This paper addresses the sensing space identification of arbitrarily shaped continuous antennas. In the context of holographic multiple-input multiple-output (MIMO), a.k.a. large intelligent surfaces, these antennas offer benefits such as super-directivity and near-field operability. The sensing space reveals two key aspects: (a) its dimension specifies the maximally achievable spatial degrees of freedom (DoFs), and (b) the finite basis spanning this space accurately describes the sampled field. Earlier studies focus on specific geometries, bringing forth the need for extendable analysis to real-world conformal antennas. Thus, we introduce a universal framework to determine the antenna sensing space, regardless of its shape. The findings underscore both spatial and spectral concentration of sampled fields to define a generic eigenvalue problem of Slepian concentration. Results show that this approach precisely estimates the DoFs of well-known geometries, and verify its flexible extension to conformal antennas.

翻译：本文针对任意形状连续天线的传感空间识别问题展开研究。在全息多输入多输出（MIMO）系统（又称大规模智能表面）背景下，此类天线具有超指向性与近场可操作性等优势。传感空间揭示了两个关键特性：（a）其维度决定了可实现的最大空间自由度（DoFs）；（b）张成该空间的有限基能够精确描述采样场。以往研究主要聚焦于特定几何形状，亟需将分析扩展至实际共形天线。为此，我们提出一个与天线形状无关的通用框架来确定传感空间。研究结果强调，通过采样场的空间与谱域集中性，可定义Slepian集中性通用特征值问题。实验表明，该方法能精准估计已知几何形状的自由度，并验证了其在共形天线上的灵活扩展能力。