无线感知技术是实现泛在感知以及感知通信一体化的关键技术，在物联网应用中具有重要意义。但是，现有的无线感知方案在感知距离和移动性上仍有明显缺陷，感知目标大多需要固定在近距离位置。面对更普遍的长距离移动目标，无线感知技术仍然缺乏可行的方案。在本课题中，我们研究了基于LoRa反向散射的无线感知技术，以拥有长通信距离的LoRa通信信号作为感知载体，在理论感知模型中加入开关键控调制的反向散射标签，利用标签的通信对感知目标进行标记，从而提高模型对移动性和干扰的鲁棒性，适应长距离移动场景下感知任务的需求。我们通过微基准实验分析了在实际信道中使用通信信号进行无线感知时，系统对信号质量的额外要求所带来的挑战，包括幅度不稳定性、漂移、频谱泄漏和信道噪声。根据感知模型，我们设计了完整的感知算法，称为Palantir，从而针对性地解决这些挑战，弥补了使用通信信号进行感知时信号质量上的不足。Palantir不占用额外的信道资源，LoRa与反向散射标签均可以执行原本的通信任务，而Palantir利用正常通信的无线信号完成感知任务。通过使用Palantir，我们可以对长距离移动场景下的骑行者进行呼吸监测。我们实现了 Palantir并进行了全面的基准实验来评估其性能。我们还构建了一个原型系统，对现实世界中的骑行者进行呼吸监测，用以验证Palantir实际部署的可行性。结果表明， Palantir可以在长达100m的距离下完成准确的感知任务，对运动周期的感知误差中值低至0.2%。

Wireless sensing is considered to be the key technology to realize ubiquitous sensing and the integration of sensing and communication. However, the existing wireless sensing schemes still have obvious defects in sensing distance and mobility. Most sensing targets need to be fixed at short distances, and there is still a lack of feasible solutions for wireless sensing of more general long-distance moving targets.In this research, we study the wireless sensing technology based on LoRa backscatter. We take the LoRa signal, which has long communication distance, as the sensing carrier. The ON-OFF-Keying-modulated backscatter tags are added to the theoretical sensing model to perform sensing in long-distance mobile scenarios. We use the communication of tags to mark the sensing target, thereby improving the robustness of the model to mobility and interference, and adapting to the needs of sensing tasks in long-distance mobile scenarios.Through micro-benchmark experiments, we analyze the challenges posed by the additional requirements on signal quality when using communication signals in real channels for wireless sensing, including amplitude instability, offset and drift, spectrum leakage, and channel noise. Based on the sensing model, we design a complete sensing algorithm, named Palantir, to address these challenges in a targeted manner. Palantir makes up for the lack of signal quality when using communication signals for sensing.Palantir does not occupy additional channel resources. Both LoRa and backscatter systems can perform the original communication tasks, while Palantir uses the standard communication wireless signal to complete the sensing task.With Palantir, we can perform respiration detection on cyclists in long-distance mobile scenarios.We implement Palantir and evaluate its performance by conducting comprehensive benchmark experiments. A prototype is also built and a case study of respiration monitoring in the real world is implemented. Results demonstrate that Palantir can perform accurate sensing at a range up to 100m. The median deviation of the detected motion period is as low as 0.2%.