Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142787
Title: A UAV classification system based on FMCW radar micro-Doppler signature analysis
Authors: Oh, Beom-Seok
Guo, Xin
Lin, Zhiping
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Oh, B.-S., Guo, X., & Lin, Z. (2019). A UAV classification system based on FMCW radar micro-Doppler signature analysis. Expert Systems With Applications, 132, 239-255. doi:10.1016/j.eswa.2019.05.007
Journal: Expert Systems With Applications
Abstract: Due to its small size, slow flying speed, and low flying altitude, classification of mini-sized unmanned aerial vehicles (UAVs) using a frequency-modulated continuous wave (FMCW) surveillance radar is a challenging task. This is because the FMCW radar echo signals are acquired at a short dwell time and thus contain limited information about targets. In this paper, we first analyze FMCW radar returns from various types of UAVs and non-UAV objects in terms of the micro-Doppler signature (m-DS) pattern. Based on the analysis results, we propose an effective and efficient UAV classification system using FMCW radar echo signals. The proposed system consists of five main parts namely, (i) burst selection, (ii) rule-based scan pruning, (iii) the empirical mode decomposition based m-DS analysis and features extraction, (iv) error counting minimization based class label estimation, and (v) scan-to-scan filtering. Our experimental results on physically measured FMCW radar echo signals from several types of UAVs and non-UAV objects show that the proposed system consistently outperforms a commercial-off-the-shelf UAV classification system in terms of the classification accuracy.
URI: https://hdl.handle.net/10356/142787
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2019.05.007
Rights: © 2019 Elsevier Ltd. All rights reserved. This paper was published in Expert Systems With Applications and is made available with permission of Elsevier Ltd.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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