Multi-camera networks for motion parameter estimation of an aircraft

A multi-camera network is proposed to estimate an aircraft's motion parameters relative to the reference platform in large outdoor fields. Multiple cameras are arranged to cover the aircraft's large-scale motion spaces by field stitching. A camera calibration method using dynamic control points created by a multirotor unmanned aerial vehicle is presented under the conditions that the field of view of the cameras is void. The relative deformation of the camera network caused by external environmental factors is measured and compensated using a combination of cameras and laser rangefinders. A series of field experiments have been carried out using a fixed-wing aircraft without artificial makers, and its accuracy is evaluated using an onboard Differential Global Positioning System. The experimental results show that the multi-camera network is precise, robust, and highly dynamic and can improve the aircraft's landing accuracy.