• Journal of Terahertz Science and Electronic Information Technology
  • Vol. 19, Issue 3, 442 (2021)
QIN Zili1、2、3、*, YANG Guan1、2、3, WANG Fangli1、2、3, LI Chao1、2, and JI Yicai1、2、3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.11805/tkyda2019552 Cite this Article
    QIN Zili, YANG Guan, WANG Fangli, LI Chao, JI Yicai. Modified genetic algorithm for optimizing MIMO sparse array[J]. Journal of Terahertz Science and Electronic Information Technology , 2021, 19(3): 442 Copy Citation Text show less

    Abstract

    The array pattern of Multiple Input Multiple Output(MIMO) antenna array has grating lobes due to the large array element spacing, and the false targets that affect the target recognition appear in the radar echo imaging. An improved genetic algorithm is proposed to optimize the array arrangement. The traditional standard genetic algorithm is improved to represent MIMO array with multiple matrix combinations, and the pattern sidelobes of sparse array with random distribution in rectangular plane are optimized. The method based on Logistic chaotic sequence is adopted to generate population disturbance and avoid the optimization process entering into the local optimal state. A uniform regular arrangement of MIMO array with 22 transmitting antennas and 22 receiving antennas and a modified MIMO array optimized by modified genetic algorithm are compared by examples. The results show that the modified genetic algorithm can effectively avoid the grating lobes in the regular array pattern, reduce the side lobes of the pattern, and improve the radar imaging performance. The optimization algorithm has strong practicability for its variable is controllable, which provides a solution for array arrangement of MIMO radar.
    QIN Zili, YANG Guan, WANG Fangli, LI Chao, JI Yicai. Modified genetic algorithm for optimizing MIMO sparse array[J]. Journal of Terahertz Science and Electronic Information Technology , 2021, 19(3): 442
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