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A Robust Parameter Estimation of LFM Signal Based on Sigmoid Transform Under the Alpha Stable Distribution Noise

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Abstract

In this paper, a novel method, which employs the fractional Fourier transform and the Sigmoid transform, is proposed to estimate parameters of the linear frequency modulation (LFM) signal under the alpha stable distribution noise environment. Two novel functions, Sigmoid fractional correlation function and Sigmoid fractional power spectrum density (Sigmoid-FPSD), are defined. Basing on these two definitions, a novel method based on Sigmoid-FPSD under alpha stable distribution noise is proposed to estimate parameters of the LFM signal. Moreover, boundedness of Sigmoid-FPSD to the \( S\alpha S \) noise and the feasibility analysis of the Sigmoid-FPSD are presented to evaluate the performance of the proposed method. Both theoretical analysis and simulations demonstrate the superior performances of the proposed approach over other existing methods. Furthermore, the proposed method does not need a priori knowledge of noise with higher estimation accuracy in alpha stable distribution noise environment.

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Acknowledgements

This work was partly supported by the National Natural Science Foundation of China under Grants 61401055 and 61671105, the Ph.D. Programs Foundation of Liaoning Province of China 20170520421 and the China Scholarship Fund.

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Authors and Affiliations

  1. College of Information Engineering, Dalian University, Dalian, 116622, Liaoning, People’s Republic of China

    Li Li

  2. Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, 39762, USA

    Li Li

  3. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, Liaoning, People’s Republic of China

    Tianshuang Qiu

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  1. Li Li
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Li, L., Qiu, T. A Robust Parameter Estimation of LFM Signal Based on Sigmoid Transform Under the Alpha Stable Distribution Noise. Circuits Syst Signal Process 38, 3170–3186 (2019). https://doi.org/10.1007/s00034-018-1008-0

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