Joint Localization and Orientation Estimation in Millimeter-Wave MIMO OFDM Systems via Atomic Norm Minimization

TL;DR

This paper introduces an atomic norm-based method for precise joint localization and orientation estimation in millimeter-wave MIMO-OFDM systems, leveraging a novel virtual channel matrix and theoretical guarantees for accuracy.

Contribution

It proposes a new atomic norm approach with a virtual channel matrix and an algorithm that jointly estimates location and orientation using both LOS and NLOS data, with theoretical performance guarantees.

Findings

Performance nearly reaches the Cramer-Rao lower bound.

Algorithm is robust to model order errors and synchronization issues.

Outperforms previous methods in accuracy and robustness.

Abstract

Herein, an atomic norm based method for accurately estimating the location and orientation of a target from millimeter-wave multi-input-multi-output (MIMO) orthogonal frequency-division multiplexing (OFDM) signals is presented. A novel virtual channel matrix is introduced and an algorithm to extract localization-relevant channel parameters from its atomic norm decomposition is designed. Then, based on the extended invariance principle, a weighted least squares problem is proposed to accurately recover the location and orientation using both line-of-sight and non-line-of-sight channel information. The conditions for the optimality and uniqueness of the estimate and theoretical guarantees for the estimation error are characterized for the noiseless and the noisy scenarios. Theoretical results are confirmed via simulation. Numerical results investigate the robustness of the proposed algorithm to incorrect model order selection or synchronization error, and highlight performance improvements over a prior method. The resultant performance nearly achieves the Cramer-Rao lower bound on the estimation error.