Decoupling Spatio-Temporal Dynamics: Microvibration Imaging Using Coherent Detection Ghost Imaging Lidar

TL;DR

This paper introduces a novel coherent detection ghost imaging lidar system that captures high-resolution, full-field microvibration patterns of targets, overcoming limitations of traditional sensors and enabling precise, non-invasive structural health monitoring.

Contribution

It develops a new CD-GI framework combining spatial multiplexing and coherent detection, with a mathematical model and self-calibration scheme to decouple micro-Doppler signatures from speckle patterns.

Findings

Successfully reconstructs microvibration patterns with 1 Hz frequency difference

Achieves sub-wavelength vibration sensitivity

Demonstrates robustness in non-invasive structural health monitoring

Abstract

Imaging the full-field microvibration of extended targets remains a formidable challenge for conventional remote sensing. Traditional array-based sensors are often severely constrained by data throughput and sensitivity limits when scaling to high spatial resolutions, while point-scanning interferometric systems lack the instantaneous full-field capability required to capture transient, spatially coupled vibration modes. To overcome these limitations, we propose a Coherent Detection-Ghost Imaging (CD-GI) framework that synergizes the spatial multiplexing capability of single-pixel imaging with the high-dimensional sensitivity of coherent detection. We establish a comprehensive mathematical model that describes the coupling mechanism of the target's spatial distribution and temporal micro-dynamics within a 1D bucket detector signal. To resolve the resulting inverse problem, we develop a frequency-channel self-calibration scheme. This approach effectively decouples the micro-Doppler signatures from spatial speckle patterns without requiring prior knowledge of the vibration frequency. Experimental results demonstrate that our system successfully reconstructs the spatially resolved microvibration patterns of adjacent targets with a frequency difference as small as 1 Hz, achieving sub-wavelength vibration sensitivity. This work bridges the gap between computational imaging and coherent metrology, offering a robust solution for non-invasive, high-precision structural health monitoring.