TY - GEN
T1 - Detection of LSSUAV using hash fingerprint based SVDD
AU - Shi, Zhiyuan
AU - Huang, Minmin
AU - Zhao, Caidan
AU - Huang, Lianfen
AU - Du, Xiaojiang
AU - Zhao, Yifeng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/28
Y1 - 2017/7/28
N2 - With the rapid development of science and technology, unmanned aerial vehicles (UAVs) gradually become the worldwide focus of science and technology. Not only the development and application but also the security of UAV is of great significance to modern society. Different from methods using radar, optical or acoustic sensors to detect UAV, this paper proposes a novel distance-based support vector data description (SVDD) algorithm using hash fingerprint as feature. This algorithm does not need large number of training samples and its computation complexity is low. Hash fingerprint is generated by extracting features of signal preamble waveforms. Distance-based SVDD algorithm is employed to efficiently detect and recognize low, slow, small unmanned aerial vehicles (LSSUAVs) using 2.4GHz frequency band.
AB - With the rapid development of science and technology, unmanned aerial vehicles (UAVs) gradually become the worldwide focus of science and technology. Not only the development and application but also the security of UAV is of great significance to modern society. Different from methods using radar, optical or acoustic sensors to detect UAV, this paper proposes a novel distance-based support vector data description (SVDD) algorithm using hash fingerprint as feature. This algorithm does not need large number of training samples and its computation complexity is low. Hash fingerprint is generated by extracting features of signal preamble waveforms. Distance-based SVDD algorithm is employed to efficiently detect and recognize low, slow, small unmanned aerial vehicles (LSSUAVs) using 2.4GHz frequency band.
KW - SVDD recognition
KW - UAV detection
KW - hash fingerprint
UR - http://www.scopus.com/inward/record.url?scp=85028339411&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028339411&partnerID=8YFLogxK
U2 - 10.1109/ICC.2017.7996844
DO - 10.1109/ICC.2017.7996844
M3 - Conference contribution
AN - SCOPUS:85028339411
T3 - IEEE International Conference on Communications
BT - 2017 IEEE International Conference on Communications, ICC 2017
A2 - Debbah, Merouane
A2 - Gesbert, David
A2 - Mellouk, Abdelhamid
T2 - 2017 IEEE International Conference on Communications, ICC 2017
Y2 - 21 May 2017 through 25 May 2017
ER -