Journal
CHINESE JOURNAL OF ELECTRONICS
Volume 31, Issue 3, Pages 442-455Publisher
WILEY
DOI: 10.1049/cje.2021.00.310
Keywords
Unmanned aerial vehicle; Reinforcement learning; Remoate localization; Wireless communications
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Funding
- National Key Scientific Instrument and Equipment Development Project [61827801]
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This paper proposes a multi-UAV-based cooperative framework for interference source localization, which iteratively performs searching and remote localization to balance the accuracy and efficiency of localization.
Interference source localization with high accuracy and time efficiency is of crucial importance for protecting spectrum resources. Due to the flexibility of unmanned aerial vehicles (UAVs), exploiting UAVs to locate the interference source has attracted intensive research interests. The off-the-shelf UAV-based interference source localization schemes locate the interference sources by employing the UAV to keep searching until it arrives at the target. This obviously degrades time efficiency of localization. To balance the accuracy and the efficiency of searching and localization, this paper proposes a multi-UAV-based cooperative framework alone with its detailed scheme, where search and remote localization are iteratively performed with a swarm of UAVs. For searching, a low-complexity Q-learning algorithm is proposed to decide the direction of flight in every time interval for each UAV. In the following remote localization phase, a fast Fourier transformation based location prediction algorithm is proposed to estimate the location of the interference source by fusing the searching result of different UAVs in different time intervals. Numerical results reveal that in the proposed scheme outperforms the state-of-the-art schemes, in terms of the accuracy, the robustness and time efficiency of localization.
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