A Novel Statistically-Aided Learning Framework for Precise Localization of UAVs-Reference-Cited by-同舟云学术

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A Novel Statistically-Aided Learning Framework for Precise Localization of UAVs

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
language:
Short-container-title:

Author:

Mandal Akash Kumar¹,Seo Jun-Bae²,De Swades¹,Poddar Ajay K.³,Rohde Ulrich⁴

Affiliation:

1. IIT Delhi,Bharti School of Telecommunication,Department of Electrical Engineering,New Delhi,India

2. Gyeongsang National University,Department of Information and Communication Engineering,South Korea

3. Synergy Microwave Corporation,Paterson,NJ,USA

4. Federal University of the Joint Forces,Faculty of Informatics,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199114/10199145/10200280.pdf?arnumber=10200280

Reference21 articles.

1. A Learning-based Noise Tracking Method of Adaptive Kalman Filter for UAV Positioning

2. RSS-Based Q-Learning for Indoor UAV Navigation

3. Autonomous UAV Trajectory for Localizing Ground Objects: A Reinforcement Learning Approach

4. Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications

5. Multiple-Vehicle Localization Using Maximum Likelihood Kalman Filtering and Ultra-Wideband Signals

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Impact of Wind on UAV Collision Avoidance;ICC 2024 - IEEE International Conference on Communications;2024-06-09

2. Vision-Guided Hierarchical Control and Autonomous Positioning for Aerial Manipulator;Applied Sciences;2023-11-09

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