V.I. Goncharenko - Dr. Sc. (Eng.), Associate Professor, Director of Military Institute, Moscow Aviation Institute (National Research University). E-mail: vladimirgonch@mail.ru D.S. Kucheryavenko - Ph.D. (Eng.), Senior Research Scientist, Military Academy of Strategic Rocket Forces (Moscow). E-mail:d_kucheryavenko@mail.ru A.M. Galiamov - Leading Engineer, Branch - Institute Aeronavigation State Resezrch Institute of Civil Aviation?. E-mail: galand1987@gmail.com

The task ofexperimental ballistics associated with the definition of the type of maneuver promising aeroballistic aircraft (ABA) on the path and telemetry measurements obtained by observing them, is important. A feature of the proposed approach to the construction type of recognition algorithm performed maneuvers during testing ABA is the application for processing telemetry and path measurements of neural network and wavelet technologies. The results of solving types of maneuvers ABA recognition problem also allow identification of ABA paths on the set of possible paths approach to the point of completion of the flight. The task of determining the type of maneuver can be considered as the problem of identification, it means that identification of the actual motion of the mathematical model, which is the best assessment of the structure and characteristics of the object with a certain structure of the measurement vector, linear or nonlinear vector-dependent phase coordinates. A feature of the mathematical solution of the problem of identification of aircraft flight model is the complexity of the model due to the presence in the composition of the various avionics systems improve stability and control, as well as because of the impact on the rocket uncontrolled disturbances caused by exposure to the atmosphere. Additional difficulties in the task of identification arise from the noise measuring devices. Another characteristic feature of modern ABPA is the fact that it operates in a wide range of speeds, altitudes, and differetn modes of dynamic inertial mass characteristics. The above features significantly complicate the solution of the problem of identification of mathematical models of flight ABA, based on traditional methods such as models based on differential, integral and algebraic equations. As an alternative to these methods is proposed to use a neural network approach and wavelet technology. The use of this approach gas the following advantages: the possibility of an accounting essentially nonlinear modes of movement; much faster movement of the traditional model and is paalicable in real-time, the possibility of filtering measurement information and its recovery in case of loss of information in the prosess of obtaining ABA during flight. In addition, significantly simplifies the process of solving the problem of identification. The developed method includes the following stages: Formation the classes of maneuvers based on wavelet transform list; training artificial neural betwork classes prrformed maneuvers; Analysis of experimental data using wavelet transform for the classification of maneuver; The formation of the classification results. For efficient operation of the neural network performed its preliminary training. Education is applied to the input of the alphabet network classes performed maneuvers that make up the training set.

 

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