Volume 11 Issue 4
Aug.  2022
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FAN Wen, YU Baoguo, CHEN Jing, et al. Joint waveform optimization and antenna position selection for MIMO radar beam scanning[J]. Journal of Radars, 2022, 11(4): 530–542. doi: 10.12000/JR22135
Citation: FAN Wen, YU Baoguo, CHEN Jing, et al. Joint waveform optimization and antenna position selection for MIMO radar beam scanning[J]. Journal of Radars, 2022, 11(4): 530–542. doi: 10.12000/JR22135
shu

Joint Waveform Optimization and Antenna Position Selection for MIMO Radar Beam Scanning

doi: 10.12000/JR22135
  • 1.

    The 54th Research Institute of CETC, Shijiazhuang 050081, China

  • 2.

    State Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang 050081, China

  • 3.

    School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China

Funds:  The National Key Research and Development Program (2021YFB3900801)
More Information
  • Corresponding author: FAN Wen, fanwen@mail.nwpu.edu.cn
  • Received Date: 2022-07-06
  • Rev Recd Date: 2022-08-12
    • Available Online: 2022-08-15
  • Publish Date: 2022-08-25
    Abstract
  • In this study, under the Peak-to-Average Power Ratio (PAPR), energy, and binary (for antenna position selection) constraints, we proposed an antenna position selection and beam scanning method for colocated Multiple-Input Multiple-Output (MIMO) radar system using the min-max beampattern amplitude matching criterion. In our design, antenna positions and a set of probing waveforms were jointly determined to match a set of beampattern masks, and hence realize the beam scan. The resultant problem was large-scale, nonconvex, nonsmooth, and typical nondeterministic hard, because of the PAPR and nonconvex binary constraints, and the max and modulus operations in the objective function. To address these issues, we first transformed the min-max problem into the Iterative weighted Least Squares (ILS) problem using the Lawson algorithm, replaced the nonsmooth nonconvex objective function with the convex majorization function, and finally applied the alternating direction method of multipliers to solve the majorized ILS problem. Finally, several numerical examples were given to show the effectiveness of the proposed algorithms.

     

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