A Delayless Frequency-Domain Kalman Filter with Improved Tracking Capability for Acoustic Feedback Cancellation

Cai Xia Lu; Fei Ran Yang; Jun Yang

doi:10.3969/j.issn.0372-2112.2018.08.021

A Delayless Frequency-Domain Kalman Filter with Improved Tracking Capability for Acoustic Feedback Cancellation

Cai Xia Lu, Fei Ran Yang, Jun Yang^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

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.

Original language	English
Pages (from-to)	1954-1959
Number of pages	6
Journal	Tien Tzu Hsueh Pao/Acta Electronica Sinica
Volume	46
Issue number	8
DOIs	https://doi.org/10.3969/j.issn.0372-2112.2018.08.021
Publication status	Published - Aug 1 2018
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2018, Chinese Institute of Electronics. All right reserved.

ASJC Scopus Subject Areas

Electrical and Electronic Engineering

Keywords

Acoustic feedback cancellation
Frequency-domain adaptive algorithm
Kalman filtering
Tracking ability

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10.3969/j.issn.0372-2112.2018.08.021

Cite this

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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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N2 - 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.

AB - 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.

KW - Acoustic feedback cancellation

KW - Frequency-domain adaptive algorithm

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KW - Tracking ability

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A Delayless Frequency-Domain Kalman Filter with Improved Tracking Capability for Acoustic Feedback Cancellation

Abstract

Bibliographical note

ASJC Scopus Subject Areas

Keywords

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