To improve the quality and efficiency of Digital Elevation Model (DEM) construction in complex terrain, this study proposes a multi⁃source DEM acquisition and fusion method that integrates high⁃resolution optical imagery and interferometric Synthetic Aperture Radar (SAR) imagery. Using an unmanned aerial vehicle and satellite remote sensing system as a platform, this method constructs a multi⁃view data acquisition chain to generate optical imagery DEM and interferometric imagery SAR⁃DEM, respectively. By introducing a point cloud classification algorithm based on texture and structural features and a regional adaptive weight estimation model, weighted fusion of multi⁃source elevation data has been achieved. The fusion process employs error constraints and seamline control strategies to address typical challenges such as terrain occlusion, data holes, and elevation jumps. Experiments in representative landforms, including forests, glaciers, deserts, cities, and water bodies, demonstrates that this method has the characteristics of high elevation restoration accuracy and good boundary continuity, and can meet the three dimensions modeling needs of various landform types. Among them, the relative elevation mean error in hilly areas is 0.5 m. The research findings provide stable and reliable technical support for fields such as high⁃resolution topographic mapping, landform evolution monitoring, and disaster early warning, and are of great significance for promoting the automation and intelligence of remote sensing mapping.

Accurate heat flux measurement is essential for developing hypersonic vehicles and their thermal protection systems. The intense aerodynamic heating generated during high⁃speed flight of aerospace vehicles is primarily dominated by convective heat transfer. However, existing heat flux gauges struggle to accurately measure surface thermal loads under extreme high-temperature and high⁃speed conditions, resulting in low measurement accuracy and significantly constraining the performance evaluation of thermal protection systems and material development. To address the lack of reliable calibration methods for heat flux sensors under high⁃temperature and high⁃speed conditions, this study introduces a dual⁃plate transient calibration method. This method adopts a highly accurate thin⁃film platinum resistance sensor as a reference, installs a Gardon gauge to be calibrated with the sensor together on a displacement ejection mechanism, and simulates the high⁃speed flight scenario of the aircraft in the wind tunnel to achieve the calibration to the Gardon heat flux gauge under airflow conditions. Calibration experiments were conducted at a flight Mach number of 0.3 and temperatures from 100 °C to 300 °C for the developed convective heat flux measurement device. The results demonstrate that the relative expanded uncertainty is 4.2% (k = 2), and this method can effectively obtain the convective heat flux sensitivity coefficient of the Gardon heat flux meter. The dual plate transient calibration method proposed in this paper provides new ideas and approaches for high⁃temperature and high⁃speed convective heat flux calibration, significantly improving the reliability of convective heat flux measurement data and providing strong technical support for the development of hypersonic aircraft and accurate measurement of thermal loads in thermal protection systems.

To address the issues of accuracy degradation and computational delay in extracting small spot centers in the field of industrial high⁃speed visual measurement, a high⁃speed real⁃time spot localization method for small⁃sized spots is proposed. A Region of Interest (ROI) extraction algorithm based on sliding window brightness consistency is designed and implemented in a Field Programmable Gate Array (FPGA) to improve detection speed. A small spot center extraction algorithm combining distance⁃weighted least⁃square fitting and a Signal⁃to⁃Noise Ratio (SNR)⁃based adaptive weight adjustment mechanism is introduced to enhance the localization robustness of small spots under varying lighting and noise conditions. Experimental results show that the proposed method has achieved a spot center localization error of not more than 0.05 pixels, with a frame rate of 160 frames per second, significantly outperforming traditional methods in processing speed. This method to a great extent meets the high⁃precision real⁃time localization requirements of small spot centers in industrial high⁃speed visual measurement.