MASSLOC: A Massive Sound Source Localization System based on Direction-of-Arrival Estimation
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866913993755459584 |
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| author | Fischer, Georg K. J. Schaechtle, Thomas Schabinger, Moritz Richter, Alexander Häring, Ivo Höflinger, Fabian Rupitsch, Stefan J. |
| author_facet | Fischer, Georg K. J. Schaechtle, Thomas Schabinger, Moritz Richter, Alexander Häring, Ivo Höflinger, Fabian Rupitsch, Stefan J. |
| contents | Acoustic indoor localization offers the potential for highly accurate position estimation while generally exhibiting low hardware requirements compared to Radio Frequency (RF)-based solutions. Furthermore, angular-based localization significantly reduces installation effort by minimizing the number of required fixed anchor nodes. In this contribution, we propose the so-called MASSLOC system, which leverages sparse two-dimensional array geometries to localize and identify a large number of concurrently active sources. Additionally, the use of complementary Zadoff-Chu sequences is introduced to enable efficient, beamforming-based source identification. These sequences provide a trade-off between favorable correlation properties and accurate, unsynchronized direction-of-arrival estimation by exhibiting a spectrally balanced waveform. The system is evaluated in both a controlled anechoic chamber and a highly reverberant lobby environment with a reverberation time of 1.6 s. In a laboratory setting, successful direction-of-arrival estimation and identification of up to 14 simultaneously emitting sources are demonstrated. Adopting a Perspective-n-Point (PnP) calibration approach, the system achieves a median three-dimensional localization error of 55.7 mm and a median angular error of 0.84 deg with dynamic source movement of up to 1.9 mps in the challenging reverberant environment. The multi-source capability is also demonstrated and evaluated in that environment with a total of three tags. These results indicate the scalability and robustness of the MASSLOC system, even under challenging acoustic conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_12024 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MASSLOC: A Massive Sound Source Localization System based on Direction-of-Arrival Estimation Fischer, Georg K. J. Schaechtle, Thomas Schabinger, Moritz Richter, Alexander Häring, Ivo Höflinger, Fabian Rupitsch, Stefan J. Audio and Speech Processing Signal Processing Acoustic indoor localization offers the potential for highly accurate position estimation while generally exhibiting low hardware requirements compared to Radio Frequency (RF)-based solutions. Furthermore, angular-based localization significantly reduces installation effort by minimizing the number of required fixed anchor nodes. In this contribution, we propose the so-called MASSLOC system, which leverages sparse two-dimensional array geometries to localize and identify a large number of concurrently active sources. Additionally, the use of complementary Zadoff-Chu sequences is introduced to enable efficient, beamforming-based source identification. These sequences provide a trade-off between favorable correlation properties and accurate, unsynchronized direction-of-arrival estimation by exhibiting a spectrally balanced waveform. The system is evaluated in both a controlled anechoic chamber and a highly reverberant lobby environment with a reverberation time of 1.6 s. In a laboratory setting, successful direction-of-arrival estimation and identification of up to 14 simultaneously emitting sources are demonstrated. Adopting a Perspective-n-Point (PnP) calibration approach, the system achieves a median three-dimensional localization error of 55.7 mm and a median angular error of 0.84 deg with dynamic source movement of up to 1.9 mps in the challenging reverberant environment. The multi-source capability is also demonstrated and evaluated in that environment with a total of three tags. These results indicate the scalability and robustness of the MASSLOC system, even under challenging acoustic conditions. |
| title | MASSLOC: A Massive Sound Source Localization System based on Direction-of-Arrival Estimation |
| topic | Audio and Speech Processing Signal Processing |
| url | https://arxiv.org/abs/2508.12024 |