Volume 11 Issue 2
Apr.  2022
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Article Navigation >  Journal of Radars  > 2022  >  11(2): 255-263
Dai Da-hai, Liao Bin, Xiao Shun-ping, Wang Xue-song. Advancements on Radar Polarization Information Acquisition and Processing[J]. Journal of Radars, 2016, 5(2): 143-155. doi: 10.12000/JR15103
Citation: WANG Xinhai, WANG Chaoyu, ZHANG Ning, et al. Phase-only method for designing a unimodular radar waveform with low ISL[J]. Journal of Radars, 2022, 11(2): 255–263. doi: 10.12000/JR21137
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Phase-only Method for Designing a Unimodular Radar Waveform with Low ISL

DOI: 10.12000/JR21137

  • Nanjing Marine Radar Institute, Nanjing 211153, China

Funds:  The National Ministries Foundation
More Information
  • Corresponding author: WANG Xinhai, wangxinhai_csic@163.com
  • Received Date: 2021-09-26
  • Accepted Date: 2022-01-11
  • Rev Recd Date: 2022-01-09
    • Available Online: 2022-01-23
  • Publish Date: 2022-02-21
    Abstract
  • Radar waveform optimization has recently drawn much attention. The radar waveform possesses not only constant amplitude but also a low autocorrelation sidelobe level. However, because of the presence of the constant modular constraint, the problem of optimizing the waveform is non-convex, which is difficult to address. The feasible domain used by the current methods usually contains the vector space with two dimensions: amplitude and phase. The optimization procedures accompanied by the constant constraint enlarge the difficulty and amount of calculation. Herein, the problem of designing unimodular sequences with low autocorrelation sidelobes is addressed, and a novel approach based on phase optimization is presented. The feasible domain is compressed into the vector space with only the phase dimension. The proposed method conducts a deep analysis of the relationship between the phases of the elements in the unimodular sequence and successively updates the vector with a closed-form solution in an element-by-element manner at each iteration using the coordinate descent method, which comprises low computational complexity. By compressing the feasible domain and updating the vector variable using the closed solution, the integrated sidelobe level and computation efficiency are improved. Representative numerical simulations are provided to verify the effectiveness of the proposed method.

     

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