Joint Adaptive Impulse Response Estimation and Inverse Filtering for Enhancing In-Car Audio

Performance of conventional audio equalization methods for improving in-car audio listening experience is limited by the uncertainties in computing the highly varying in-car channel response. Hence these methods generally compute the channel response which is then utilized in designing the inverse filter. In this paper, a novel adaptive equalization method is developed where the channel impulse response and inverse filter are jointly estimated. The method iteratively estimates the uncertainties in the channel response using a Kalman filter and updates the inverse filter gains at every step. The joint estimation method is thus adaptive and robust to the highly varying in-car acoustic conditions. Additional contributions of this work include the development of a car database that captures impulse responses and noise samples under various in-car conditions. Both subjective and objective evaluations are performed to show the performance improvements obtained using the proposed method.