Domain-Adaptive Direction of Arrival (DOA) Estimation in Complex Indoor Environments Based on Convolutional Autoencoder and Transfer Learning

Direction of arrival (DOA) estimation for signal sources in indoor environments has become increasingly important in wireless communications and smart home applications. However, complex indoor conditions, such as multipath effects and noise interference, pose significant challenges to estimation ac...

Full description

Saved in:

Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 25; no. 10; p. 2959
Main Authors:	Shen, Lingyu, Li, Jianfeng, Pan, Jingjing, Shi, Junpeng, Xu, Rui, Wang, Hao, Deng, Weiming
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 08.05.2025 MDPI
Subjects:	Adaptation Algorithms Datasets Deep Learning Design DOA domain adaptation indoor scenes Location-based systems Machine learning Methods Mobile communication systems Neural networks Signal processing Support vector machines Wireless communication systems China domain adaptation Deep Learning indoor scenes DOA
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!