Description: The useful information which enters from radar stations of all group of air defense of ground forces needs to be processed on control center. Decision-making by the commander of the corresponding control link demands time for processing of this information and carrying out optimum operations. The flow of the entering information very big, at the same time information can come to a control loop as it is serial, and in parallel. Therefore automation of processing and distribution of information in a control loop of an air defense system of ground forces is necessary. The purpose of article is development of an advanced method of the automated information processing of the bound to quality of information and an exception of mistakes in processing, excess and improbable information on control center of air defense of ground forces at simultaneous receipts parallel and serial flows of information for increase in overall performance of all control loop. In article improvement of an algorithm of the automated information processing is carried out having excluded excess time for processing of false information which treated on control center necessary earlier. Thus the offered mathematical model approach on improvement of a method of the automated information processing can be used and introduced on control centers by means of air defense of different level of hierarchy of new generation. Such method will allow to increase efficiency of work of structure of channels of the automated control system on simultaneous information processing which will enter on control centers, both in parallel, and is serial. Use of the advanced automated information processing will allow to reduce time for information processing and for decision-making by the commander of the corresponding link on distribution of the purposes between divisions of air defense of ground forces. It will lead to increase in effectiveness of all control loop
Keywords: automated information processing, control point, distribution of air targets, control loop, matrix theory, mass service theory
1. Filatov, N.V. (1990), “Avtomatizirovanniye sistemy upravleniya voysk PVO Sukhoputnykh voysk. Chast 2” [Automated
control systems of troops of air defense of the Ground Forces. Part 2], MA ADF, Kyiv, 308 p.
2. Horodnov, V.P., Drobakha, H.A. and Yermoshyn, M.O. (2004), “Modeliuvannia y otsinka efektyvnosti boiovykh dii viisk
(syl) protypovitrianoi oborony: teoriia, praktyka, istoriia rozvytku: monohrafiia” [Modeling and evaluation of the effectiveness of
combat operations of forces (forces) of air defense: theory, practice, history of development: monograph], KhMU, Kharkiv, 410 p.
3. Yarosh, S.P., Yermoshyn, M.O. and Drobakha, H.A. (2014), “Modelyuvannya boyovykh diy zenitnoho raketnoho
pidrozdilu” [Modeling of combat operations of the anti-aircraft missile unit], KNAUF, Kharkіv, 380 p.
4. Kovalenko, S.P., Tsvihun, V.M., Konyeva, I.V. and Leushyn, S.H. (2004), “Metod avtomatyzovanoi obrobky informatsii
na PU PPO mekhanizovanoi (tankovoi) bryhady pry paralelnykh ta poslidovnykh potokakh informatsii” [The method of automated
information processing on the PU of an air defense mechanized (tank) brigade with parallel and successive streams of
information], Information Processing Systems, No. 7(35), pp. 71-76.
5. Kovalenko, S.P., Kolomiytsev, O.V., Obryadin, V.V. and Khudarkovskyi, K.I. (2007), “Metod efektyvnoho rozpodilu
tsilei pry upravlinni vohnem pidrozdilu” [Method of effective distribution of goals in fire control unit], Information Processing
Systems, No. 3(16), pp. 41-43.
6. Kovalenko, S.P., Kolomiytsev, O.V. and Levahin, H.A. (2010), “Efektyvnyi rozpodil tsilei mizh pidrozdilamy PPO SV –
pokaznyk vidvernenoho zbytku viiskam” [Effective distribution of goals between the units of Air Defense Ground Forces – an
indicator of the deflected damage to troops], Systems of Arms and Military Equipment, No. 2(22), pp. 211-215.
7. Kutsenko, V.V., Kovalenko, S.Р. and Dobrowolski, D.D. (2017), Parameters numerical values of errors distribution law
in coordinate measuring process at the difference-distancemeasuring passive location method, Science and Technology of the Air
Force of Ukraine, No. 1(26), 82-84. https://doi.org/10.30748/nitps.2017.26.17
8. Dave, B., Boddy, S.C. and Koskela, L.J. (2010), Improving information flow within the production management system
with web services, Proceedings of the 18th Annual Conference of the International Group for Lean Construction, National Building
Research Institute, Technion-Israel Institute of Technology, pp. 445-455.
9. Cheng, T., Teizer, J., Migliaccio, G.C. and Gatti, U.C. (2013), Automated task-level activity analysis through fusion of
real time location sensors and worker's thoracic posture data, Automation in Construction, No. 29, pp. 24-39.
10. Kubler, S., Madhikermi, M., Buda, A. and Främling, K. (2014), QLM Messaging Standards: Introduction and Comparison
with Existing Messaging Protocol, Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics,
Springer International Publishing, pp. 237-256.
11. Nguyen, T.A. and Aiello, M. (2013), Energy intelligent buildings based on user activity: A survey, Energy and buildings,
No. 56, pp. 244-257.
12. Bhargav, D., Kubler, S., Främling, K. and Koskela, L. (2014), Addressing information flow in lean production management
and control in construction, Proceedings IGLC, No. 22, pp. 592-581.
13. Kala, T., Mouflard, C. and Seppänen, O. (2012), Production Control Using LocationBased Management System on a
Hospital Construction Project, 20th Annual Conference of the International Group for Lean Construction, San Diego, California,
14. Englehardt, S., Eubank, C., Zimmerman, P., Reisman, D. and Narayanan, A. (2014), Web privacy measurement: Scientific
principles, engineering platform, and new results, available at: www.randomwalker.info/publications/ WebPrivacyMeasurement.
pdf, 2014, (accessed Nov. 22, 2014).