.png){kind=icon}
返回
Acoustic Vector Sensor Multi-Source Detection Based on Multimodal Fusion
.png){kind=icon}
OA
AI
DOI：10.3390/s23031301.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The direction of arrival (DOA) and number of sound sources is usually estimated by short-time Fourier transform and the conjugate cross-spectrum. However, the ability of a single AVS to distinguish between multiple sources will decrease as the number of sources increases. To solve this problem, this paper presents a multimodal fusion method based on a single acoustic vector sensor (AVS). First, the output of the AVS is decomposed into multiple modes by intrinsic time-scale decomposition (ITD). The number of sources in each mode decreases after decomposition. Then, the DOAs and source number in each mode are estimated by density peak clustering (DPC). Finally, the density-based spatial clustering of applications with the noise (DBSCAN) algorithm is employed to obtain the final source counting results from the DOAs of all modes. Experiments showed that the multimodal fusion method could significantly improve the ability of a single AVS to distinguish multiple sources when compared to methods without multimodal fusion.
Keyword:
acoustic vector sensor
modal decomposition
density peak clustering
DOA
source counting
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
Mobocertinib (Tak-788): A targeted inhibitor of egfr exon 20 insertion mutants in non–small cell lung cancerMobocertinib (Tak-788): 非小细胞肺癌中EGFR外显子20插入突变体的靶向抑制剂.png)
IF0
PREAI
分享收藏分享收藏An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection SystemSENSORSOAAI
SENSORSIF3.5
OAAI分享收藏分享收藏An Improved DBSCAN Algorithm Based on the Neighbor Similarity and Fast Nearest Neighbor QueryIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容