Bayesian non-field-of-view target estimation incorporating an acoustic sensor

This paper presents non-field-of-view (NFOV) target estimation incorporating an acoustic sensor, which consists of two microphones. The proposed approach derives the interaural level difference (ILD) of observations from the two microphones for different target positions and stores the ILDs as database a priori. Given a new acoustic observation on a target, an acoustic observation likelihood is created by calculating the correlation of the ILD of the new observation to the stored ILDs. A joint observation likelihood is then developed by fusing the optical and acoustic observation likelihoods, and the recursive Bayesian estimation updates and maintains belief on the target using the joint observation likelihood. The proposed approach detects a target positively using an acoustic sensor even if it is outside the field of view of the optical sensor and localizes the target accurately by estimating it within the RBE. The efficacy of the proposed approach was first validated by experimental studies. Further numerical demonstrations then show the applicability of the proposed approach to the NFOV target estimation.