What question did this study set out to answer?

The aim is to develop a method for detecting low, slow, small unmanned aerial vehicles using hash fingerprints.

May 1, 2017

Detection of LSSUAV using hash fingerprint based SVDD

ZSZhiyuan ShiDalian University of Technology MHMinmin HuangXiamen University CZCaidan ZhaoXiamen University

Key Points

The aim is to develop a method for detecting low, slow, small unmanned aerial vehicles using hash fingerprints.
Proposed a distance-based support vector data description (SVDD) algorithm.
Utilized hash fingerprints generated from signal preamble waveforms.
Employed the algorithm in the 2.4GHz frequency band for detection.
Achieved efficient detection with low computational complexity.
Eliminated the need for a large number of training samples.

Abstract

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.

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