Memory-efficient approximate three-dimensional beamforming
Localization of acoustic sources using a sensor array is typically performed by estimating direction-of-arrival (DOA) via beamforming of the signals recorded by all elements. Software-based conventional beamforming (CBF) forces a trade-off between memory usage and direction resolution, since time de...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Acoustical Society of America
2024
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| Online Access: | https://hdl.handle.net/1721.1/154270 |
| _version_ | 1811087721206120448 |
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| author | Rypkema, Nicholas R. Fischell, Erin M. Schmidt, Henrik |
| author_facet | Rypkema, Nicholas R. Fischell, Erin M. Schmidt, Henrik |
| author_sort | Rypkema, Nicholas R. |
| collection | MIT |
| description | Localization of acoustic sources using a sensor array is typically performed by estimating direction-of-arrival (DOA) via beamforming of the signals recorded by all elements. Software-based conventional beamforming (CBF) forces a trade-off between memory usage and direction resolution, since time delays associated with a set of directions over which the beamformer is steered must be pre-computed and stored, limiting the number of look directions to available platform memory. This paper describes a DOA localization method that is memory-efficient for three-dimensional (3D) beamforming applications. Its key lies in reducing 3D look directions [described by azimuth/inclination angles (ϕ, θ) when considering the array as a whole] to a single variable (a conical angle, ζ) by treating the array as a collection of sensor pairs. This insight reduces the set of look directions from two dimensions to one, enabling computational and memory efficiency improvements and thus allowing direction resolution to be increased. This method is described and compared to CBF, with comparisons provided for accuracy, computational speedup, and memory usage. As this method involves the incoherent summation of sensor pair outputs, gain is limited, restricting its use to localization of strong sources—e.g., for real-time acoustic localization on embedded systems, where computation and/or memory are limited. |
| first_indexed | 2024-09-23T13:50:37Z |
| format | Article |
| id | mit-1721.1/154270 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:50:37Z |
| publishDate | 2024 |
| publisher | Acoustical Society of America |
| record_format | dspace |
| spelling | mit-1721.1/1542702024-09-21T04:33:55Z Memory-efficient approximate three-dimensional beamforming Rypkema, Nicholas R. Fischell, Erin M. Schmidt, Henrik Localization of acoustic sources using a sensor array is typically performed by estimating direction-of-arrival (DOA) via beamforming of the signals recorded by all elements. Software-based conventional beamforming (CBF) forces a trade-off between memory usage and direction resolution, since time delays associated with a set of directions over which the beamformer is steered must be pre-computed and stored, limiting the number of look directions to available platform memory. This paper describes a DOA localization method that is memory-efficient for three-dimensional (3D) beamforming applications. Its key lies in reducing 3D look directions [described by azimuth/inclination angles (ϕ, θ) when considering the array as a whole] to a single variable (a conical angle, ζ) by treating the array as a collection of sensor pairs. This insight reduces the set of look directions from two dimensions to one, enabling computational and memory efficiency improvements and thus allowing direction resolution to be increased. This method is described and compared to CBF, with comparisons provided for accuracy, computational speedup, and memory usage. As this method involves the incoherent summation of sensor pair outputs, gain is limited, restricting its use to localization of strong sources—e.g., for real-time acoustic localization on embedded systems, where computation and/or memory are limited. 2024-04-23T18:03:07Z 2024-04-23T18:03:07Z 2020-12-01 2024-04-23T17:56:35Z Article http://purl.org/eprint/type/JournalArticle 0001-4966 1520-8524 https://hdl.handle.net/1721.1/154270 Nicholas R. Rypkema, Erin M. Fischell, Henrik Schmidt; Memory-efficient approximate three-dimensional beamforming. J. Acoust. Soc. Am. 1 December 2020; 148 (6): 3467–3480. en 10.1121/10.0002852 The Journal of the Acoustical Society of America Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Acoustical Society of America Acoustical Society of America |
| spellingShingle | Rypkema, Nicholas R. Fischell, Erin M. Schmidt, Henrik Memory-efficient approximate three-dimensional beamforming |
| title | Memory-efficient approximate three-dimensional beamforming |
| title_full | Memory-efficient approximate three-dimensional beamforming |
| title_fullStr | Memory-efficient approximate three-dimensional beamforming |
| title_full_unstemmed | Memory-efficient approximate three-dimensional beamforming |
| title_short | Memory-efficient approximate three-dimensional beamforming |
| title_sort | memory efficient approximate three dimensional beamforming |
| url | https://hdl.handle.net/1721.1/154270 |
| work_keys_str_mv | AT rypkemanicholasr memoryefficientapproximatethreedimensionalbeamforming AT fischellerinm memoryefficientapproximatethreedimensionalbeamforming AT schmidthenrik memoryefficientapproximatethreedimensionalbeamforming |