RIS辅助的单跳与双跳多径下的单站感知与目标检测
RIS-Aided Monostatic Sensing and Object Detection with Single and Double Bounce Multipath
AI总结：
提出一种RIS辅助的单站感知框架，通过设计预编码与合并方案分离信号，利用双跳RIS感知与单跳非RIS感知结合映射滤波器估计目标，数值结果验证了其有效性。
摘要：
我们提出了一种在单跳和双跳信号传播环境中，由可重构智能表面（RIS）辅助的用户设备（UE）进行单站感知的框架。我们设计了合适的UE侧预编码和合并方案，以促进信号分离。基于链路的几何信道参数，我们推导了可分辨信号的自适应检测概率。然后，我们利用通过无源RIS的双跳信号（即RIS感知）和直接到达目标的单跳多径（即非RIS感知），基于映射滤波器估计无源目标。最后，我们提供了数值结果，证明通过所提出的框架可以实现有效的感知。
英文摘要：
We propose a framework for monostatic sensing by a user equipment (UE), aided by a reconfigurable intelligent surface (RIS) in environments with single- and double-bounce signal propagation. We design appropriate UE-side precoding and combining, to facilitate signal separation. We derive the adaptive detection probabilities of the resolvable signals, based on the geometric channel parameters of the links. Then, we estimate the passive objects using both the double-bounce signals via passive RIS (i.e., RIS-sensing) and the single-bounce multipath direct to the objects (i.e., non-RIS-sensing), based on a mapping filter. Finally, we provide numerical results to demonstrate that effective sensing can be achieved through the proposed framework.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
