Wavefield separation projector processing with a prioriknowledge for acoustic source localization in rooms

In bounded media, wavefield separation projector is an array processing used to extract the direct path from the reverberated ones. Associated with a simple sparse localization algorithm, it makes an attractive method for source localization in rooms of unknown shape. However, the large number of microphones required by the method can prevent its applicability. In this work, we propose to add three different a priori knowledge to dramatically decrease the number of microphones. First, an estimation of the critical distance allows to reduce the required rank of the projection operator and therefore the number of receivers. The second method increases the number of receivers thanks to “virtual measurements” on the boundaries, when the room geometry is partially known. Finally, the last method requires a simple calibration step based on the passive recovering of the Green’s functions between all the pairs of microphones, which also extends the model to weakly inhomogeneous propagation medium. The properties of the 3 methods are discussed. We show numerically and experimentally that these methods lead to a precise source localization, with a moderate number of microphones.