Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor
This paper considers the problem of tracking multiple acoustic sources using a single acoustic vector sensor (AVS). Firstly, a particle filtering (PF) approach is developed to track the direction of arrivals of fixed and known number of sources. Secondly, a more realistic tracking scenario which ass...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/99511 http://hdl.handle.net/10220/13513 |
| _version_ | 1811678839124787200 |
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| author | Premkumar, A. B. Zhong, Xionghu |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Premkumar, A. B. Zhong, Xionghu |
| author_sort | Premkumar, A. B. |
| collection | NTU |
| description | This paper considers the problem of tracking multiple acoustic sources using a single acoustic vector sensor (AVS). Firstly, a particle filtering (PF) approach is developed to track the direction of arrivals of fixed and known number of sources. Secondly, a more realistic tracking scenario which assumes that the number of acoustic sources is unknown and time-varying is considered. A random finite set (RFS) framework is employed to characterize the randomness of the state process, i.e., the dynamics of source motion and the number of active sources, as well as the measurement process. As deriving a closed-form solution for the multi-source probability density is difficult, a particle filtering approach is employed to arrive at a computationally tractable approximation of the RFS densities. The proposed RFS-PF algorithm is able to simultaneously detect and track multiple sources. Simulations under different tracking scenarios demonstrate the ability of the proposed approaches in tracking multiple acoustic sources. |
| first_indexed | 2024-10-01T02:59:38Z |
| format | Journal Article |
| id | ntu-10356/99511 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:59:38Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/995112020-05-28T07:18:28Z Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor Premkumar, A. B. Zhong, Xionghu School of Computer Engineering DRNTU::Engineering::Computer science and engineering This paper considers the problem of tracking multiple acoustic sources using a single acoustic vector sensor (AVS). Firstly, a particle filtering (PF) approach is developed to track the direction of arrivals of fixed and known number of sources. Secondly, a more realistic tracking scenario which assumes that the number of acoustic sources is unknown and time-varying is considered. A random finite set (RFS) framework is employed to characterize the randomness of the state process, i.e., the dynamics of source motion and the number of active sources, as well as the measurement process. As deriving a closed-form solution for the multi-source probability density is difficult, a particle filtering approach is employed to arrive at a computationally tractable approximation of the RFS densities. The proposed RFS-PF algorithm is able to simultaneously detect and track multiple sources. Simulations under different tracking scenarios demonstrate the ability of the proposed approaches in tracking multiple acoustic sources. 2013-09-18T01:32:09Z 2019-12-06T20:08:14Z 2013-09-18T01:32:09Z 2019-12-06T20:08:14Z 2012 2012 Journal Article Zhong, X., & Premkumar, A. B. (2012). Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor. IEEE transactions on signal processing, 60(9), 4719-4733. 1053-587X https://hdl.handle.net/10356/99511 http://hdl.handle.net/10220/13513 10.1109/TSP.2012.2199987 en IEEE transactions on signal processing © 2012 IEEE |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Premkumar, A. B. Zhong, Xionghu Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor |
| title | Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor |
| title_full | Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor |
| title_fullStr | Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor |
| title_full_unstemmed | Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor |
| title_short | Particle filtering approaches for multiple acoustic source detection and 2-D direction of arrival estimation using a single acoustic vector sensor |
| title_sort | particle filtering approaches for multiple acoustic source detection and 2 d direction of arrival estimation using a single acoustic vector sensor |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/99511 http://hdl.handle.net/10220/13513 |
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