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Compressed Sensing-Based Multi-Abnormality Self-Detecting and Faults Location Method for UAV Swarms

Fei XIONG, Hai WANG, Aijing LI, Dongping YU, Guodong WU

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Summary :

The security of Unmanned Aerial Vehicle (UAV) swarms is threatened by the deployment of anti-UAV systems under complicated environments such as battlefield. Specifically, the faults caused by anti-UAV systems exhibit sparse and compressible characteristics. In this paper, in order to improve the survivability of UAV swarms under complicated environments, we propose a novel multi-abnormality self-detecting and faults location method, which is based on compressed sensing (CS) and takes account of the communication characteristics of UAV swarms. The method can locate the faults when UAV swarms are suffering physical damages or signal attacks. Simulations confirm that the proposed method performs well in terms of abnormalities detecting and faults location when the faults quantity is less than 17% of the quantity of UAVs.

Publication
IEICE TRANSACTIONS on Communications Vol.E102-B No.10 pp.1975-1982
Publication Date
2019/10/01
Publicized
2019/04/26
Online ISSN
1745-1345
DOI
10.1587/transcom.2018DRP0033
Type of Manuscript
Special Section PAPER (Special Section on Exploring Drone for Mobile Sensing, Coverage and Communications: Theory and Applications)
Category

Authors

Fei XIONG
  Army Engineering University of PLA
Hai WANG
  Army Engineering University of PLA
Aijing LI
  Army Engineering University of PLA
Dongping YU
  Army Engineering University of PLA
Guodong WU
  Army Engineering University of PLA

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