A. O. Slavyanskiy - Post-graduate Student, Baltic State Technical University «VOENMECH» named D.F. Ustinov, St. Petersburg. E-mail: slavynskiy@raki.aero
E. V. Volkov - Post-graduate Student, Planes design department, Moscow Aviation Institute (National Research University)
M. A. Ruzakov - Ph.D.(Econ.), Head of HIO-5, Moscow Aviation Institute (National Research University). E-mail: ruzakovm@mail.ru
O. S. Dolgov - Dr.Sc. (Eng.), Professor, Vice-Head of School №1 «Aviation technique», Moscow Aviation Institute (National Research University). E-mail: ruzakovm@mail.ru
O. V. Koledaev - Research Scientist, Siberian Siberian State Aerospace University, Krasnoyarsk

Different aspects of aviation experts considered the system of collective salvation (SCS) world for more than a decade. However, almost acceptable approaches to the creation of such a system is still not developed fully due to the complexity of solving the problems and reliability issues purely technical. One of the most important aspects of the implementation of SCS is the organization of the descent control automatically according to the information from the various sensors as well as from external sources, the orientation and positioning of the SCS. Most modern aircraft systems are the basis of the basic inertial navigation system (INS), which are composed of linear acceleration sensors (accelerometers) and angular rate (gyro or a pair of accelerometers, which measure the centrifugal force). With their help, the deviation associated with the housing unit of the coordinate system of the coordinate system fixed to the Earth, having orientation angles: yaw (rate), pitch and roll. Linear deviation coordinates as latitude, longitude and altitude is determined by integrating accelerometers. Developed a test program of processing video data in a specified environment, the analysis of the possibility of using methods developed for use in detection, video identification, determination of the geometric characteristics of the observed objects, information on the relative positions of each of the observed objects other. The possibility and effectiveness of existing methods of machine vision in the task navigation SCS.

 

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