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Title

Designing a suitable measurement matrix for reconstruction of radar targets using compressive sensing

Pages

  21-30

Abstract

 Using of Compressive Sensing in Radar systems caused to eliminate the Matched Filter from receiver, and to reduce the required receiver analog-to-digital conversion bandwidth in Radar systems. One of Compressive Sensing parameters is Measurement Matrix. Measurement Matrix for Radar systems is usually random matrix. Although exact recovery of signal using random matrices is possible with high probability and this matrix is incoherent with every basis matrix but implementation of that is impossible in practice. So it is useful to use deterministic matrices as Measurement Matrix. One of these matrices is Alltop Matrix that obtained from Alltop sequence. There are limitations in use of this matrix for Compressive Sensing. We not only will resolve These limitations in this article but also will present a suitable alternative for Matched Filter block based on Compressive Sensing that has better performance in comparison to Matched Filter and can reconstruct Radar targets with lower error than Matched Filter.

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    APA: Copy

    Samadi, Sh., Vali Zadeh, M., & Chehel Amirani, m.. (2021). Designing a suitable measurement matrix for reconstruction of radar targets using compressive sensing. JOURNAL OF RADAR, 8(2 ), 21-30. SID. https://sid.ir/paper/956753/en

    Vancouver: Copy

    Samadi Sh., Vali Zadeh M., Chehel Amirani m.. Designing a suitable measurement matrix for reconstruction of radar targets using compressive sensing. JOURNAL OF RADAR[Internet]. 2021;8(2 ):21-30. Available from: https://sid.ir/paper/956753/en

    IEEE: Copy

    Sh. Samadi, M. Vali Zadeh, and m. Chehel Amirani, “Designing a suitable measurement matrix for reconstruction of radar targets using compressive sensing,” JOURNAL OF RADAR, vol. 8, no. 2 , pp. 21–30, 2021, [Online]. Available: https://sid.ir/paper/956753/en

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