发表机构
MOE Key Laboratory for Intelligent Networks and Network Security, School of Information and Communication Engineering, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University; Institute for Artificial Intelligence, Tsinghua University; State Key Laboratory of Intelligent Technologies and Systems, Tsinghua University; Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University（西安交通大学电子信息工程学院信息与通信工程学院智能网络与网络安全教育部重点实验室; 清华大学人工智能研究院; 清华大学智能技术与系统国家重点实验室; 清华大学自动化系北京信息科学与技术国家研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对 DFT-P-OCDM 同延迟-多普勒 bin 内多径分辨难题，提出 TSUR 框架，可精准分辨路径、鲁棒抗延迟偏移并降低分数多普勒估计误差。
AI 中文摘要
通信系统可在无需专用雷达传输的情况下，复用其发射信号进行感知。对于已确立的 DFT 预处理正交线性调频分复用（DFT-P-OCDM）波形，当双选择性信道中的多条物理路径落入同一同延迟-多普勒 bin 时，该任务会变得困难。在此情况下，从导频推断出的可分辨延迟类别的数量可能少于同 bin 内的物理路径数量，这种不匹配会增加路径数量确定、分数多普勒偏移估计和信道重构的难度。我们推导了同延迟-多普勒 bin 内有多条路径的双选择性信道在 DFT 预处理菲涅耳（DPF）域中的输入与输出之间的逐点关系。基于此输入输出关系，我们提出了两阶段超高分辨率（TSUR）框架：第一阶段利用相位进展的导频估计延迟，第二阶段利用泄漏样本估计每个延迟类别的多普勒和路径数量。此外，我们推导了克拉美-罗下界（CRLB）并分析了导频配置如何权衡感知分辨率与通信恢复。仿真结果表明，TSUR 可分辨同延迟-多普勒 bin 内的相同延迟路径，对现有延迟偏移保持鲁棒性，且比顺序提取和离格基准实现更低的分数多普勒估计误差。
英文摘要
Communication systems can reuse their transmitted signals for sensing without dedicated radar transmissions. For an established DFT-preprocessed orthogonal chirp division multiplexing (DFT-P-OCDM) waveform, this task becomes difficult when several physical paths in a doubly selective channel fall into the same co-delay-Doppler bin. In this case, the number of resolvable delay classes inferred from the pilot may be smaller than the number of physical paths within the co-bin. This mismatch increases the difficulty of path number determination, fractional Doppler offset estimation, and channel reconstruction. We derive a pointwise relationship between the input and output in the DFT preprocessed Fresnel (DPF) domain for doubly selective channels with multiple paths within the co-delay-Doppler bin. Based on this input and output relation, we propose the two stage ultra high resolution (TSUR) framework. The first stage uses pilots of the phase progression to estimate delay, while the second stage uses the leakage samples to estimate the Doppler and the number of paths within each delay class. Furthermore, we derive CRLBs and analyze how the pilot configuration trades sensing resolution and communication recovery. Simulation results demonstrate that TSUR resolves same delay paths within a co-delay-Doppler bin, remains robust to exist delay offsets, and achieves lower fractional Doppler estimation errors than sequential extraction and off-grid baselines.
