MWIR–Visible Dual-Channel Airborne Imaging integration for High-Resolution Urban Mapping

Abstract. High-resolution airborne remote sensing increasingly requires the coordinated acquisition of geometric and thermal information for applications such as urban infrastructure inspection, environmental monitoring, and emergency response. However, conventional airborne systems typically operate optical and thermal sensors as loosely coupled subsystems, leading to temporal misalignment, unstable geometric relationships, and limited consistency in fused products.

This paper presents EagleFrame IR-VM28K, a tightly coupled airborne MWIR–visible–GNSS/IMU integrated system designed for high-resolution thermal–optical observation. The system integrates a cooled mid-wave infrared (MWIR) imaging subsystem, a high-resolution visible dual-camera subsystem, and an AP+30 GNSS/IMU navigation unit under a unified mechanical structure, electrical control, and timing framework. A resolution-aware imaging strategy based on sweeping acquisition is adopted to enhance the effective thermal representation capability of the MWIR subsystem.

A unified processing workflow is established, including hardware synchronization, trajectory post-processing, installation-parameter calibration using POSPAC CalQC, MWIR radiometric correction, geometric reconstruction, cross-modal co-registration, and fusion. Furthermore, a multi-temporal thermal analysis framework is introduced to characterize thermal inertia and temporal thermal evolution of urban surfaces.

Flight experiments over Wujin District demonstrate that the proposed system achieves strong spatial consistency between visible and MWIR imagery and effectively represents thermal characteristics of roofs, pavements, and water bodies. Comparative analysis shows that tightly coupled integration and calibration significantly improve cross-modal alignment and fusion quality. The results confirm that the proposed system provides a robust solution for high-resolution airborne thermal–optical remote sensing and offers a foundation for thermal anomaly detection and urban thermal process analysis.