N.R. Khalimov¹, S.L. Ivanov², A.V. Fedorov³

1–3  MESC AF «N.E. Zhukovsky and Y.A. Gagarin Air Force Academy» (Voronezh, Russia)

Any radar complex exercising control over the airspace has a limited capacity. When processing information about a large number of air objects, overloads occur in information systems and part of the information is inevitably lost. To solve this problem, you need to group the goals. If you refuse to group, then this can lead to oversaturation of the displayed situation on the monitor and the human operator, according to his physical capabilities, will not be able to cope with its assessment. That is, the more goals, the worse the quality of the tasks being solved. One of the ways to solve this problem is to reduce the number of tracked objects by grouping them. Therefore, grouping is a necessary measure taken to simplify the presentation and assessment of the situation. The currently used algorithms for grouping air objects are based on spatial gating, which have low efficiency in a difficult environment. Therefore, the development of new strobe-free methods of grouping air objects is an urgent task.

Objective – to develop and research a new strobe-free algorithm for grouping air objects in radar complexes for detecting and tracking air targets.

In work a new algorithm for grouping air objects is synthesized, which is based on one of the methods of cluster analysis and an optimal decision rule according to the Neumann-Pearson criterion about the belonging of the considered set of air objects to one group. Some results of simulation modeling of the synthesized algorithm in a complex air environment in comparison with the algorithm based on production rules are presented.

Practical significance – the developed algorithm for grouping air objects is more efficient than both the grouping algorithm in the spatial strobe and the algorithm based on production rules. This is especially noticeable in cases of flight of several groups to air objects on intersecting trajectories. The developed algorithm does not impose great requirements on the computing system of the radar complex and can be implemented in practice without restrictions.

Khalimov N.R., Ivanov S.L., Fedorov A.V. Synthesis of an algorithm for grouping air objects in radar systems. Achievements of modern radioelectronics. 2021. V. 75. № 2. P. 18–28. DOI: 10.18127/j20700784-202102-02.  [in Russian]

1. Kanashchenkov A.I., Merkulov V.I., Samarin O.F. Oblik perspektivnykh bortovykh radiolokatsionnykh sistem. Vozmozhnosti i ogranicheniya. M.: IPRZhR. 2002. [in Russian]
2. Zhambyu M. Ierarkhicheskiy klasternyy analiz i sootvetstviya. Per. s frants. B.G. Mirkina. M.: Finansy i statistika. 1988. [in Russian]
3. Khalimov N.R., Fedeorov A.V. Gruppirovanie vozdushnykh tseley v IUS na osnove divizimnogo algoritma. Tezisy III Vseross. nauch.praktich. konf. «Navigatsiya, navedenie i upravlenie LA». M.: GosNIIAS. 2017. S. 78–80. [in Russian]
4. Fedorov A.V., Khalimov N.R. Algoritmy prinyatiya resheniya prinadlezhnosti vozdushnykh ob"ektov k odnoy gruppe. Vestnik VKO. 2016. № 4 (24). S. 34–40. [in Russian]
5. Bogdanov A.V., Filonov A.A. Primenenie uzkopolosnoy doplerovskoy fil'tratsii v mnogofunktsional'nykh radiolokatsionnykh kompleksakh: monografiya. Tver': VU PVO. 2015. [in Russian]
6. Seydzh E., Mels Dzh. Teoriya otsenivaniya i ee primenenie v svyazi i upravlenii. Per s angl. pod red. prof. B.R. Levina. M.: Svyaz'. 1976. [in Russian]
7. Tikhonov V.I., Kharisov V.N. Statisticheskiy analiz i sintez radiotekhnicheskikh ustroystv i sistem: Ucheb. posobie dlya vuzov. M.: Radio i svyaz'. 1991. [in Russian]
8. Khalimov N.R. Algoritm traektornogo soprovozhdeniya vozdushnykh tseley na osnove rasshirennogo fil'tra Kalmana. Radiotekhnika. 2017. № 9. C. 73–76. [in Russian]
9. Khalimov N.R., Fedorov A.V., Afonin I.E. Metodika otsenki effektivnosti algoritmov gruppirovaniya vozdushnykh ob"ektov. Vestnik VKO. 2020. № 1(25). S. 12–19. [in Russian]