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JOURNALS // Problemy Upravleniya // Archive

Probl. Upr., 2022 Issue 1, Pages 54–66 (Mi pu1271)

This article is cited in 3 papers

Control the moving objects and navigation

A conceptual applied geographic information system for modeling search autonomous correlation-extreme navigation systems

A. I. Alchinova, I. N. Gorokhovskyb

a Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia
b Research Center of Topographic and Navigational Support, Central Research Institute No. 27, Moscow, Russia

Abstract: This paper presents a conceptual applied geographic information system (AGIS) for modeling search correlation-extreme navigation systems (CENSs) to control moving objects. As demonstrated below, the development and mass implementation of autonomous navigation systems of this type as the only alternative to satellite navigation systems can currently be based on subject-oriented information technology. The AGIS can be used to assemble models of a wide range of CENSs and models of technologies for adjusting their operation in specified areas with necessary computational experiments. The required software components, storage structure, and interface features are determined by constructing a general mathematical model. While preserving all specifics of the search algorithms of CENSs, this model covers the well-known image combining algorithms and, moreover, includes a synthesis scheme for search algorithms of new-type CENSs using pattern recognition and scene analysis, clustering, neural network training, and cloud data processing. Stress testing is the most important type of computational experiments with CENS models. A mathematical model of stress effects is constructed for a particular case. It describes various operating conditions for CENSs, including fatal deviations from normal operation.

Keywords: applied geographic information system, correlation-extreme navigation system, shooting system, pattern recognition, scene analysis, learning machines, neural network, parallel computing, cloud computing, mathematical modeling, stress testing of the system.

UDC: 629.7.051

Received: 05.10.2021
Revised: 11.11.2021
Accepted: 23.12.2021

DOI: 10.25728/pu.2022.1.4


 English version:
Control Sciences, 2022:1, 43–54


© Steklov Math. Inst. of RAS, 2026