Prefiltering Approach of Adaptive Eigenvalue Decomposition Method for an Improved Time Delay Estimation in Room Environment

Time delay estimation is an essential step in sound source localization and beamforming systems, and an extensive amount of research has been performed on this subject. This task entails the accurate estimation of the relative time delay between two microphone signals originating from the same source. To overcome the limitations of the existing methods, the adaptive eigenvalue decomposition (AED) algorithm was developed for time delay estimation in reverberant acoustic environments in the early 2000s. This paper attempts to improve delay estimation performance using autoregressive model-based prefiltering for the AED algorithm. The proposed method establishes an autoregressive model of the room impulse response beforehand. Then, the model is utilized as a linear prediction filter to remove the reverberation component from the microphone signals, which improves the estimation capability of the algorithm. Monte Carlo experiments are performed to demonstrate the improved performance for various reverberation levels and signal-to-noise ratios. Provided that the noise level is moderate, the proposed method is shown to greatly increase the accuracy of the conventional approach in a highly reverberant room.