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Measurement matrix design for CS-MIMO radar using multi-objective optimization

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Abstract

In this paper, we design a measurement matrix for a compressive sensing-multiple-input multiple-output radar in the presence of clutter and interference. To optimize the measurement matrix, three main criteria are considered simultaneously to improve detection and sparse recovery performance while suppressing clutter and interference. To this end, we consider three well-known criteria including Bhattacharyya distance, mutual coherency of sensing matrix, and signal-to-clutter-plus-interference ratio. Due to the use of simultaneous multi-objective functions, a multi-objective optimization (MOO) framework is exploited. Some numerical examples are provided to illustrate the achieved improvement of our proposed method in target detection and sparse recovery performance. Simulation results show that the proposed MOO technique for measurement matrix design can achieve superior performance in target detection compared with Gaussian random measurement matrix technique.

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Authors and Affiliations

  1. The Array Processing Lab., School of Electrical Engineering, University of Tehran, Tehran, Iran

    Nafiseh Shahbazi & Aliazam Abbasfar

  2. Iran University of Science and Technology, Tehran, Iran

    Mohammad Jabbarian-Jahromi

Authors
  1. Nafiseh Shahbazi
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  2. Aliazam Abbasfar
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  3. Mohammad Jabbarian-Jahromi
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Correspondence to Aliazam Abbasfar.

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Shahbazi, N., Abbasfar, A. & Jabbarian-Jahromi, M. Measurement matrix design for CS-MIMO radar using multi-objective optimization. Multidim Syst Sign Process 29, 761–782 (2018). https://doi.org/10.1007/s11045-017-0542-4

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  • DOI: https://doi.org/10.1007/s11045-017-0542-4

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