Eigenanalysis-based broadband source localization

The localization process consists in finding the candidate source location that maximizes the synchrony between the properly time-shifted microphone outputs. In addition to using well-known crosscorrelation-based criteria such as the steered response power (SRP), minimum variance (MV), and multichannel crosscorrelation (MCCC), this synchrony can be measured using the averaged magnitude difference function (AMDF) and the averaged magnitude sum function (AMSF) whose calculations involve low computational cost. In this paper, we study the crosscorrelation and AMDF (with AMSF) based approaches using an arbitrary number of microphones. Specifically, we use the eigenanalysis of the parameterized spatial correlation matrix (PSCM) to first provide a unifying study of the most popular crosscorrelation-based techniques. Then, we show the efficiency of the AMDF and AMSF in localizing an acoustic source using multiple microphones by proposing two new parameterized matrices named as the parameterized averaged magnitude difference matrix (PAMDM) and the parameterized averaged magnitude sum matrix (PAMSM). The eigenanalysis of these two matrices reveals new criteria.