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Aircraft Trajectory Tracking Using Radar Equipment with Fuzzy Logic Algorithm

Author

Listed:
  • Maria Simona Raboaca

    (National R&D Institute for Cryogenic and Isotopic Technologies, 240050 Râmnicu Vâlcea, Romania
    Faculty of Electrical Engineering and Computer Science, “Stefan cel Mare” University of Suceava, 720229 Suceava, Romania
    Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania)

  • Catalin Dumitrescu

    (“Polytechnic” University of Bucharest, 060042 Bucharest, Romania)

  • Ioana Manta

    (National R&D Institute for Cryogenic and Isotopic Technologies, 240050 Râmnicu Vâlcea, Romania
    “Polytechnic” University of Bucharest, 060042 Bucharest, Romania)

Abstract

Radio-electronic means, including equipment for transmissions, radio-location, broadcasting, and navigation, allow the execution of various research missions and combat forces management. Determining the target coordinates and directing the armament towards them, obtaining and processing data about enemies, ensuring the navigation of ships, planes and outer atmospheric means, transmitting orders, decisions, reports and other necessary information for the armed forces; these are only some of the possibilities of radio-electronic technology. Fuzzy logic allows the linguistic description of the laws of command, operation and control of a system. When working with complex and nonlinear systems, it can often be observed that, as their complexity increases, there is a decrease in the significance of the details in describing the global behavior of the system. Even though such an approach may seem inadequate, it is often superior and less laborious than a rigorous mathematical approach. The main argument in favor of fuzzy set theory is to excel in operating with imprecise, vague notions. This article demonstrates the superiority of a fuzzy tracking system over the standard Kalman filter tracking system under the conditions of uneven accelerations and sudden change of direction of the targets, as well as in the case of failure to observe the target during successive scans. A cascading Kalman filtering algorithm was used to solve the speed ambiguity and to reduce the measurement error in real-time radar processing. The cascade filters are extended Kalman filters with controlled gain using fuzzy logic for tracking targets using radar equipment under difficult tracking conditions.

Suggested Citation

  • Maria Simona Raboaca & Catalin Dumitrescu & Ioana Manta, 2020. "Aircraft Trajectory Tracking Using Radar Equipment with Fuzzy Logic Algorithm," Mathematics, MDPI, vol. 8(2), pages 1-20, February.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:2:p:207-:d:317298
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    Citations

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    Cited by:

    1. Li, Huanhuan & Jiao, Hang & Yang, Zaili, 2023. "AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    2. Piyush Dhawankar & Prashant Agrawal & Bilal Abderezzak & Omprakash Kaiwartya & Krishna Busawon & Maria Simona Raboacă, 2021. "Design and Numerical Implementation of V2X Control Architecture for Autonomous Driving Vehicles," Mathematics, MDPI, vol. 9(14), pages 1-24, July.

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