Time Domain Spherical Harmonic Analysis for Adaptive Noise Cancellation over a Spatial Region

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    18 Citations (Scopus)

    Abstract

    Active Noise Cancellation (ANC) is a well researched topic for minimizing unwanted acoustic noise, and spatial ANC is a recently introduced concept that focuses on continuous spatial regions. Adaptive filter designing for spatial ANC is often based on frequency-domain spherical harmonic decomposition method, which has a major limitation due to the increased system latency. In this paper, we develop a time-domain spherical harmonic based signal decomposition method and use it to develop two time-space domain feed-forward adaptive filters for spatial ANC. Through simulations we show that the proposed methods can achieve higher noise reduction performance over the control region with microphones located on the surface of the region compared to the conventional time-domain adaptive filter.

    Original languageEnglish
    Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages516-520
    Number of pages5
    ISBN (Electronic)9781479981311
    DOIs
    Publication statusPublished - May 2019
    Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
    Duration: 12 May 201917 May 2019

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume2019-May
    ISSN (Print)1520-6149

    Conference

    Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
    Country/TerritoryUnited Kingdom
    CityBrighton
    Period12/05/1917/05/19

    Fingerprint

    Dive into the research topics of 'Time Domain Spherical Harmonic Analysis for Adaptive Noise Cancellation over a Spatial Region'. Together they form a unique fingerprint.

    Cite this