Skip to main content
SpringerLink
Log in

Intra-pulse Modulation Feature Analysis for Radar Signals

  • Conference paper
  • First Online:
Recent Trends in Intelligent Computing, Communication and Devices

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1006))

  • 1282 Accesses

Abstract

Radar signal sorting based on intra-pulse parameters is applied in complex electromagnetic environment well. This method provides a new basis and ideas for the sorting and identification of radiation source signals, and also a possible way to improve the current sorting ability of radiation source signals. This paper discusses several aspects from domain analysis, frequency-domain analysis, time–frequency analysis, wavelet analysis, atomic decomposition, high-order statistical analysis, and nonlinear dynamic analysis methods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Danielsen, P.L., Agg, D.A., Burke, N.R.: The application of pattern recognition techniques to ESM data processing. In IEE Colloquium on SP for ESM Systems, 26 Apr: 6/1–6/4 (1988)

    Google Scholar 

  2. Pu, Y.W., Jin, W.D., Zhu, M.: Classification of radar emitter signals using cascade feature extractions and hierarchical decision technique. In: ICSP2006 Proceedings (2006)

    Google Scholar 

  3. Pu, Y.W., Jin, Y.D., Hu, L.Z.: Classification method of instantaneous frequency derivative characteristics of radar emitter signals. J. Harbin Inst. Technol. 1, 136–140 (2009)

    Google Scholar 

  4. Marian, W., Adam, K., Janusz, D., et al.: The method of regression analysis approach to the specific emitter identification. In: International Conference on MIKON, pp. 491–494 (2006)

    Google Scholar 

  5. Janusz, D., Marian, W., Jan, M.: Applying the radiated emission to the specific emitter identification. J. Telecommun. Info. Technol. 2, 57–60 (2005)

    Google Scholar 

  6. Janusz, D., Adam, K., Robert, O.: An application of iterated function system attractor for specific radar source identification. In: 17th International Conference on MIKON, pp. 1–4 (2008)

    Google Scholar 

  7. Lundén, J\., Koivunen, V.: Automatic Radar Waveform Recognition. IEEE J. Selected Top. Signal Process. 1, 124–136 (2007)

    Article  Google Scholar 

  8. Zilberman, E.R., Pace, P,E.: Autonomous time-frequency morphological feature extraction algorithm for LPI radar modulation classification. In: ICIP, pp. 2321–2324 (2006)

    Google Scholar 

  9. Gulum, T.O., Pace, P.E., Cristi, R.: Extraction of polyphase radar modulation parameters using a wigner-ville distribution and radon transform. In: ICASSP, pp. 1505–1508 (2008)

    Google Scholar 

  10. Qiang, G., Ya-jun, L., Chang-hong, W., He-yang, C.: Novel detection method for multi-component LFM signals. In: 2010 First International Conference on Pervasive Computing, Signal Processing and Applications, pp. 759–762 (2010)

    Google Scholar 

  11. Pu, Y.W., Wang, J.H., Jin, W.D.: A novel fractional autocorrelation based feature extraction approach for radar emitter signals. In: ICSP2008 Proceedings, pp. 2338–2341 (2008)

    Google Scholar 

  12. Delpart, N.: Asymptotic wavelet and gabor analysis: extraction of instantaneous frequencies. IEEE Trans. Info. Theory 38(3), 644–664 (1992)

    Article  MathSciNet  Google Scholar 

  13. Chen, T., Jin, W., Chen, Z.: Feature extraction using wavelet transform for radar emitter signals. In: 2009 International Conference on Communications and Mobile Computing, pp. 414–418 (2009)

    Google Scholar 

  14. Chen, C.X., He, M.H., Yu, Ci.: A novel method for extraction of in-pulse feature of LFM signal. In: 2010 2nd International Conference on Industrial Mechatronics and Automation, pp. 692–697 (2010)

    Google Scholar 

  15. Yu, Z.B., Jin, Y.D., Chen, C.X.: Radar emitter signal recognition based on wavelet ridge frequency cascading characteristics. J. SouthWest JiaoTong Uni. 45(2), 290–295 (2010)

    Google Scholar 

  16. Zhang, G., Jin, W., Hu, L.: Application of wavelet packet transform to signal recognition. In: Proceedings of the 2004 International Conference on Intelligent Mechatronics and Automation Chengdu, China, pp. 542–547 (2004)

    Google Scholar 

  17. Zhang, G., Huang, K., Jiang, W., Zhou, Y.: A method for extracting subtle features of radiation sources based on signal envelope. Syst. Eng. Electron. 28(6), 795–797 (2006)

