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.

Model-based machine learning.

DoA estimation

Hardware impairments

ISAC

Author

Baptiste Chatelier

Mitsubishi Electric R&D Centre Europe

Institut d'Electronique et de Telecommunications de Rennes

INSA 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

Institut d'Electronique et de Telecommunications de Rennes

INSA Rennes

Henk Wymeersch

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Luc Le Magoarou

INSA Rennes

Institut d'Electronique et de Telecommunications de Rennes

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

More information

Created

12/9/2024