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Diagnosis of Faulty Sensors in Phased Array Radar Using Compressed Sensing and Hybrid IRLS–SSF Algorithm

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Abstract

In this work, a compressed sensing technique for diagnosis of faulty sensor in an array antenna is proposed. This technique starts from collecting the measurement of the far field pattern. The system relating the difference among the field measured using the healthy reference array and the field radiated by the array under test is analyzed using a parallel coordinate descent (PCD) algorithm, separable surrogate functionals (SSF) algorithm, iterative-reweighted-least-squares (IRLS) algorithm and hybrid IRLS–SSF. These algorithms are applied for complete and partial defective sensors in an array antenna. The simulation results indicate that the proposed hybrid algorithm outperforms in terms of localization of failure sensor with a less number of measurements. It has been shown that the hybrid IRLS–SSF algorithm provides an accurate diagnosis of complete and partial defective sensors as compared to PCD, SSF or IRLS alone. Variety of simulations has been provided to validate the performance of the designed algorithms in diversified scenarios.

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Authors and Affiliations

  1. School of Engineering and Applied Sciences, ISRA University, Islamabad, Pakistan

    Shafqat Ullah Khan

  2. Department of Electrical Engineering, Air University Islamabad, Islamabad, Pakistan

    Ijaz Mansoor Qureshi

  3. Department of Electronic Engineering, International Islamic University, Islamabad, Pakistan

    Hassan Haider & Bilal Shoaib

  4. Department of Electrical Engineering, COMSATS Institute of Information Technology Attock, Lahore, Pakistan

    Fawad Zaman

Authors
  1. Shafqat Ullah Khan
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  2. Ijaz Mansoor Qureshi
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  3. Hassan Haider
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  4. Fawad Zaman
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  5. Bilal Shoaib
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Correspondence to Shafqat Ullah Khan.

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Khan, S.U., Qureshi, I.M., Haider, H. et al. Diagnosis of Faulty Sensors in Phased Array Radar Using Compressed Sensing and Hybrid IRLS–SSF Algorithm. Wireless Pers Commun 91, 383–402 (2016). https://doi.org/10.1007/s11277-016-3466-7

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  • DOI: https://doi.org/10.1007/s11277-016-3466-7

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