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http://dx.doi.org/10.5573/ieie.2016.53.3.114

Feature Extraction Algorithm for Distant Unmmaned Aerial Vehicle Detection  

Kim, Juho (Department of Ocean System Engineering, Jeju National University)
Lee, Kibae (Department of Ocean System Engineering, Jeju National University)
Bae, Jinho (Department of Ocean System Engineering, Jeju National University)
Lee, Chong Hyun (Department of Ocean System Engineering, Jeju National University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.53, no.3, 2016 , pp. 114-123 More about this Journal
Abstract
The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.
Keywords
harmonic complex tone; unmaned aerial vehicle; sound detetion; ELM(Extreme Learning Machine);
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Times Cited By KSCI : 2  (Citation Analysis)
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1 S. Saripalli, J. F. Montgomery and G. Sukhatme, "Visually guided landing of an unmanned aerial vehicle", IEEE Transactions on Robotics and Automation, Vol. 19, No. 3, pp. 371-380, June, 2003   DOI
2 B. Sinopoli, M. Micheli, G. Donato and T. J. Koo, "Vision based navigation for an unmaaned aerial vehicle", Proceedings 2001 ICRA. IEEE international Conference on Robotics and Automation, Vol. 2, pp. 1757-1764, May, 2001
3 Tien Pham and Leng Sim, "Acoustic detection and tracking of small, low-flying threat aircraft", 23rd Army Science Conference, pp. Dec, 2002
4 Tien Pham and Nino Srour, "TTCP AG-6: Acoustic Detection and Tracking of UAVs", Defense and Security. International Society for Optics and Photonics, pp. 24-30, Sep, 2004
5 Constantino Rago, Ravi Prasanth and Raman K. Mehra, "Failure detection and identification and fault tolerant control using the IMM-KF with applications to the Eagle-Eye UAV", Proceedings of the 37th Conference on IEEE, Vol. 4, pp. 4208-4231, Dec, 1998
6 A. H. Boudinar, N. Benouzza, A. Bendiabdellah, N. Boughanmi, "The use of improved Root- MUSIC frequency estimation method for three phase induction motor incipient rotor's faults detection", Acta Electrotechnica et Informatica, Vol. 8, No. 2, pp. 22-28, Feb, 2008
7 Ding Jianli and Yang Yong, "Aircraft noise Detection based on SVM optimized with gentic algorithm", Journal of Convergence Information Technology(JCIT), Vol. 8, No. 10, pp. 422-428, May, 2013   DOI
8 C. Asensio, M. Ruiz and M. Recuero, "Real-time aircraft noise likeness detector", Applied Acoustics, Vol. 71, No. 6, pp. 539-545, June, 2010   DOI
9 M. Sabri, J. Alirezaie and S. Krishanan, "Audio noise detection using hidden Markov model", Statical Signal Processing, 2003 IEEE Workshop on. IEEE, pp. 627-640, Sept, 2003
10 Hamid Farrokhi, "Performance of Root-MUSIC on TOA estimation for an indoor spread spectrum ranging system", 12th WSEAS International Conference on COMMUNICATIONS, pp. 306-310, July, 2008
11 B. Volcker and B. Orrersten, "Chirp parameter estimation from a sample covariance matrix", IEEE Transactions on Signal Processing, Vol. 49, No. 3, pp. 603-612, Mar, 2001   DOI
12 Jaeil Lee, Youn Joung Kang, Chong Hyun Lee, Seung Woo Lee and Jinho Bae, "Analysis of Features and Discriminability of Transient Signals for a Shallow Water Ambient Noise Environment", Journal of the Institute of Electronics and Information Engineers, Vol. 51, No. 7, pp. 209-220, July, 2013   DOI
13 Guang-Bin Huang, Qin-Yu Zhu and Chee- Kheong Siew, "Extreme learning machine: Theory and applications", Neurocomputing, Vol. 70, No. 1, pp. 489-501, Dec, 2006   DOI
14 C. A. Jensen, M. A. El-Sharkawi and R. J. Maks, "Power System Security Assessment Using Neural Networks: Feature Selection Using Fisher Discrimination", IEEE Trans. on PowerSys, Vol. 16, No. 4, pp. 757-763, Nov, 2001
15 Kibae Lee, Chong Hyun Lee, Jinho Bae and Jaeil Lee, "EEG Signal Classification Algorithm based on DWT and SVM for Driving Robot Control", Journal of the Institute of Electronics and Information Engineers, Vol. 52, No. 8, pp, 117-125, Aug, 2015   DOI
16 Nan-Ying Liang and Guang-Bin Huang, "A fast and accurate online sequential learning algorithm for feedforward networks", IEEE Transactions of Neural Networks, Vol. 17, No. 6, pp. 1411-1423, Nov, 2006   DOI
17 Bo-Hoon Lee, Jae-Hoon Cho and Yong-Tae Kim, "Modeling of Magentic Levitation Logistics Transport System Using Extreme Learning Machine", Journal of the Institute of Electronics and Information Engineers, Vol. 50, No. 1, Jan, 2013
18 Xinjie Wu, "An improved learning machine for classification problem based on affinity propagation clustering", International Journal of Advancements in Computing Technology(IJACT), Vol. 4, No. 10, pp. 274-280, June, 2012   DOI
19 Giorgia Sinibaldi, Luca Marino, "Experimental analysis on the noise of propellers for small UAV", Applied Acoustics, Vol. 74, pp. 79-88, 2013   DOI