基于逆麦克斯韦的墙感知OFDM-ISAC慢速移动目标感知
Inverse Maxwell-Based Wall-Aware OFDM-ISAC for Slow-Moving Target Sensing
- Polytechnique Montréal（蒙特利尔理工学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对穿墙OFDM-ISAC慢速目标感知，提出基于逆麦克斯韦的墙感知距离反演，消除墙体引起的距离偏差，并证明其与平移自由空间分支等价，数值验证有效。
AI中文摘要：
本文研究了短距离室内正交频分复用（OFDM）系统中的集成感知与通信（ISAC），其中感知路径穿越建筑墙体。目标为墙后的慢速移动用户设备，其回波嵌入墙体反射和静态室内杂波中。由于墙体引入额外传播长度、衰减和内部反射，传统延迟变换会报告表观距离。因此，我们将物理距离估计表述为针对已知墙体的逆麦克斯韦问题：距离算子为离散化一维亥姆霍兹方程的畸变玻恩雅可比矩阵，该矩阵由校准后的墙体离线组装，并在线应用于每次快照的距离反演，从而使得距离-多普勒图以物理距离而非表观距离为索引。随后我们证明该算子存在结构性限制：当双向墙体因子具有恒定幅度和线性相位时，墙感知距离图像与自由空间图像在平移网格上完全一致，对于所有脊线水平、锥度和噪声实现均成立。因此，平移相同额外长度的自由空间分支是必要的比较基准。针对代表性分层墙体的仅感知数值结果（所有分支位于同一距离网格，采用共同的后FFT CSI模型）表明，所提出的反演方法消除了墙不知情处理无法消除的距离偏差，且标量校正的自由空间反演与之紧密接近，两者在经验距离均方根误差和检测概率上在整个测试扫描范围内仅存在微小差异。
英文摘要：
In this paper, we study integrated sensing and communication (ISAC) for short-range indoor orthogonal frequency-division multiplexing (OFDM) systems in which the sensing path crosses a building wall. The target is a slow-moving user equipment behind the wall, and its echo is embedded in the wall reflection and static indoor clutter. Because the wall adds excess propagation length, attenuation, and internal reflections, a conventional delay transform reports an apparent range. We therefore formulate physical-range estimation as an inverse Maxwell problem for the known wall: the range operator is the distorted-Born Jacobian of the discretized one-dimensional Helmholtz equation, assembled offline from the calibrated wall and applied online as a per-snapshot range inversion, so that the range-Doppler map is indexed by physical rather than apparent range. We then prove that this operator carries a structural limitation: when the two-way wall factor has constant magnitude and linear phase, the wall-aware range image is identically the free-space image on a translated grid, for every ridge level, taper, and noise realization. A free-space branch translated by the same excess length is therefore a required comparison. Sensing-only numerical results for a representative layered wall, with every branch on one range grid and a common post-FFT CSI model, show that the proposed inverse removes the range bias that wall-unaware processing cannot, and that a scalar-corrected free-space inverse tracks it closely, the two differing only marginally in empirical range RMSE and detection probability across the tested sweep.
