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Sparsity-Aware Adaptive Directional Time–Frequency Distribution for Source Localization

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Abstract

Multi-component characteristics and missing data samples introduce artifacts and cross-terms in quadratic time–frequency distributions, thus affecting their readability. In this study, we propose a new time–frequency method that employs directional smoothing and compressive sensing to reduce cross-terms and mitigate artifacts associated with missing samples. The efficacy of the proposed time–frequency distribution for solving real-life problems is illustrated by employing it to estimate direction of arrival of sparsely sampled sources in under-determined scenario. Numerical results show that the proposed method is superior to other state-of-the-art methods both in terms of obtaining clear time–frequency representation and accurately estimating direction of arrival.

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Authors and Affiliations

  1. Electrical Engineering, Foundation University, Islamabad, Pakistan

    Nabeel Ali Khan

  2. Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan

    Sadiq Ali

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  1. Nabeel Ali Khan
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  2. Sadiq Ali
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Correspondence to Nabeel Ali Khan.

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Ali Khan, N., Ali, S. Sparsity-Aware Adaptive Directional Time–Frequency Distribution for Source Localization. Circuits Syst Signal Process 37, 1223–1242 (2018). https://doi.org/10.1007/s00034-017-0603-9

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