Adaptive Target Location Method for Cross-in-a-circle Apron Using Monocular High-Speed Camera

The recognition of airport apron targets and the determination of target positions are critically important in positioning the apron when there are abnormal target positions or unmanned aerial vehicles (UAVs) engaged in autonomous cargo retrieval. This is crucial for ensuring the safety and efficiency of the apron. However, challenges such as resource-intensive processes and suboptimal accuracy in position solving have been encountered due to limitations in hardware equipment and the complexity of multi-sensor fusion. In this paper, we propose an adaptive target location method for airport aprons based on monocular high-speed cameras. This method employs adaptive frame differencing and perspective transformation based on geometric shape extraction to detect apron objects and calculate their azimuth and deflection from the apron center. Importantly, our approach relies solely on a single visible-light camera, eliminating the need for complex multi-sensor fusion involving binocular matching, Global Navigation Satellite Systems (GNSS), or Inertial Measurement Units (IMU). Experimental results demonstrate that the proposed method achieves position solving accuracy within 1 meter and real-time recognition and solving capabilities for apron objects.