A Delayless Frequency-Domain Kalman Filter with Improved Tracking Capability for Acoustic Feedback Cancellation
LU Cai-xia1,2, YANG Fei-ran1, YANG Jun1,2
1. Key Laboratory of Noise and Vibration Research, Institute of Acoustic, Chinese Academy of Sciences, Beijing 100190, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China
Abstract：The partitioned block frequency-domain Kalman filter (PBFDKF) is appealing due to its fast convergence speed,low steady-state misalignment and small inherent delay.However,the tracking ability of the PBFDKF is poor.In this paper,we firstly analyze the tracking performance of the PBFDKF and then we propose an improved PBFDKF-based adaptive feedback cancellation algorithm.Moreover,we present a new delayless implementation with lower complexities.Simulation results demonstrate the performance advantage of the proposed algorithm.
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2018, Vol. 46 
