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Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments

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Published in:IEEE Access
Format: Online Article RSS Article
Published: 2026
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spellingShingle Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments
Computer Sciience
General
Computer Sciience
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Sciience
General
Computer Sciience
Computer Sciience
General
Computer Sciience
subject_facet Computer Sciience
General
Computer Sciience
title Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments
title_auth Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments
title_full Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments
title_fullStr Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments
title_full_unstemmed Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments
title_short Deep Learning-Based Drone Heading Estimation Using BiLSTM and Multi-Head Attention: A Comparative Study of Simulation and Real-World Flight Experiments
title_sort deep learning-based drone heading estimation using bilstm and multi-head attention: a comparative study of simulation and real-world flight experiments
topic Computer Sciience
General
Computer Sciience
url http://ieeexplore.ieee.org/document/11541011