Predicate algebra application for air objects recognition by the radar spectral image

Authors

DOI:

https://doi.org/10.15587/1729-4061.2014.29737

Keywords:

predicate algebra, air objects recognition, spectral image, clutter, human-operator

Abstract

The possibility of predicate algebra application for air objects recognition by the radar spectral image is analyzed in the paper. The author examines the human-operator's decision-making algorithms to analyze the features of clutter and air objects signals spectra. The spectral pattern is described by the predicate on the set of spectral channels, which have exceeded a certain threshold value. Features-predicates, by a combination of which the instantaneous spectrum uniquely correlates with one of the spectrum types, are introduced to identify the spectral types. Air objects recognition is held by solving the developed equations of predicate operations. Based on the obtained equations, functional diagram of the automatic determination of the spectral types is constructed.

As a result it is shown that the application of mathematical tools of predicate algebra allows automatic and real-time performance of all operations on the identification of features and radar recognition of air objects by the spectral image of the received signals.

Author Biographies

Владимир Витальевич Жирнов, Kharkiv National University of Radio Electronics Lenin ave. 14, Kharkov, Ukraine, 61166

PhD, a leading researcher

Scientific Research Centre of integrated electronic systems and technologies 

Светлана Владимировна Солонская, Kharkiv National University Road Str. Petrovsky, 25, Kharkov, Ukraine, 61005

Senior Lecturer

The Natural and Humanity Disciplines Department

References

  1. Russel, S., Norvig, P. (2006). Artificial intelligence. A modern approach. Second Edition. Williams, 1410.
  2. Luger, G. F. (2005). Artificial intelligence: structures and strategies for complex problem-solving. 4 edition. Williams, 864.
  3. Robinson, J. (1965). A machine-oriented logic based on the resolution principle. Journal of the ACM (JACM), 12 (1), 23–41.
  4. Bondarenko, M. F., Shabanov-Kushnarenko, Yu. P. (2007). Teoriya intellekta. Uchebnik. Harkov: izd-vo SMIT, 576.
  5. Bondarenko, M. F., Chikina, V. A. (1998). O metode matematicheskogo opisaniya morfologicheskih otnosheniy i ih shemnoy realizatsii. Problemy bioniki, 48, 3–11.
  6. Bondarenko, M. F., Shabanov-Kushnarenko, Yu. P. (1987).Obabstraktnom opredelenii algebry konechnyih predikatov. Problemy bioniki, 39, 3–12.
  7. Shabanov-Kushnarenko, S. Yu. (1994). Komparatornaya identifikatsiya protsessov mnogomernoy kolichestvennoy otsenki. Hark. tehn. un-t radioelektroniki, 230.
  8. Bondarenko, M. F., Shabanov-Kushnarenko, S. Yu. (1989). O lineynyh predikatah. Problemy bioniki, 43, 3–7.
  9. Bondarenko, M. F. (1983). Issledovanie sistemy aksiom algebry konechnyih predikatov. ASU i pribory avtomatiki, 66, 120–129.
  10. Borodaenko, D. N. (2001). Raspoznavanie obrazov. Raspoznavanie obrazov i iskusstvennyiy intellekt. Available at: http://www.ocrai.narod.ru (Last accessed: 26.12.2007).
  11. Gorelik, A. L., Skripkin, V. A. (2004). Metody raspoznavaniya. Mosow: Vyssh. shk, 261.
  12. Slagle, J. R., Gardiner, O. A., Kyungsook, N. (1990). Knowledge specification on an expert system. IEEE Expert, 5 (4), 29–38. doi: 10.1109/64.58019
  13. Schank, R. (1972). Conceptual Dependency: a Theory of Natural Language Understanding Cognitive. Cognitive Psychology, 3 (4), 552–631. doi: 10.1016/0010-0285(72)90022-9
  14. Manning, C. D., Raghavan, P., Schütze, H. (2008). Introduction to Information Retrieval.CambridgeUniversityPress, 496.
  15. Zhuravlev, Yu. I. (2005).Obalgebraicheskom podhode k resheniyu zadach raspoznavaniya ili klassifikatsii. Problemy kibernetiki. Moscow: Nauka, 33, 5–68.
  16. Solonskaya, S. V. (2004). O vozmozhnosti ispolzovaniya algebry predikatov dlya klassifikatsii vozdushnyh ob'ektov po radiolokatsionnomu spektralnomu izobrazheniyu. Radiotehnika, 139, 73–76.
  17. Zhyrnov, V. V., Solonskaya, S. V. (2005). Intellektualnaya sistema radioloka-tsionnogo obnaruzheniya malozametnyh vozdushnyh ob'ektov. Radioelektronika i informatika: Nauchno-tehnicheskiy zhurnal, 3, 134–138.
  18. Zhyrnov, V. V., Solonskaya, S. V. (2006). Raspoznavanie radiolokatsionnyh otmetok po spektralnomu izobrazheniyu s adaptivnymi vesovymi koeffitsientami. Radioelektronika i informatika: Nauchno-tehnicheskiy zhurnal, 1, 121–124.
  19. Teyz, A., Gribomon, P. (1990). Logicheskiy podhod k iskusstvennomu intellektu: ot klassicheskoy logiki k logicheskomu programmirovaniyu. Moscow: Mir, 432.

Published

2014-12-19

How to Cite

Жирнов, В. В., & Солонская, С. В. (2014). Predicate algebra application for air objects recognition by the radar spectral image. Eastern-European Journal of Enterprise Technologies, 6(3(72), 48–53. https://doi.org/10.15587/1729-4061.2014.29737

Issue

Section

Control processes