Fast Online Source Steering Algorithm for Tracking Single Moving Source Using Online Independent Vector Analysis

We address the problem of separating moving sources using an online independent vector analysis (IVA). To solve this problem, researchers have extended the iterative projection (IP) and iterative source steering (ISS) algorithms developed for the batch auxiliary-function-based IVA (AuxIVA) to online scenarios and showed their effectiveness. However, the conventional online IP and ISS are slow because they update K × K covariance matrices for all sources, where K is the number of microphones. Here we show that, in a target-source tracking scenario in which only one source moves, there exists an inexpensive formula for the online ISS that avoids updating the full covariance matrices without changing the behavior of the algorithm at all. The time complexity of the proposed algorithm, which we call online source steering (OSS), is 1/K times smaller than that of the conventional online IP and online ISS for the target-source tracking task. A numerical experiment of separating a moving source demonstrates that the proposed OSS is significantly faster than the conventional online IP and online ISS.