Automatic Phase Calibration for High-resolution mmWave Sensing via Ambient Radio Anchors

TL;DR

AutoCalib is a novel framework that automatically calibrates high-resolution mmWave radars by leveraging ambient radio anchors, significantly improving calibration accuracy and enabling practical high-resolution sensing without artificial references.

Contribution

It introduces AutoCalib, the first method to automatically identify ambient radio anchors for precise calibration of mmWave radars, overcoming limitations of existing calibration techniques.

Findings

AutoCalib reduces phase error by 74% compared to uncalibrated systems.

AutoCalib outperforms existing methods by 83% in calibration accuracy.

AutoCalib achieves 96% of corner reflector calibration performance in real environments.

Abstract

Millimeter-wave (mmWave) radar systems with large array have pushed radar sensing into a new era, thanks to their high angular resolution. However, our long-term experiments indicate that array elements exhibit phase drift over time and require periodic phase calibration to maintain high-resolution, creating an obstacle for practical high-resolution mmWave sensing. Unfortunately, existing calibration methods are inadequate for periodic recalibration, either because they rely on artificial references or fail to provide sufficient precision. To address this challenge, we introduce AutoCalib, the first framework designed to automatically and accurately calibrate high-resolution mmWave radars by identifying Ambient Radio Anchors (ARAs)-naturally existing objects in ambient environments that offer stable phase references. AutoCalib achieves calibration by first generating spatial spectrum templates based on theoretical electromagnetic characteristics. It then employs a pattern-matching and scoring mechanism to accurately detect these anchors and select the optimal one for calibration. Extensive experiments across 11 environments demonstrate that AutoCalib capable of identifying ARAs that existing methods miss due to their focus on strong reflectors. AutoCalib's calibration performance approaches corner reflectors (74% phase error reduction) while outperforming existing methods by 83%. Beyond radar calibration, AutoCalib effectively supports other phase-dependent applications like handheld imaging, delivering 96% of corner reflector calibration performance without artificial references.