Hybrid wireless localization with a new radio frequency beamforming scheme

近年来，为了满足物联网时代日益增长的短程定位需求，出现了许多解决方案。示例包括基于无线通信网络、传感器网络、射频识别（RFID）以及调频连续波（FMCW）和超宽带（UWB）系统的系统。大多数解决方案依赖于已建立的网络或询问器，并且目标必须携带诸如蜂窝电话和RFID标签之类的设备。FMCW/UWB系统可以在不要求目标携带任何设备的情况下定位目标，但需要较大的传输信号带宽来实现理想的距离分辨率。该项目将探索射频（RF）压缩感知解决方案和混合模式定位机制，用于短程无线定位。提出的解决方案还将以用户为中心，通过有效地感知用户活动和优化资源分配。它将显著降低硬件成本、功耗、电路复杂性、频谱使用和信号处理负载。本研究的最终目标是在低成本移动设备上实现无处不在的短距离无线定位。它将影响许多无线系统和应用，从而对我们的社会产生广泛的影响。该项目旨在开发下一代无线定位系统。与传统的压缩传感雷达或定位系统在解调期间或之后进行数据压缩不同，该解决方案将有效地压缩基于先进射频波束形成阵列产生的多波束辐射方向图的数据。该阵列将以随机辐射模式探测空间，而不是单一的扫描光束，从而减少了空间样本的数量和采集样本所需的资源。与传统的数字波束形成方案相比，该方案具有硬件成本低、功耗小、电路复杂度低等优点。此外，将设计一种混合模式定位机制，融合多普勒/干涉、频移键控（FSK）和FMCW检测模式的优点，根据目标的状态切换检测模式，使频谱使用和信号处理负荷降到最低。该系统将通过以用户为中心的操作进一步减少频谱使用，该操作基于人体运动特征有效地感知和跟踪人体受试者。将衍生出特殊的定位算法来识别与其他物体不同的独特人类行为。该项目将积极让K-12和本科生参与研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Many solutions have been developed in recent years to meet the increasing demand of short-range localization in the internet of things (IoT) era. Examples include systems based on wireless communication networks, sensor networks, radio-frequency identification (RFID), as well as frequency modulated continuous-wave (FMCW) and ultra-wideband (UWB) systems. Most of the solutions rely on established networks or interrogators, and the targets must carry devices such as cellular phones and RFID tags. FMCW/UWB systems can localize objects without requiring the targets to carry any device but need a large transmitted signal bandwidth to achieve desirable range resolution. This project will explore a radio frequency (RF) compressed sensing solution and a hybrid-mode localization mechanism for short-range wireless localization. The proposed solution will also be user-centered by efficiently sensing user activities and optimizing resource allocation. It will significantly reduce the hardware cost, power consumption, circuit complexity, spectrum usage, and signal processing load. The ultimate goal of this research is to achieve ubiquitous short-range wireless localization on low-cost mobile devices. It will influence many wireless systems and applications, and thus have broad impacts to our society.This project aims to develop the next generation wireless localization system. Different from conventional compressed sensing radar or localization systems that mostly perform data compression during or after demodulation, the proposed solution will efficiently compress data based on multi-beam radiation patterns produced by an advanced RF beamforming array. The array will probe the space with randomized radiation patterns instead of a single scanning beam, thus reducing the amount of spatial samples and the resources required to take the samples. Compared with conventional digital beamforming, the proposed solution is advantageous in lower hardware cost, less power consumption and lower circuit complexity. In addition, a hybrid-mode localization mechanism will be devised to fuse the advantages of Doppler/interferometry, frequency shift keying (FSK), and FMCW detection modes, so that the spectrum usage and signal processing load are kept to the minimum by switching the detection mode based on the status of the targets. The system will further reduce spectrum usage by user-centered operation, which efficiently senses and tracks human subjects based on human motion characteristics. Special localization algorithms will be derived to identify the unique human behavior that is distinct from other objects. The project will actively involve K-12 and undergraduate students in research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.