOV) to infer an accurate DOA. In this paper we (i) use a more realistic "soft" FOV; (ii) account for multiple sources; and (iii) suggest a strategy for the MA. We find that the presence of more than one source can improve DOA estimation, and also that an optimal strategy for the MA squints near the expected DOA, as opposed to directly at it.