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Iterative missing data recovery algorithm for non-stationary signals

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Abstract

This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding components to convert them into stationary components. Following this, a relatively recent nonparametric iterative missing data recovery procedure is employed to reconstruct the time-varying amplitudes of the signal components. The complete signal is constructed by adding all the estimated components, which is used as an input signal to re-estimate the IFs and time-varying amplitudes in an iterative procedure. Studies based on simulated and real data sets show that the proposed approach provides better estimates as compared to the state of the art.

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Acknowledgements

This research was partly funded by internal research grant of Foundation University Islamabad (grant number: FUI/ORIC/IFP-Grant#78).

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Authors and Affiliations

  1. Foundation University Islamabad, Islamabad, Pakistan

    Nabeel Ali Khan

  2. Faculty of Engineering Sciences, GIK Institute, Topi, Pakistan

    Naveed R. Butt

  3. Center for Mathematical Sciences, Lund University, 22100, Lund, Sweden

    Andreas Jakobsson

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  1. Nabeel Ali Khan
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  2. Naveed R. Butt
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  3. Andreas Jakobsson
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Correspondence to Naveed R. Butt.

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Khan, N.A., Butt, N.R. & Jakobsson, A. Iterative missing data recovery algorithm for non-stationary signals. SIViP 16, 1731–1738 (2022). https://doi.org/10.1007/s11760-021-02128-5

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  • DOI: https://doi.org/10.1007/s11760-021-02128-5

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