VECTOR: Velocity-Enhanced GRU Neural Network for Real-Time 3D UAV Trajectory Prediction

VECTOR: Velocity-Enhanced GRU Neural Network for Real-Time 3D UAV Trajectory Prediction

This paper addresses the challenge of predicting 3D trajectories for Unmanned Aerial Vehicles (UAVs) in real-time, a critical task for applications like aerial surveillance and defense. Current prediction models primarily leverage only position data, which may not provide the most accurate forecasts...

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Bibliographic Details
Main Authors: Omer Nacar, Mohamed Abdelkader, Lahouari Ghouti, Kahled Gabr, Abdulrahman Al-Batati, Anis Koubaa
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Drones
Subjects:
unmanned aerial vehicles (UAV)
3D trajectory prediction
sequence-based neural networks
gated recurrent units (GRUs)
transformers
short long term memory (LSTM)
Online Access:https://www.mdpi.com/2504-446X/9/1/8
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