Skip to main content

Detection and Parameter Estimation of MIMO-LFM Signals by Fractional Autocorrelation Envelope

  • Conference paper
  • First Online:
Communications, Signal Processing, and Systems (CSPS 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 463))

  • 69 Accesses

Abstract

This paper proposed an improved method based on fractional Fourier transform (FRFT) for multicarrier LFM signals of MIMO radar (MIMO-LFM) by analyzing its characteristics. First, the intercepted signal model and FRFT are analyzed. Then the signal detection and parameter estimation of MIMO-LFM signals based on FRFT autocorrelation envelope is derived after analyzing the superiority and shortage of conventional FRFT. After that, the detection performance of the proposed method is deduced, and the theoretical results show that this method outperformance the conventional time-frequency method for MIMO-LFM signals processing. Finally, the simulation results demonstrate the validity of the proposed method.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover 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. Haimovich, A.M., Blum, R.S., Cimini, L.J.: MIMO radar with widely separated antennas. IEEE Signal Process. Mag. 25(1), 116–129 (2007)

    Google Scholar 

  2. Li, J., Stoica, P.: MIMO Radar Signal Processing. Wiley-IEEE Press, Hoboken (2008)

    Google Scholar 

  3. Howard, S., Sirianunpiboon, S., Cochran, D.: Detection and characterization of MIMO radar signals. In: International Conference on Radar, pp. 330–334. IEEE (2013)

    Google Scholar 

  4. Tang, X., Tang, J., Tang, B., Gao, Z., Bi, X., Du, J.: A new electronic reconnaissance technology for MIMO radar. In: IEEE CIE International Conference on Radar (Radar), Vol. 1, pp. 79–83. IEEE (2011)

    Google Scholar 

  5. Li, Y., Wang, J., He, X., Tang, B.: A method for PRI estimation of multicomponent LFM signals from MIMO radars. In: IEEE International Conference on Computational Science and Engineering, pp. 1034–1038. IEEE (2014)

    Google Scholar 

  6. Li, Y., Tang, B.: Parameters estimation and detection of MIMO-LFM signals using MWHT. Int. J. Electron. 103(3), 439–454 (2016)

    Google Scholar 

  7. Fang, C., Zi, H., Hong, L., Jun, L.: The parameter setting problem of signal OFDM-LFM for MIMO radar. In: International Conference on Communications, Circuits and Systems. ICCCAS 2008, pp. 876–880. IEEE (2008)

    Google Scholar 

  8. He, Q., He, Z., Li, H.: Multibeam amplitude comparison problems for MIMO radar’s angle measurement. In: Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers. ACSSC 2007, pp. 2163–2167. IEEE (2007)

    Google Scholar 

  9. Ozaktas, H.M., Arikan, O., Kutay, M.A., Bozdagt, G.: Digital computation of the fractional fourier transform. IEEE Trans. Signal Process. 44(9), 2141–2150 (1996)

    Google Scholar 

  10. Mendlovic, D., Ozaktas, H.M., Lohmann, A.W.: Fractional correlation. Appl. Opt. 34(2), 303–309 (1995)

    Google Scholar 

  11. Barbarossa, S.: Analysis of multicomponent LFM signals by a combined Wigner-Hough transform. IEEE Trans. Signal Process. 43(6), 1511–1515 (1995)

    Google Scholar 

  12. Liu, F., Huang, Y., Tao, R., Wang, Y.: Resolution ability of fractional Fourier transform in multi-component LFM signal chirp-rate. In: 4th International Conference on Wireless Communications, Networking and Mobile Computing. WICOM’08, pp. 1–4. IEEE (2008)

    Google Scholar 

  13. Zhaoyang, Q., Jun, Z., Pei, W., Bin, T.: Parameter estimation of phase code and linear frequency modulation combined signal based on fractional autocorrelation and haar wavelet transform. In: IEEE International Conference on Computational Science and Engineering, pp. 936–939. IEEE (2014)

    Google Scholar 

Download references

Acknowledgments

The work in this paper is funded by the National Natural Science Foundation of China (Grant No. 61571088).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yifei Liu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, Y., Kongxiang, M., Qiu, Z., Tang, B. (2019). Detection and Parameter Estimation of MIMO-LFM Signals by Fractional Autocorrelation Envelope. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_28

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-6571-2_28

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6570-5

  • Online ISBN: 978-981-10-6571-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics