Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source

Flying unmanned aerial vehicles (UAVs) in swarms can have numerous advantages. However, to maintain a safe distance between them during flight is very challenging. To achieve this, each UAV in the swarms needs to know its relative location with respect to one another. This work proposes a method for...

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Main Authors: Syaril, Azrad, Salman, Abdulaziz, Al-Haddad, Syed Abdul Rahman
Format: Article
Language:English
Published: Aeronautical and Astronautical Society of the Republic of China 2024
Online Access:http://psasir.upm.edu.my/id/eprint/111185/1/Performance%20of%20DOA%20Estimation%20Algorithms%20for%20Acoustic%20Localization%20of%20Indoor%20Flying%20Drones%20Using%20Art.pdf
http://psasir.upm.edu.my/id/eprint/111185/
https://www.airitilibrary.com/Article/Detail/P20140627004-N202403020027-00035
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spelling my.upm.eprints.1111852024-06-22T15:05:38Z http://psasir.upm.edu.my/id/eprint/111185/ Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source Syaril, Azrad Salman, Abdulaziz Al-Haddad, Syed Abdul Rahman Flying unmanned aerial vehicles (UAVs) in swarms can have numerous advantages. However, to maintain a safe distance between them during flight is very challenging. To achieve this, each UAV in the swarms needs to know its relative location with respect to one another. This work proposes a method for relative localization using the chirping sound emitted from UAVs flying together indoors. The strategy is simulated to assess localization performance of three different types of chirping sounds indoors using six microphone arrays. The estimated direction of arrival (DOA) of the chirping sound is calculated using several published algorithms that include MUSIC, CSSM, SRP-PHAT, TOPS and WAVES. The sound is produced in a simulated flying indoor environment with several different settings of sound-to-noise ratio (SNR) and reverberation time (RT). Based on the results, it has been found that chirping sound with a wider frequency band produced better results in terms of mean values of DOA estimation error. The chirping sound performance is also tested with the actual UAVs operating under different rotor speeds. Similarly, it is observed that the chirping sound with wider band also produced better results in three of the algorithms, which is reflected in their absolute mean error. Nevertheless, further work has to be done to filter out the UAVs’ rotor noise and also the indoor reverberation effects for better performance. Aeronautical and Astronautical Society of the Republic of China 2024-03 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/111185/1/Performance%20of%20DOA%20Estimation%20Algorithms%20for%20Acoustic%20Localization%20of%20Indoor%20Flying%20Drones%20Using%20Art.pdf Syaril, Azrad and Salman, Abdulaziz and Al-Haddad, Syed Abdul Rahman (2024) Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source. Journal of Aeronautics, Astronautics and Aviation, 56 (1S). pp. 469-476. ISSN 1990-7710 https://www.airitilibrary.com/Article/Detail/P20140627004-N202403020027-00035 10.6125/JoAAA.202403_56(1S).34
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Flying unmanned aerial vehicles (UAVs) in swarms can have numerous advantages. However, to maintain a safe distance between them during flight is very challenging. To achieve this, each UAV in the swarms needs to know its relative location with respect to one another. This work proposes a method for relative localization using the chirping sound emitted from UAVs flying together indoors. The strategy is simulated to assess localization performance of three different types of chirping sounds indoors using six microphone arrays. The estimated direction of arrival (DOA) of the chirping sound is calculated using several published algorithms that include MUSIC, CSSM, SRP-PHAT, TOPS and WAVES. The sound is produced in a simulated flying indoor environment with several different settings of sound-to-noise ratio (SNR) and reverberation time (RT). Based on the results, it has been found that chirping sound with a wider frequency band produced better results in terms of mean values of DOA estimation error. The chirping sound performance is also tested with the actual UAVs operating under different rotor speeds. Similarly, it is observed that the chirping sound with wider band also produced better results in three of the algorithms, which is reflected in their absolute mean error. Nevertheless, further work has to be done to filter out the UAVs’ rotor noise and also the indoor reverberation effects for better performance.
format Article
author Syaril, Azrad
Salman, Abdulaziz
Al-Haddad, Syed Abdul Rahman
spellingShingle Syaril, Azrad
Salman, Abdulaziz
Al-Haddad, Syed Abdul Rahman
Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
author_facet Syaril, Azrad
Salman, Abdulaziz
Al-Haddad, Syed Abdul Rahman
author_sort Syaril, Azrad
title Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
title_short Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
title_full Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
title_fullStr Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
title_full_unstemmed Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
title_sort performance of doa estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
publisher Aeronautical and Astronautical Society of the Republic of China
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/111185/1/Performance%20of%20DOA%20Estimation%20Algorithms%20for%20Acoustic%20Localization%20of%20Indoor%20Flying%20Drones%20Using%20Art.pdf
http://psasir.upm.edu.my/id/eprint/111185/
https://www.airitilibrary.com/Article/Detail/P20140627004-N202403020027-00035
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score 13.18916