CoIR:压缩隐式雷达 压缩隐式雷达
IEEE transactions on pattern analysis and machine intelligence
|August 10, 2023
概括
这项研究介绍了CoIR,这是一种使用卷积神经网络和压缩传感的新型稀疏雷达成像方法. 它使用更少的天线实现高精度成像,性能优于标准毫米波 (mmWave) 雷达系统.
科学领域:
- 电气工程 电气工程
- 计算机视觉 计算机视觉
- 信号处理 信号处理
背景情况:
- 毫米波 (mmWave) 信号通过雾和尘埃等不利的环境条件提供强大的成像,优于光学系统.
- 传统的毫米波雷达系统由于物理孔径小和传统的信号处理,因此具有低角度分辨率.
- 稀缺的雷达成像提供了一种解决方案,可以提高光圈尺寸,同时降低功耗和带宽要求.
研究的目的:
- 为毫米波应用开发高精度稀疏雷达成像系统.
- 为了利用隐性神经网络偏差和压缩传感来改进雷达成像.
- 为了减少毫米波雷达系统所需的天线元件的数量.
主要方法:
- 开发了一种名为CoIR的合成分析方法,利用卷积解码器和压缩传感.
- 该系统采用数据集不可知的方法,在训练或测试期间不需要辅助传感器.
- 引入了一种新的稀疏阵列设计,与传统的MIMO阵列相比,使天线元件减少了5.5倍.
主要成果:
- 与标准毫米波雷达相比,CoIR系统表现出优越的成像性能.
- 拟议的方法在模拟和实验毫米波雷达数据上都超过了其他竞争性的未经训练的方法.
- 通过稀疏的雷达成像技术,在角分辨率上取得了显著的改进.
结论:
- 在毫米波应用中,CoIR为稀疏的雷达成像提供了高度准确和高效的解决方案.
- 开发的稀疏阵列设计显著降低了硬件复杂性和成本.
- 这项工作提升了雷达成像系统在具有挑战性的环境中运行的能力.
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