Abstract
Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for radar signal detection. In this paper, a novel radar detection approach based on time-frequency distribution (TFD) is proposed. Exploiting the complementation of linear TFD and bilinear TFD approaches, the cross terms of Wigner-Ville distribution (WVD) are suppressed. By using an optimal threshold selected adaptively, the regions of WVD auto terms are determined exactly. And the multicomponent radar signals can be detected efficiently. Simulation results show that this approach can efficiently detect not only linear frequency modulation (LFM) signals, but also normal signals and phase modulation (BPSK and QPSK) signals.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ren M, Cai J, Zhu Y, He M (2008) Radar emitter signal classification based on mutual information and fuzzy support vector machines. In: Proceedings of international conference on software process, Beijing, China, pp 1641–1646
Latombe G, Granger E, Dilkes F (2010) Fast learning of grammar production probabilities in radar electronic support. IEEE Trans Aerosp Electron Syst 46(3):1262–1290
Bezousek P, Schejbal V (2004) Radar technology in the Czech Republic. IEEE Aerosp Electron Syst Mag 19(8):27–34
Li X, Bi G, Ju Y (2009) Quantitative SNR analysis for ISAR imaging using LPFT. IEEE Trans Aerosp Electron Syst 45(3):1241–1248
Xing M, Wu R, Li Y, Bao Z (2009) New ISAR imaging algorithm based on modified Wigner-Ville distribution. IET Radar Sonar Navig 3(1):70–80
Jianxun L, Qiang LV, Jianming G, Chunhua, X (2007) An intelligent signal processing method of radar anti deceptive jamming. In: Wen TD (ed) ISTM/2007: 7th international symposium on test and measurement, vols 1–7, conference proceedings, Chinese Soc Modern Tech Equipment; Chinese Assoc Higher Educ, (2007) 1057–1060 7th international symposium on test measurement, Beijing, Peoples Republic China, August 05–08
Svensson A, Jakobsson A (2001) Adaptive detection of a partly known signal corrupted by strong interference. IEEE Signal Process Lett 18(12):729–732
Bin GF, Liao CJ, Li, XJ (2011) The method of fault feature extraction from acoustic emission signals using Wigner-Ville distribution. In: Yang YH, Qu XL, Luo YP, Yang A (eds) Optical, electronic materials and applications, PTS 1-2, volume 216 of advanced materials research, Hunan institute engineering, Hunan university science and technology, Shanghai Jiaotong university, Chongqing normal university, Wuhan university technology, Nanyang technology university, Hebei polytechnic university, international conference on optical, electronic materials and applications, Chongqing, Peoples Republic China, pp 732–737, March 04–06
Feng L, Peng SD, Ran T, Yue W (2008) Multi-component LFM signal feature extraction based on improved wigner-hough transform. In: 2008 4th international conference on wireless communications, networking and mobile computing, vols 1–31, international conference on wireless communications, networking and mobile computing, IEEE communication society, IEEE Antennas and propagation society, Dalian university technology, Wuhan university, Scientific research publishing, (2008) 1938–1941 4th international conference on wireless communications, networking and mobile computing, Dalian, Peoples Republic China, October 12–17
Li L, Ji HB, Jiang L (2011) Quadratic time-frequency analysis and sequential recognition for specific emitter identification. IET Signal Proc 5(6):568–574
Zhang G, Rong H, Jin W (2006) Pulse modulation recognition of unknown radar emitter signals using support vector clustering. Lecture Notes in Artificial Intelligence (FSKDZO06), vol 4223. Springer, Heidelberg, pp 120–429
Rong H, Zhang G, Jin W (2006) Application of S-method to multi-component emitter signals. In: Lecture Notes in Artificial Intelligence (FSKDZO06), vol 4223, Springer, pp 420–429
Haykin S, Bhattacharya T (1997) Modular learning strategy for signal detection in a nonstationary environment. IEEE Trans Signal Process 45(6):1619–1637
Cohen L (1989) Time-frequency distributions-a review. Proc IEEE 77(7):941–981
Li Q, Shui P, Lin Y (2006) A new method to suppress cross-terms of WVD via thresholding superimposition of multiple spectrograms. J Electron Inf Technol 28(8):1435–1438
Mann S, Haykin S (1995) The chirplet transform: physical considerations. IEEE Trans Signal Process 43(11):2745–2761
Bultan A (1999) A four-parameter atomic decomposition of chirplets. IEEE Trans Signal Process 47(3):731–745
Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(1):62–66
Acknowledgments
This work was supported by a grant from National Natural Science Foundation of China (grant number: 61102084).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, Z., Yang, Z., Yin, Z., Quan, T. (2014). A Novel Radar Detection Approach Based on Hybrid Time-Frequency Analysis and Adaptive Threshold Selection. In: Sun, F., Li, T., Li, H. (eds) Knowledge Engineering and Management. Advances in Intelligent Systems and Computing, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37832-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-37832-4_8
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37831-7
Online ISBN: 978-3-642-37832-4
eBook Packages: EngineeringEngineering (R0)