Atıf İçin Kopyala
Taş A. İ., Iscan M., Gurkan B., Yilmaz C.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, sa.01423312231213677, 2023 (SCI-Expanded)
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Yayın Türü:
Makale / Tam Makale
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Basım Tarihi:
2023
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Doi Numarası:
10.1177/01423312231213677
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Dergi Adı:
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
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Derginin Tarandığı İndeksler:
Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
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Yıldız Teknik Üniversitesi Adresli:
Evet
Özet
The continuous telemetry transmission between unmanned aerial vehicles (UAVs) and ground control stations is important particularly in scenarios lacking global positioning system (GPS) data. This paper proposes an adaptive novel elliptic trajectory formula-based tracking algorithm for received signal strength indicator (ANETF-RSSI) which dynamically optimizes model parameters based on energy-associated RSSI measurement errors. ANETF-RSSI generates a variable two-dimensional (2D) RSSI map to identify optimal paths, even under challenging conditions like circular flight paths, varying operating ranges, and accelerated maneuvering, which causes uncertainty into RSSI measurements during flight. In contrast to previous methods, the proposed approach eliminates the reliance on telemetry data such as GPS or complex multiantenna configurations, ensuring robust UAV communication continuity across routes ranging from 100 m to 100 km, even as the UAV rotates around the antenna. This method offers substantial contributions, including enhanced monitoring precision, simplified hardware configurations, continuous tracking with superior accuracy, and adaptability to diverse range routes without the need for preflight parameter tuning. Performance evaluations demonstrate that the proposed ANETF-RSSI method consistently outperforms existing technique, improving nominal performance by 32.02% in the most challenging operational scenarios and achieving a remarkable 48.76% improvement in minimum RSSI values. Consequently, this research provides a versatile and adaptive tracking solution for unexpected UAV flight trajectories.