Underdetermined DOA Estimation via Independent Component Analysis and Time-Frequency Masking

This paper presents an algorithm for the estimation of the direction of arrival (DOA) in underdetermined situations, that is, there is more sources than sensors. The algorithm performs the estimation in an iterative manner, each iteration consists of two-steps: first estimation of the DOA of a dominant source via the Independent Component Analysis and then removal of the detected source from the mixture via time-frequency masking. Experiments, performed using speech signals mixed in real environment when only two microphones are used but three and four sources are present, demonstrate that the proposed algorithm can estimate the DOAs more accurately than two previously used underdetermined DOA algorithms.