Autonomous Model-Based Object Identification & Camera Position Estimation with Application to Airport Lighting Quality Control

The development of an autonomous system for the accurate measurement of the quality of aerodrome ground lighting (AGL) in accordance with current standards and recommendations is presented. The system is composed of an imager which is placed inside the cockpit of an aircraft to record images of the AGL during a normal descent to an aerodrome. Before the performance of the AGL is assessed, it is first necessary to uniquely identify each luminaire within the image and track it through the complete image sequence. A model-based (MB) methodology is used to ascertain the optimum match between a template of the AGL and the actual image data. Projective geometry, in addition to the image and real world location of the extracted luminaires, is then used to calculate the position of the camera at the instant the image was acquired. Algorithms are also presented which model the distortion apparent within the sensors optical system and average the camera’s intrinsic parameters over multiple frames, so as to minimise the effects of noise on the acquired image data and hence make the camera’s estimated position and orientation more accurate. The positional information is validated using actual approach image data.