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MIMO radar OFDM chirp waveform diversity design with sparse modeling and joint optimization

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Abstract

In multiple-input multiple-output radar systems, the employed waveforms should have a large time-bandwidth product, good correlation property and satisfactory ambiguity function performance. This paper proposes a orthogonal frequency division multiplexing (OFDM) chirp waveform diversity design scheme with sparse modeling and joint optimization of the waveform code matrix and amplitude matrix. First, we formulate the waveform diversity design as a mathematical optimization problem with sparse modeling and optimally design a code matrix to select the hopping frequencies for each waveform. Thereafter, the waveform amplitudes are adaptively designed by minimizing the cross-correlation peaks with genetic algorithm. The proposed method can easily generate multiple pseudo-orthogonal waveforms with satisfactory correlation and ambiguity function performance. Additionally, the impacts of waveform number, hopping frequency interval and selectable frequency index are discussed. The superiority of the proposed OFDM chirp waveform design over existing methods is verified by extensive simulation results.

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Authors and Affiliations

  1. School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Shengjuan Cheng & Wen-Qin Wang

  2. Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China

    H. C. So

Authors
  1. Shengjuan Cheng
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  2. Wen-Qin Wang
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  3. H. C. So
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Corresponding author

Correspondence to Wen-Qin Wang.

Additional information

The work described in this work was supported in by the Program for New Century Excellent Talents in University under grant NCET-12-0095, Sichuan Province Science Fund for Distinguished Young Scholars under grant 2013JQ0003, and a Marie Curie Fellowship (FP7/2007-2013, grant agreement PIIF-GA-2012-326672).

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Cheng, S., Wang, WQ. & So, H.C. MIMO radar OFDM chirp waveform diversity design with sparse modeling and joint optimization. Multidim Syst Sign Process 28, 237–249 (2017). https://doi.org/10.1007/s11045-015-0340-9

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