Topology Optimization of Planar Microphone Array Based on NSGA-II

The detection equipment based on a microphone array is widely used. At present, there are many redundant array elements in the microphone array, which significantly affects the main lobe width and sidelobe level in the positioning parameters, reduces the detection accuracy and resolution, leads to inaccurate positioning, and increases the cost of the detection equipment. Aiming at the redundant array elements in the microphone array, first, the microphone topology was optimized for main lobe width, sidelobe level, and number of microphones by using the fast nondominated sorting genetic algorithm-II (NSGA-II) to remove the redundant array elements. Then, a 2-D microphone array simulation model was established, and the sound source was located using the beam-forming algorithm. The topology structure before and after optimization is compared and analyzed. To illustrate the superiority of the NSGA-II algorithm, the NSGA-II algorithm and MOPSO algorithm are used to optimize the topology of the rectangular array and concentric circle array, respectively. Finally, the above simulation results are verified by experiments. The results show that, compared with the topology structure of the microphone array before optimization, the sidelobe level and the number of microphones are optimized by more than 46%. The array optimized by the NSGA-II algorithm has better positioning performance and improves the detection accuracy and resolution.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-08-22
DOI
https://doi.org/10.1109/jsen.2024.3439265
Citations
5
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
1.75
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article

Topology Optimization of Planar Microphone Array Based on NSGA-II

Yanling Lv, Kexian Ai
5 citations
IEEE Sensors Journal
Speech and Audio Processing
1.75
article

Topology Optimization of Planar Microphone Array Based on NSGA-II

Yanling Lv, Kexian Ai
article en
5 citations

Abstract

The detection equipment based on a microphone array is widely used. At present, there are many redundant array elements in the microphone array, which significantly affects the main lobe width and sidelobe level in the positioning parameters, reduces the detection accuracy and resolution, leads to inaccurate positioning, and increases the cost of the detection equipment. Aiming at the redundant array elements in the microphone array, first, the microphone topology was optimized for main lobe width, sidelobe level, and number of microphones by using the fast nondominated sorting genetic algorithm-II (NSGA-II) to remove the redundant array elements. Then, a 2-D microphone array simulation model was established, and the sound source was located using the beam-forming algorithm. The topology structure before and after optimization is compared and analyzed. To illustrate the superiority of the NSGA-II algorithm, the NSGA-II algorithm and MOPSO algorithm are used to optimize the topology of the rectangular array and concentric circle array, respectively. Finally, the above simulation results are verified by experiments. The results show that, compared with the topology structure of the microphone array before optimization, the sidelobe level and the number of microphones are optimized by more than 46%. The array optimized by the NSGA-II algorithm has better positioning performance and improves the detection accuracy and resolution.

IEEE Sensors JournalVol. 24(19)
Harbin University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 15%
Speech and Audio Processing
1.75
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Topology Optimization of Planar Microphone Array Based on NSGA-II — Yanling Lv, Kexian Ai · IEEE Sensors Journal (2024) | TGRS Research Map | TGRS