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Instantaneous Frequency Estimation of Nonlinear Frequency-Modulated Signals Under Strong Noise Environment

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Abstract

Instantaneous frequency (IF) is the most important parameter of a signal, which is an important representation of non-stationary signals, such as frequency-modulated signals. Usually, signals are received with noises. Under noise environment, the conventional IF estimation methods for nonlinear frequency-modulated (NLFM) signal cannot work. In this paper, we focus on how to extract IF of NLFM signal under strong noise environment. First, a modified S-method (SM) is proposed to represent the time–frequency (TF) characteristic. The modified SM uses an adaptive smooth window. The symmetric window is used for multi-component signals and asymmetric window for mono-component signals. The modified SM enhances the TF energy concentration and suppresses the cross-terms effectively. Then, the Viterbi algorithm is used to extract the IF from the TF plane. Viterbi algorithm is a hidden Markov chain approach, which is proposed here as the IF estimator. The proposed method is utilized for various types of NLFM signals. Simulation results demonstrate the efficiency and validity of the proposed method under strong noise environment.

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Authors and Affiliations

  1. School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an, 710055, People’s Republic of China

    Li Jiang

  2. School of Electronic Engineering, Xidian University, Xi’an, 710071, People’s Republic of China

    Li Jiang, Lin Li, Guoqing Zhao & Yang Pan

Authors
  1. Li Jiang
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  2. Lin Li
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  3. Guoqing Zhao
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  4. Yang Pan
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Correspondence to Lin Li.

Additional information

This research was supported by Science and Technology Foundation of Xi’an University of Architecture and Technology (Grant No. QN1507) and the National Natural Science Foundation of China (Grant No. 61201287).

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Jiang, L., Li, L., Zhao, G. et al. Instantaneous Frequency Estimation of Nonlinear Frequency-Modulated Signals Under Strong Noise Environment. Circuits Syst Signal Process 35, 3734–3744 (2016). https://doi.org/10.1007/s00034-015-0230-2

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  • DOI: https://doi.org/10.1007/s00034-015-0230-2

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