Advertisement

A Method of Simultaneous Signals Spectrum Analysis for Instantaneous Frequency Measurement Receiver

  • Dmitrii Kondakov
  • Alexey Kosmynin
  • Alexander Lavrov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11118)

Abstract

In this paper the simplified problem of frequency determination for multiple simultaneously present harmonic oscillations through subsampling is considered. The proposed (used) subsampling is realized by Dirac function comb with principal frequency much less than input signal frequencies. So all signal frequencies are transformed to first Nyquist zone. We consider subsampling is implemented in three parallel channels when comb principal frequencies are differing but close one to another. Each channel includes also ADC, FFT unit and digital processing unit. Output channel information is a set of possible input frequencies, and these sets intersection is searched for finding input frequencies. Proposed system math model was developed for estimation of ambiguity of recovering values for original input frequencies. The subsampler with three parallel channels was realized as a small unit. It works as mixer with comb type heterodyne in superheterodyne receiver. The subsampler has analog bandwidth up to 5 GHz with 100 MHz principal frequencies. Its experimental characteristics are presented.

Keywords

Subsampling Multicomponent signal Frequency recovering Nyquist zone Dirac function comb 

References

  1. 1.
    Tsui, J.B.Y.: Microwave receivers with electronic warfare applications. Institution of Engineering and Technology (2005)Google Scholar
  2. 2.
    Gruchalla-Wesierski, H., Czyzewski, M., Slowik, A.: The estimation of simultaneous signals frequencies in the IFM receiver using parametric methods. In: MIKON 2008–17th International Conference on Microwaves, Radar and Wireless Communications, vol. 11, pp. 1–4 (2008)Google Scholar
  3. 3.
    Lioun, L.L., Lin, D.M., Tsui, J.B.: Determination of electronic warfare receiver’s instantaneous dynamic range using music method. In: 2008 IEEE National Aerospace and Electronics Conference, pp. 59–67 (2008)Google Scholar
  4. 4.
    Tzou, N.: Low cost sparse multiband signal characterization using asynchronous multi-rate sampling: algorithms and hardware. J. Electr. Test. 31, 85–98 (2015)CrossRefGoogle Scholar
  5. 5.
    Mishali, M., Eldar, Y., Tropp, J.: Efficient sampling of sparse wideband analog signals. In: 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, pp. 290–294 (2008)Google Scholar
  6. 6.
    Venkataramani, R., Bresler, Y.: Perfect reconstruction formulas and bounds on aliasing error in sub-nyquist nonuniform sampling of multiband signals. IEEE Trans. Inform. Theory 46(6), 2173–2183 (2000)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Graf, R.F.: Modern Dictionary of Electronics. In: Electronics & Electrical (1999)Google Scholar
  8. 8.
    Strichartz, R.: Guide to Distribution Theory and Fourier. World Scientific Publishing Company, Singapore (2003)CrossRefGoogle Scholar
  9. 9.
    Kondakov, D.V., Kosmynin, A. N., Lavrov, A. P.: Multicomponent signal frequency estimation algorithm for digital receiver with subsampling. In: RLNC 2017–23th International Conference on Radio Location, Nagivation and Communication, vol. 2, pp. 481–486 (2017). (in Russian)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Dmitrii Kondakov
    • 1
  • Alexey Kosmynin
    • 1
  • Alexander Lavrov
    • 1
  1. 1.Peter the Great St. Petersburg Polytechnic UniversitySt. PetersburgRussia

Personalised recommendations