Position estimation of rotating sound source using Kalman filtering based on time difference of arrival measurements

Abstract

In this work, we are interested in tracking a rotating sound source using a Kalman filtering technique based on a set of non-linear time difference of arrival (TDOA) measurements. Array of microphones measure acoustic signal emitted from a rotating source and the TDOA estimates are calculated followed by a solution for hyperbolic position fix. The position estimation of sound source based on TDOA is a popular technique in source localization. The method involves calculation of a set of nonlinear equations and poor accuracy of TDOA estimates often results in inaccuracy in location. In this work, the range difference is expressed by a model movement on which a recursive extended Kalman Filter has been developed. The TDOA measurements optimize the estimated values which are reduced as observation in extended Kalman filtering algorithm. Location estimation is updated from TDOA measurements along with the time history data. The Cramer-Rao Lower Bound (CRLB) is derived and simulations are compared. [Work supported by National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2010-0014978).]