混合智能非线性优化用于FDA-MIMO静态平台上的被动微波阵列雷达
Yimeng Zhang1, Wenxing Li1, Bin Yang2
1College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China.
Micromachines
|January 28, 2026
概括
本研究介绍了一种用于被动微波阵列的新型非线性频率抵消设计,增强5G/6G通信和雷达系统. 这种新方法提高了静态平台的空间分辨率和干扰抑制.
科学领域:
- 电磁学和波浪传播
- 天线理论和设计.
- 信号处理 信号处理
背景情况:
- 被动微波阵列组件对于5G/6G,汽车雷达和传感器至关重要.
- 目前的设计面临空间分辨率和干扰抑制的局限性,原因是固定几何和单频激发.
- 现有的频率多元阵列多输入多输出 (FDA-MIMO) 架构存在范围角度合和有限的束形灵活性.
研究的目的:
- 为被动微波阵列提出非线性频率抵消设计,以克服当前架构的局限性.
- 增强空间光谱自由度,以改善聚焦和干扰抑制.
- 制定一个强大的优化策略,解决多个目标和环境干扰.
主要方法:
- 对于非线性频率抵消设计,使用了Dingo-Gray Wolf混合智能优化器.
- 采用了多度健身功能,同时优化侧叶抑制,零造型和频率偏移平滑度.
- 在静态场景中进行了模拟,以评估在空间-光谱不匹配下的性能.
主要成果:
- 提出的方法实现了高分辨率的二维聚焦,超越了传统方法.
- 显著提高干扰抑制能力被证明.
- 即使在现实的空间频谱不匹配的情况下,也观察到稳定的性能,这表明了强度.
结论:
- 非线性频率抵消设计有效地提高了静态平台上的被动微波阵列组件的可控性和稳定性.
- 这种方法为需要精确的空间光谱控制的先进通信和传感系统提供了有希望的解决方案.
- 混合智能优化策略为设计复杂的射频前端元件提供了强大的工具.
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