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

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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.

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Authors and Affiliations

  1. School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Jinfeng Hu, Yaxuan Zhang, Huiyong Li, Wei Xia & Jun Li

  2. School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Miao Yang

Authors
  1. Jinfeng Hu
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  2. Yaxuan Zhang
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  3. Miao Yang
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  4. Huiyong Li
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  5. Wei Xia
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  6. Jun Li
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Corresponding author

Correspondence to Jinfeng Hu.

Additional information

This work is supported by the Fundamental Research Funds for the Central Universities of Ministry of Education of China (Grant No. ZYGX2014J021) and the National Natural Science Foundation of China (Grant Nos. 61101172, 61371184, 61101173, 61201280).

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Hu, J., Zhang, Y., Yang, M. et al. Weak harmonic signal detection method from strong chaotic interference based on convex optimization. Nonlinear Dyn 84, 1469–1477 (2016). https://doi.org/10.1007/s11071-015-2582-3

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  • DOI: https://doi.org/10.1007/s11071-015-2582-3

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