基于共形超表面天线的计算微波定位与材料识别
Computational Microwave Localization and Material Identification Using Conformal Metasurface Antennas
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中文总结 AI 辅助
该研究提出采用共形频率分集超表面天线的微波传感方法，可联合定位识别管道内材料，无需大型阵列等复杂硬件，能区分金属、木材、尼龙棒并定位，还可扩展至双目标定位。
中文摘要 AI 辅助
本文提出一种采用共形频率分集超表面的简单紧凑微波传感方法，用于联合定位和识别管道内的材料。该频率分集超表面由电尺寸大的基片集成波导（SIW）构成，其上印制具有不同谐振频率的超材料辐射单元。这些天线可产生空间上不同的方向图，能将信息编码到简单的频率扫描中。将两个此类天线环绕在管道周围，以定位和识别内部物体，从而用简单的频率扫描替代庞大复杂的断层扫描天线阵列。为此，通过将不同材料制成的目标物放置在可能位置的网格中，实验构建传感矩阵。利用计算处理，我们表明该系统可成功区分金属、木材和尼龙棒，并通过独特的频率特征准确确定其位置。研究了该方法在双目标定位中的扩展应用。结果凸显了一种简单、低成本且可靠的微波传感框架，无需大型阵列、扫描或复杂硬件即可实现材料表征和定位。
英文摘要
This paper presents a simple and compact microwave sensing approach using conformal frequency-diverse metasurfaces to jointly localize and identify materials within a pipe. The frequency-diverse metasurfaces consist of an electrically large SIW patterned with metamaterial radiators with diverse resonant frequencies. These antennas can generate spatially distinct patterns that can encode information into simple frequency sweeps. Two such antennas are wrapped around a pipe to localize and identify objects inside, thereby replacing large, complex tomographic antenna arrays with simple frequency sweeps. To do that, a sensing matrix is experimentally populated using targets made of different materials placed in a grid of possible locations. Using computational processing, we show that the system successfully distinguishes among metal, wood, and nylon rods and accurately localizes their positions using unique frequency signatures. The extension of this method to two-object localization is examined. The results highlight a simple, low-cost, and reliable framework for microwave sensing that enables material characterization and localization without large arrays, scanning, or complex hardware.
