A Comprehensive Algorithm for Detection, Identification of Naval Surface Forces and Target Allocation of Network-Centric Controlled Weapons
Authors: Voronov E.M., Kuslya A.M., Repkin A.L., Sychev S.I., Khamaev N.V., Timofeev D.A. | Published: 20.12.2020 |
Published in issue: #4(133)/2020 | |
DOI: 10.18698/0236-3933-2020-4-75-98 | |
Category: Informatics, Computer Engineering and Control | Chapter: System Analysis, Control, and Information Processing | |
Keywords: grouping, a group of controlled weapons, naval surface forces, network-centric control, detection, identification, target allocation, multivariate analysis of effectiveness |
The purpose of the study was to examine and solve the problem of detecting and identifying the objects of naval surface forces by a group of controlled weapons within the group using coordinates and the type of such objects. The main target of naval surface forces was determined according to the parameters of the frequency of detection of the objects by the group of controlled weapons and the reliability of identification of the objects of naval surface forces. A matrix for detecting the objects of naval surface forces by the group of controlled weapons has been formed and analyzed. The introduction of restrictions on the tactics of actions of the group of controlled weapons and on the coefficient of convolution of criteria in the task of target allocation makes it possible to ensure almost complete absence of intersections of trajectories of controlled weapons. On the basis of statistical modeling of the configuration of the systems and the corresponding probabilities of detection and identification, the effectiveness of the developed algorithm is shown. An example of a multi-stage calculation of one variant from a statistical series of experiments is given, followed by a preliminary assessment of target allocation by the group of controlled weapons in accordance with the current configurations of the group of weapons and naval surface forces. The multivariate analysis of the efficiency of the algorithm operation on various configurations of the systems showed a high degree of identification of the objects of naval surface forces in comparison with the existing algorithms. A range of values for the probabilities of identifying the types of the objects of naval surface forces by the group of controlled weapons has been identified, which provides an almost unambiguous determination of the main target of naval surface forces
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