Directional active noise control for drone noise reduction

Drones have become essential tools for applications ranging from aerial surveillance to last-mile delivery, raising concerns about noise pollution in populated environments. This paper presents a directional active noise control (ANC) framework that targets far-field noise reduction, rather than local suppression. A virtual microphone-based ANC algorithm is employed, using a near-drone microphone array to attenuate noise in a specific region. Experiments in a semi-anechoic chamber show an average reduction of 4.78 dB in the 1500-2400 Hz band and up to 10 dB at harmonic frequencies, highlighting the promise of directional ANC for quieter drone operations in sensitive settings.

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Publication Details

Journal
JASA Express Letters
Published
2025-12-01
DOI
https://doi.org/10.1121/10.0039953
Primary Topic
Advanced Adaptive Filtering Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Directional active noise control for drone noise reduction

Thushara D. Abhayapala, Yile Zhang, Hanwen Bi, Prasanga N. Samarasinghe
JASA Express Letters
Advanced Adaptive Filtering Techniques
article

Directional active noise control for drone noise reduction

Thushara D. Abhayapala, Yile Zhang, Hanwen Bi, Prasanga N. Samarasinghe
article en

Abstract

Drones have become essential tools for applications ranging from aerial surveillance to last-mile delivery, raising concerns about noise pollution in populated environments. This paper presents a directional active noise control (ANC) framework that targets far-field noise reduction, rather than local suppression. A virtual microphone-based ANC algorithm is employed, using a near-drone microphone array to attenuate noise in a specific region. Experiments in a semi-anechoic chamber show an average reduction of 4.78 dB in the 1500-2400 Hz band and up to 10 dB at harmonic frequencies, highlighting the promise of directional ANC for quieter drone operations in sensitive settings.

JASA Express LettersVol. 5(12)
Australian National University (AU)
Openalex Percentile: Top 61%
Advanced Adaptive Filtering Techniques
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