Observation of aircraft ground performance with multicamera video monitoring system

One of emerging issues in general aviation development is providing safety of small airplanes operation on local and remote airfields with the absence of the control tower by implement the automated system for monitoring the small aircraft ground performance. Method used in IMUMETER system is based on measurements of aircraft accelerations, magnetic field vector, as well as Global Positioning System (GPS) position. The convolution neural network was developed to recognizes characteristic moments of flight during takeoff and liftoff. The multi-camera system was prepared to collect data necessary to train a neural network. The system consist of a set of two CCD cameras equipped with an appropriate camera links, software and the computers for concurrent observation of the aircrafts. A method of camera calibration was developed to maintain measurement traceability using a laser tracker. System was tested in laboratory conditions. The system will use image recognition techniques of plains.