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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| Format: | Article |
| Language: | English |
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Aeronautical and Astronautical Society of the Republic of China
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/111185/ http://psasir.upm.edu.my/id/eprint/111185/1/Performance%20of%20DOA%20Estimation%20Algorithms%20for%20Acoustic%20Localization%20of%20Indoor%20Flying%20Drones%20Using%20Art.pdf |
| _version_ | 1848865618350047232 |
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| author | Syaril, Azrad Salman, Abdulaziz Al-Haddad, Syed Abdul Rahman |
| author_facet | Syaril, Azrad Salman, Abdulaziz Al-Haddad, Syed Abdul Rahman |
| author_sort | Syaril, Azrad |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T14:07:34Z |
| format | Article |
| id | upm-111185 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:07:34Z |
| publishDate | 2024 |
| publisher | Aeronautical and Astronautical Society of the Republic of China |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| 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 |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/111185/ http://psasir.upm.edu.my/id/eprint/111185/ http://psasir.upm.edu.my/id/eprint/111185/ http://psasir.upm.edu.my/id/eprint/111185/1/Performance%20of%20DOA%20Estimation%20Algorithms%20for%20Acoustic%20Localization%20of%20Indoor%20Flying%20Drones%20Using%20Art.pdf |