Matematicheskoe modelirovanie
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Impact factor

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Matem. Mod.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Matematicheskoe modelirovanie, 2022, Volume 34, Number 9, Pages 83–106
DOI: https://doi.org/10.20948/mm-2022-09-06
(Mi mm4406)
 

Object recognition method based on their signal-geometric signs by means of a robotic security complex

Yu. A. Pushkarev, V. V. Sviridov

Branch of the Military Academy of the Peter the Great Strategic Missile Forces, Serpukhov
References:
Abstract: The article considers a methodological approach to the recognition of intrusion objects into a protected area using optoelectronic means of a robotic complex, which is based on the existence of a certain feature space (a set of signal and geometric features) for each class and type of object. The solved problem of comparing Bayesian a posteriori probabilities of classes (types) of objects is reduced to calculating a priori probabilities and energy distribution functions of signals and geometric parameters of objects, i.e. likelihood functions of a feature to a specific class (type) of an object. On the basis of the obtained parameters, the dependences of the probability of correct recognition, the probability of skipping, false recognition and confusion of objects on the coefficient of distinctness when the object signal energy deviates from the standard in smaller and larger directions are analyzed. The results obtained are necessary to solve the problem of adaptive group control of robotic complexes when solving operational and tactical tasks in an uncertain dynamic environment.
Keywords: robotic complex, adaptive group control, probability of correct recognition, probability of omission, feature space, a posteriori probability, likelihood function, object.
Received: 01.03.2022
Revised: 01.03.2022
Accepted: 16.05.2022
English version:
Mathematical Models and Computer Simulations, 2023, Volume 15, Issue 2, Pages 297–311
DOI: https://doi.org/10.1134/S207004822302014X
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: Yu. A. Pushkarev, V. V. Sviridov, “Object recognition method based on their signal-geometric signs by means of a robotic security complex”, Matem. Mod., 34:9 (2022), 83–106; Math. Models Comput. Simul., 15:2 (2023), 297–311
Citation in format AMSBIB
\Bibitem{PusSvi22}
\by Yu.~A.~Pushkarev, V.~V.~Sviridov
\paper Object recognition method based on their signal-geometric signs by means of a robotic security complex
\jour Matem. Mod.
\yr 2022
\vol 34
\issue 9
\pages 83--106
\mathnet{http://mi.mathnet.ru/mm4406}
\crossref{https://doi.org/10.20948/mm-2022-09-06}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=4403412}
\transl
\jour Math. Models Comput. Simul.
\yr 2023
\vol 15
\issue 2
\pages 297--311
\crossref{https://doi.org/10.1134/S207004822302014X}
Linking options:
  • https://www.mathnet.ru/eng/mm4406
  • https://www.mathnet.ru/eng/mm/v34/i9/p83
  • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Математическое моделирование
    Statistics & downloads:
    Abstract page:135
    Full-text PDF :26
    References:31
    First page:6
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024