发表机构
Indian Institute of Technology Kanpur; United States DEVCOM Army Research Laboratory; Linköping University（坎普尔印度理工学院; 美国DEVCOM陆军研究实验室; 林雪平大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种三阶段信号处理框架，在ISABC系统中联合估计目标与杂波参数并恢复AmBC标签符号，以解耦强耦合信号，提升感知精度与通信可靠性。
AI 中文摘要
集成感知与通信（ISAC）已成为在共享硬件和频谱框架内统一雷达感知与无线通信的关键范式。与此同时，环境反向散射通信（AmBC）作为一种低功耗解决方案，通过调制和反射现有射频信号实现无源连接，已引起广泛关注。受这些进展的启发，本文研究了一种集成感知与环境反向散射通信（ISABC）框架，其中双功能雷达通信（DFRC）收发器在杂乱环境中联合执行高分辨率目标感知和低功耗标签检测。在此ISAC和AmBC背景下，我们开发了一个综合系统模型，联合捕获目标和杂波参数的估计（包括延迟、多普勒频移和复反射率）以及嵌入式AmBC标签符号的恢复。所得到的DFRC信号模型揭示了直达路径反射、杂波回波和无源反向散射信号之间的强耦合，导致高度纠缠的估计问题。为解决这一挑战，我们提出了一种稳健的三阶段信号处理框架，在检测AmBC标签消息之前依次估计目标和杂波参数。这种结构化方法有效解开了叠加分量，提高了ISAC系统中感知精度和通信可靠性。大量仿真以克拉美-罗下界（CRLB）为基准，证明了所提出的基于DFRC的解决方案具有优越的估计性能。结果进一步突出了ISABC系统中感知精度与反向散射通信效率之间的基本权衡。
英文摘要
Integrated sensing and communication (ISAC) has emerged as a key paradigm for unifying radar sensing and wireless communications within a shared hardware and spectral framework. In parallel, ambient backscatter communication (AmBC) has gained attention as a low-power solution for enabling passive connectivity by modulating and reflecting existing radio-frequency signals. Motivated by these developments, this paper investigates an integrated sensing and ambient backscatter communication (ISABC) framework in which a dual-functional radar-communication (DFRC) transceiver jointly performs high-resolution target sensing and low-power tag detection in cluttered environments. Within this ISAC and AmBC setting, we develop a comprehensive system model that jointly captures the estimation of target and clutter parameters, including delay, Doppler shift, and complex reflectivity, together with the recovery of embedded AmBC tag symbols. The resulting DFRC signal model reveals strong coupling among direct-path reflections, clutter echoes, and passive backscatter signals, leading to a highly entangled estimation problem. To address this challenge, we propose a robust three-stage signal processing framework that sequentially estimates target and clutter parameters before detecting the AmBC tag message. This structured approach effectively disentangles the superimposed components, improving both sensing accuracy and communication reliability in ISAC systems. Extensive simulations, benchmarked against the Cramer-Rao lower bound (CRLB), demonstrate the superior estimation performance of the proposed DFRC-based solution. The results further highlight the fundamental trade-offs between sensing accuracy and backscatter communication efficiency in ISABC systems.
