Advertisement

Nonlinear Dynamics

, Volume 84, Issue 3, pp 1469–1477 | Cite as

Weak harmonic signal detection method from strong chaotic interference based on convex optimization

  • Jinfeng Hu
  • Yaxuan Zhang
  • Miao Yang
  • Huiyong Li
  • Wei Xia
  • Jun Li
Original Paper

Abstract

Noticing that the second-order matrix of chaotic signal is stationary, we propose a method for detecting weak harmonic signal from strong chaotic interference based on convex optimization. After a data matrix in frequency domain is composed by combining reference cells and the detection cell, we detect weak harmonic signals by searching each frequency channel based on an optimization filter. Then, the signal detection problem is boiled down to an optimization problem. Further, we design an optimization filter based on second-order cone programs. The filter can maintain the gain of signal from current frequency channel and suppress signals from other frequency channels. The harmonic signal can be detected by the output signal-to-interference-plus-noise ratio (SINR) of each frequency channel. Compared with the neural network methods, the proposed method has following advantages: (1) It can detect weak harmonic signal under lower SINR and (2) it is robust against white Gaussian noise.

Keywords

Chaos Optimal filter Signal detection Output SINR 

References

  1. 1.
    Xing, H.Y., Cheng, Y.Y., Xu, W.: Detection of weak target signal with least-squares support vector machine and generalized embedding windows under chaotic background. Acta Phys. Sin. 61(10), 100506–100506 (2012)Google Scholar
  2. 2.
    Xiang, X.Q., Shi, B.C.: Weak signal detection based on the information fusion and chaotic oscillator. Chaos Interdiscip. J. Nonlinear Sci. 20(1), 261–300 (2010)Google Scholar
  3. 3.
    Zhang, J.G., Xu, H., Wang, B.J., Liu, L., Su, P.C., Li, J.X.: Wiring fault detection with Boolean-chaos time-domain reflectometry. Nonlinear Dyn. 80, 553–559 (2015)CrossRefGoogle Scholar
  4. 4.
    Li, H.T., Zhu, S.L., Qi, C.H., Gao, M.X., Wang, G.Z.: Nonlinear analysis of drivers heart rate variability on the Prairie Highway. Adv. Mater. Res. 734, 3145–3151 (2013)CrossRefGoogle Scholar
  5. 5.
    Wu, Y.F., Huang, S.P., Jin, G.B.: Study on partial discharge signal detection by coupled Duffing oscillators. Acta Phys. Sin. 62(13), 130505–130505 (2013)Google Scholar
  6. 6.
    Khunkitti, P., Kaewrawang, A., Siritaratiwat, A., Mewes, T., Mewes, C.K., Kruesubthaworn, A.: A novel technique to detect effects of electromagnetic interference by electrostatic discharge simulator to test parameters of tunneling magnetoresistive read heads. J. Appl. Phys. 117(17), 17A908 (2015)CrossRefGoogle Scholar
  7. 7.
    Panagopoulos, S., Soraghan, J.J.: Small-target detection in sea clutter. IEEE Trans. Geos. Remote Sens. 42(7), 1355–1361 (2004)CrossRefGoogle Scholar
  8. 8.
    Guan, J., Liu, N.B., Huang, Y., He, Y.: Fractal characteristic in frequency domain for target detection within sea clutter. IET Radar Sonar Navig. 6(5), 293–306 (2012)CrossRefGoogle Scholar
  9. 9.
    Eski, I., Temürlenk, A.: Design of neural network-based control systems for active steering system. Nonlinear Dyn. 73(3), 1443–1454 (2013)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Ivancevic, T., Jain, L., Pattison, J., Hariz, A.: Nonlinear dynamics and chaos methods in neurodynamics and complex data analysis. Nonlinear Dyn. 56(1–2), 23–44 (2009)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Tuntas, R.: A new intelligent hardware implementation based on field programmable gate array for chaotic systems. Appl. Soft Comput. 35, 237–246 (2015)CrossRefGoogle Scholar
  12. 12.
    Hennessey, G., Leung, H., Drosopoulos, A., Yip, P.C.: Sea-clutter modeling using a radial-basis-function neural network. IEEE J. Ocean. Eng. 26(3), 358–372 (2001)CrossRefGoogle Scholar
  13. 13.
    Han, M., Xi, J., Xu, S., Lin, F.L.: Prediction of chaotic time series based on the recurrent predictor neural network. IEEE Trans. Signal Process. 52(12), 3409–3416 (2004)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Jaeger, H., Haas, H.: Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science 304(5667), 78–80 (2004)CrossRefGoogle Scholar
  15. 15.
    Xue, Y.B., Yang, L., Haykin, S.: Decoupled echo state networks with lateral inhibition. Neural Netw. 20(4), 365–376 (2007)CrossRefMATHGoogle Scholar
  16. 16.
    Vali, R., Berber, S.M., Nguang, S.K.: Analysis of chaos-based code tracking using chaotic correlation statistics. IEEE Trans. Cir. Syst. I Reg. Pap. 59(4), 796–805 (2012)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Vidal, P., Kanzieper, E.: Statistics of reflection eigenvalues in chaotic cavities with nonideal leads. Phys. Rev. Lett. 108(20), 206806 (2012)CrossRefGoogle Scholar
  18. 18.
    Li, C.T., Lee, C.W., Shen, J.J.: An extended chaotic maps-based keyword search scheme over encrypted data resist outside and inside keyword guessing attacks in cloud storage services. Nonlinear Dyn. 80(3), 1601–1611 (2015)Google Scholar
  19. 19.
    Hu, J.F., Guo, J.B.: Breaking a chaotic secure communication scheme. Chaos Interdiscip. J. Nonlinear Sci. 18(1), 013121 (2008)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Zheng, H., Hu, J., Wu, P., Liu, L., He, Z.: Study on synchronization and parameters insensitivity of a class of hyperchaotic systems using nonlinear feedback control. Nonlinear Dyn. 67(2), 1515–1523 (2012)MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Vorobyov, S.A., Gershman, A.B., Luo, Z.: Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem. IEEE Trans. Signal Process. 51(2), 313–324 (2003)CrossRefGoogle Scholar
  22. 22.
    Khabbazibasmenj, A., Vorobyov, S.A., Hassanien, A.: Robust Adaptive Beamforming Based on Steering Vector Estimation With as Little as Possible Prior Information. IEEE Trans. Signal Process. 60(6), 2974–2987 (2012)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Jinfeng Hu
    • 1
  • Yaxuan Zhang
    • 1
  • Miao Yang
    • 2
  • Huiyong Li
    • 1
  • Wei Xia
    • 1
  • Jun Li
    • 1
  1. 1.School of Electronic EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of Resources and EnvironmentUniversity of Electronic Science and Technology of ChinaChengduChina

Personalised recommendations