Abstract
The acoustic environment affects the properties of the audio signals recorded. Generally, given room impulse responses (RIRs), three sets of parameters have to be extracted in order to create an acoustic model of the environment: sources, sensors and reflector positions. In this paper, the cross-correlation based iterative sensor position estimation (CISPE) algorithm is presented, a new method to estimate a microphone configuration, together with source and reflector position estimators. A rough measurement of the microphone positions initializes the process; then a recursive algorithm is applied to improve the estimates, exploiting a delay-and-sum beamformer. Knowing where the microphones lie in the space, the dynamic programming projected phase slope algorithm (DYPSA) extracts the times of arrival (TOAs) of the direct sounds from the RIRs, and multiple signal classification (MUSIC) extracts the directions of arrival (DOAs). A triangulation technique is then applied to estimate the source positions. Finally, exploiting properties of 3D quadratic surfaces (namely, ellipsoids), reflecting planes are localized via a technique ported from image processing, by random sample consensus (RANSAC). Simulation tests were performed on measured RIR datasets acquired from three different rooms located at the University of Surrey, using either a uniform circular array (UCA) or uniform rectangular array (URA) of microphones. Results showed small improvements with CISPE pre-processing in almost every case.