Associating acoustic transients for localization by multiple arrays.

Abstract

This paper first presents two methods to estimate the location of an acoustic transient based on measurements of its time‐of‐arrival and direction‐of‐arrival at a set of microphone arrays. One is a least‐square (LS) estimator, the other a maximum likelihood (ML) estimator. Both are compared to the Cramer–Rao lower bound for reference. They are then extended to associate detections (of the same event) at different arrays by a maximum a posteriori (MAP) formulation that can sort out outliers and multipath detections while re‐using the likelihood values computed in the first part. Simulations show that the LS estimator performs slightly better than the ML estimator when the observation noise does not match the noise model. Both methods exhibit a bias in the range estimate, which accounts for most of the square error. The MAP estimator, applied to live fire data, was accurate and successfully resolved simultaneous multiple targets from outlier and multipath noise.