发表机构
South China University of Technology; Queen Mary University of London; University of Missouri; Hong Kong Metropolitan University（华南理工大学; 伦敦大学玛丽女王学院; 密苏里大学; 香港都会大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种部分移动平面FAS的两状态可重构稀疏孔径方案，通过种子阵列与信息高效细化位置联合处理，在等预算下降低二维到达角估计误差，并明确其相对全静态稀疏孔径的适用边界。
AI 中文摘要
经典稀疏阵列在有限阵元和射频（RF）链预算下扩大了感知孔径，但其固定几何结构在宽扇区可辨识性与局部角度分辨率之间引入了持续的权衡。本文将这种静态设计转化为两状态可重构稀疏孔径，允许平面流体天线系统（FAS）中的部分端口在初始观测后移动。一个紧凑的、满足奈奎斯特间距的种子阵列首先提供了一种受模糊度控制的采集几何结构。随后，剩余的流体端口移动或切换到信息高效的细化位置，并将重构前后采集的测量数据联合处理。我们在端口总数、RF链总数、移动预算和共同的总快照预算固定的条件下构建接收机。一个策略级Fisher信息矩阵（FIM）恒等式考虑了依赖于观测的细化几何结构。对于单源情况，松弛的平面D-最优分析给出了偏向角落的孔径规律，而有限端口证书则限制了在间距、可达性和部分驱动约束下保留的信息。对于多源情况，一个孔径与条件数代理生成可行的稀疏布局，并使用带有共阵、间距和移动正则化的精确帧FIM进行排序和局部细化。种子多重信号分类（MUSIC）识别出可靠的角度区域，随后在两个状态下进行联合集中似然细化。等预算仿真表明，重构稀疏孔径可将可用面积和移动转化为更低的角度误差，并以更少的驱动端口保留大部分全移动增益。仿真还确定了工作边界：如果全稀疏孔径可以永久部署，则避免移动和快照分割可能更为可取。
英文摘要
Classical sparse arrays enlarge the sensing aperture under limited element and radio-frequency (RF) chain budgets, but their fixed geometries impose a persistent tradeoff between wide-sector identifiability and local angular resolution. This paper converts this static design into a two-state reconfigurable sparse aperture by allowing only part of a planar fluid antenna system (FAS) to move after an initial observation. A compact, Nyquist-spaced seed first provides an ambiguity-controlled acquisition geometry. The remaining fluid ports then move or switch to information-efficient refinement positions, and the measurements collected before and after reconfiguration are jointly processed. We formulate the receiver under fixed total numbers of ports and RF chains, a movement budget, and a common total-snapshot budget. A policy-level Fisher information matrix (FIM) identity accounts for the observation-dependent refinement geometry. For a single source, a relaxed planar D-optimal analysis gives the corner-favoring aperture law, while a finite-port certificate bounds the information retained under spacing, reachability, and partial-actuation constraints. For multiple sources, an aperture-and-conditioning surrogate generates feasible sparse layouts that are ranked and locally refined using the exact frame FIM with coarray, spacing, and movement regularization. Seed multiple signal classification (MUSIC) identifies a reliable angular basin, followed by joint concentrated-likelihood refinement over both states. Equal-budget simulations show that reconfiguring a sparse aperture converts available area and movement into lower angular error and retains much of the all-movable gain with fewer actuated ports. They also identify the operating boundary: if a full sparse aperture can remain permanently deployed, avoiding movement and snapshot splitting can be preferable.
Comments14 figures, 2 tables