    Google Scholar 

  18. Ren, M.Q., Cai, J.Y., Zhu, Y.Q.: Radar signal feature extraction based on wavelet ridge and high order spectra analysis. In: Radar Conference, 2009 IET International, pp. 1–5 (2009)

    Google Scholar 

  19. Lopez-Risueno, G., Grajal, J., Yeste-Ojeda, O.: Atomic decomposition-based radar complex signal interception. IEE Proc. Radar Sonar Navig. 150(4), 323–331 (2003)

    Google Scholar 

  20. Ming, Z., Weidong, J., Yunwei, P., Laizhao, H., et al.: A novel feature extraction approach for radar emitter signals. In: ICSP2008 Proceedings, pp. 2338–2341 (2008)

    Google Scholar 

  21. Cheng, J.X., Zhang, G.X.: Time-frequency atom feature extraction method for radar signal source of complex system. J. Xi’an Jiaotong Uni.y 44(4), 108–113 (2010)

    Google Scholar 

  22. Si, X.C., Chai, J.F.: Radar signal feature extraction and automatic classification based on FRFT-Based α-envelope curve. J. Electron. Info. Technol. 31(8), 1892–1897 (2009)

    Google Scholar 

  23. Jouny, I., Moses, R.L., Garber, F.D.: Classification of radar signals using the bispectrum. Int. Conf. Acoustics Speech Signal Process. 5, 3429–3432 (1991)

    Google Scholar 

  24. Yang, Z., Zhu, Y., Xu, G., et al.: Signal sorting of unknown radar radiation sources based on HOS. Electron. Countermeasure 123(6), 10–13 (2008)

    Google Scholar 

  25. Hong, S., Huangbin, A.: A radar signal sorting method based on blind source separation. Modern Radar 28(3), 47–50 (2006)

    Google Scholar 

  26. Qin, K.B., Shen, Q., Wang, J.: A novel method for sorting radar emitter signal based on the bispectrum. In: International Conference on Information Engineering and Computer Science, pp. 1–4 (2009)

    Google Scholar 

  27. Han, J., He, M., Cheng, B.: A new method for signal sorting of unknown radar radiation sources. Aerospace Electron. Competition 25(1), 40–43 (2011)

    Google Scholar 

  28. Zhang, G., Jin, W., Hu, L.: Fractal feature extraction of radar emitter signals. In: CEEM’ 2003, pp. 161–164. Hangzhou, China (2003)

    Google Scholar 

  29. Zhang, G.X., Hu, L.Z., Jin W.D.: Complexity feature extraction of radar emitter signals. In: Asia-Pacific Conference on Environmental Electromagnetics CEEM’ 2003, pp. 459–498. Hangzhou, China (2003)

    Google Scholar 

  30. Zhang, G.X., Jin, W.D., Hu, L. Z.: Radar emitter signal recognition based on complexity feature. J. Southwest Jiaotong Uni. 12(2), 116–122 (2004)

    Google Scholar 

  31. Pincus, S.M.: Approximate entropy as a measure of system complexity. Pro. Natl. Acad. Sci 88, 2297–2301 (1991)

    Article  MathSciNet  Google Scholar 

  32. Richman, J.S., Moorman, J.R.: Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 278(6), H2039–H2049 (2000)

    Article  Google Scholar 

Download references

Acknowledgements

This paper was supported in part by the National Natural Science Foundation of China under the Grant no. 61601499, 61701527 and 61601503.

Author information

Authors and Affiliations

  1. Air and Missile Defense College, Air Force Engineering University, Xi’an, 710051, China

    Shi-qiang Wang, Xingcheng Li, Hui-yong Zeng & Juan Bai

  2. Basic Department, Air Force Engineering University, Xi’an, 710051, China

    Caiyun Gao

Authors
  1. Shi-qiang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Caiyun Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xingcheng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hui-yong Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Juan Bai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hui-yong Zeng .

Editor information

Editors and Affiliations

  1. Victoria Business School, Victoria University of Wellington, Wellington, New Zealand

    Vipul Jain

  2. Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. University "Politehnica" of Bucharest, Bucharest, Romania

    Florin Popențiu Vlădicescu

  4. Department of Computer Science and Engineering, Oakland University, Rochester, MI, USA

    Ishwar K. Sethi

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, Sq., Gao, C., Li, X., Zeng, Hy., Bai, J. (2020). Intra-pulse Modulation Feature Analysis for Radar Signals. In: Jain, V., Patnaik, S., Popențiu Vlădicescu, F., Sethi, I. (eds) Recent Trends in Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-9406-5_98

Download citation

Publish with us

Policies and ethics

Search

Navigation