Deep Learning Based Source Direction Estimation with Magnitude-only Array Measurements

Jingdong Kuang, Wei Liu, Zhengyu Wan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Most DOA estimation techniques require phase information of the received array signals to accurately estimate the direction of arrival (DOA). Nevertheless, in some scenarios, the phase information may not be easily accessible or reliable due to various reasons such as hardware limitations or calibration issues. One way to tackle this challenge is to discard the phase information or only measure the magnitude of the received signals. In this work, a deep-learning (DL) based DOA estimation method is proposed for effective DOA estimation with magnitude-only measurements. To improve the generalization ability and robustness of the proposed solution, an attention mechanism is employed, and to avoid the implicit assumption that the number of signals is known in the training process, labels of the data are converted into the one-hot form. Simulation results show that the proposed solution has superior performance in terms of computational complexity, accuracy, and robustness compared to traditional DOA estimation algorithms.

Original languageEnglish
Title of host publicationISCAS 2024 - IEEE International Symposium on Circuits and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350330991
DOIs
Publication statusPublished - Jul 2024
Event2024 IEEE International Symposium on Circuits and Systems, ISCAS 2024 - Singapore, Singapore
Duration: 19 May 202422 May 2024

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference2024 IEEE International Symposium on Circuits and Systems, ISCAS 2024
Country/TerritorySingapore
CitySingapore
Period19/05/2422/05/24

Keywords

  • attention mechanism
  • deep learning
  • Direction of arrival
  • magnitude measurements
  • sensor arrays

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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