Advertisement

Velocity deception jamming discrimination using quantization effect

  • Mahdi NouriEmail author
  • Mohsen Mivehchy
Mixed Signal Letter

Abstract

In this letter, the effects of number of quantization levels are studied in the airborne digital radio frequency memory (DRFM). The artificial signal, produced by DRFM, has quantized amplitude that results in different cross-correlations (with respect to the real target echo signal), when correlated by continuous reference signal. The proposed method includes a technique to release from the estimation of amplitude fluctuations. Then, a closed-form expression is presented for likelihood ratio test discrimination. Simulation results prove the efficiency and robustness of the proposed method.

Keywords

Deception jamming Digital radio frequency memory Quantization levels Likelihood ratio test 

References

  1. 1.
    Roome, S. J. (1990). Digital radio frequency memory. Electronics and Communication Engineering Journal, 2, 147.CrossRefGoogle Scholar
  2. 2.
    Gold, D., & Ur, H. (1993). Method for reduction of harmonics, caused by coarse quantisation, suitable for digital radio frequency memory. Electronics Letters, 29(4), 411–412.CrossRefGoogle Scholar
  3. 3.
    Berger, S. D. (2003). Digital radio frequency memory linear range gate stealer spectrum. IEEE Transactions on Aerospace and Electronic Systems, 39(2), 725–735.CrossRefGoogle Scholar
  4. 4.
    Richmond, C. D. (2000). Performance of the adaptive sidelobe blanker detection algorithm in homogeneous environments. IEEE Transactions on Signal Processing, 48(5), 1235–1247.MathSciNetCrossRefGoogle Scholar
  5. 5.
    Zhang, J. D., Zhu, X. H., & Wang, H. Q. (2009). Adaptive radar phase-coded waveform design. Electronics Letters, 45(20), 1052–1053.CrossRefGoogle Scholar
  6. 6.
    Garmatyuk, D. S., & Narayanan, R. M. (2002). ECCM capabilities of an ultrawideband bandlimited random noise imaging radar. IEEE Transactions on Aerospace and Electronic Systems, 38(4), 1243–1255.CrossRefGoogle Scholar
  7. 7.
    Aslett, M. (2015). Mercury Co. [Online]. Retrieved March, 2017 from https://mrcy.com/products/microwave-rf/drfm/.
  8. 8.
    Greco, M., Gini, F., & Farina, A. (2008). Radar detection and classification of jamming signals belonging to a cone class. IEEE Transactions on Signal Processing, 56(5), 1984–1993.MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Nouri, M., Mivehchy, M., & Sabahi, M. F. (2017). Novel anti-deception jamming method by measuring phase noise of oscillators in LFMCW tracking radar sensor networks. IEEE Access, 5, 11455–11467.CrossRefGoogle Scholar
  10. 10.
    Nouri, M., Mivehchy, M., & Sabahi, M. F. (2017). Target recognition based on phase noise of received signal. IET Electronics Letters, 53(12), 808–810.CrossRefGoogle Scholar
  11. 11.
    Nouri, M., Mivehchy, M., & Sabahi, M. F. (2017). Target recognition based on phase noise of received laser signal in lidar jammer. Chinese Optics Letters, 15(10), 100302.CrossRefGoogle Scholar
  12. 12.
    Nouri, M., Mivehchy, M., & Sabahi, M. F. (2017). Jammer target discrimination based on local variance of signal histogram in tracking radar and its implementation. Signal, Image and Video Processing, 11(6), 1025–1032.CrossRefGoogle Scholar
  13. 13.
    Nouri, M., Mivehchy, M., & Aghdam, S. A. (2015). Adaptive time-frequency kernel local fisher discriminant analysis to distinguish range deception jamming. IEEE conference on computing, communication and networking technologies (ICCCNT) (pp. 1–5).Google Scholar
  14. 14.
    Nouri, M., Mivehchy, M., Parvaresh, F., & Sabahi, M. F. (2018). Target recognition and discrimination based on multiple-frequencies LFM signal with subcarrier hopping. Multidimensional Systems and Signal Processing, 30, 1–25.zbMATHGoogle Scholar
  15. 15.
    Olivier, K., & Gouws, M. (2013). Modern wideband DRFM architecture and real-time DSP capabilities for radar test and evaluation. In Saudi international conference of electronics, communications and photonics (pp. 1–4).Google Scholar
  16. 16.
    Skolnik, M. I. (1962). Introduction to radar. In M. I. Skolnik (Ed.), Radar handbook. New York: McGraw-Hill.Google Scholar
  17. 17.
    Baillie, R., Borwein, D., & Borwein, J. M. (2008). Surprising sinc sums and integrals. The American Mathematical Monthly, 115(10), 888–901.MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Van Trees, H. L. (2001). Detection, estimation, and modulation theory. New York: Wiley.CrossRefzbMATHGoogle Scholar
  19. 19.
    Siddiqui, M. M. (1962). Some problems connected with Rayleigh distributions. Journal of Research of the National Bureau of Standards, 66, 167–174.MathSciNetzbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Electrical EngineeringUniversity of IsfahanIsfahanIran

Personalised recommendations