Physically Parameterized Differentiable MUSIC for DoA Estimation with Uncalibrated Arrays
Preprint, 2024
Direction of arrival (DoA) estimation is a common sensing problem in radar, sonar, audio, and wireless communication systems. It has gained renewed importance with the advent of the integrated sensing and communication paradigm. To fully exploit the potential of such sensing systems, it is crucial to take into account potential hardware impairments that can negatively impact the obtained performance. This study introduces a joint DoA estimation and hardware impairment learning scheme following a model-based approach. Specifically, a differentiable version of the multiple signal classification (MUSIC) algorithm is derived, allowing efficient learning of the considered impairments. The proposed approach supports both supervised and unsupervised learning strategies, showcasing its practical potential. Simulation results indicate that the proposed method successfully learns significant inaccuracies in both antenna locations and complex gains. Additionally, the proposed method outperforms the classical MUSIC algorithm in the DoA estimation task.
DoA estimation
Model-based machine learning.
Hardware impairments
ISAC
Author
Baptiste Chatelier
INSA
Mitsubishi Electric R&D Centre Europe
Institut d'Electronique et de Telecommunications de Rennes
José Miguel Mateos Ramos
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Vincent Corlay
Mitsubishi Electric R&D Centre Europe
Christian Häger
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Matthieu Crussière
INSA
Institut d'Electronique et de Telecommunications de Rennes
Henk Wymeersch
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Luc Le Magoarou
Institut d'Electronique et de Telecommunications de Rennes
INSA
Hardware-aware Integrated Localization and Sensing for Communication Systems
Swedish Research Council (VR) (2022-03007), 2023-01-01 -- 2026-12-31.
Areas of Advance
Information and Communication Technology
Subject Categories (SSIF 2011)
Telecommunications
Communication Systems
Signal Processing
DOI
10.48550/arXiv.2411.15144