Hybrid wireless localization with a new radio frequency beamforming scheme

采用新射频波束形成方案的混合无线定位

• 批准号: 1808613
• 负责人: Changzhi Li
• 金额: $ 32.5万
• 依托单位: Texas Tech University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1808613&HistoricalAwards=false
• 关键词: Hybrid; wireless; localization; new; radio

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.

近年来，已经开发了许多解决方案来满足物联网（IoT）时代对短距离定位日益增长的需求。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，目标必须携带手机和RFID标签等设备。FMCW/UWB系统可以定位目标而不需要目标携带任何设备，但需要大的发射信号带宽来实现所需的距离分辨率。该项目将探索用于短距离无线定位的射频（RF）压缩传感解决方案和混合模式定位机制。所提出的解决方案还将通过有效地感知用户活动和优化资源分配来以用户为中心。它将显著降低硬件成本、功耗、电路复杂度、频谱使用和信号处理负载。本研究的最终目标是在低成本的移动的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。与传统的压缩感知雷达或定位系统主要在解调期间或之后执行数据压缩不同，所提出的解决方案将基于由先进的RF波束成形阵列产生的多波束辐射图案来有效地压缩数据。该阵列将用随机辐射模式而不是单个扫描波束探测空间，从而减少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，混合模式定位机制将被设计为融合多普勒/干涉测量，频移键控（FSK），和FMCW检测模式的优点，使频谱使用和信号处理负载保持在最低限度，通过切换检测模式的基础上的目标的状态。该系统将通过以用户为中心的操作进一步减少频谱使用，从而基于人体运动特征有效地感知和跟踪人体主体。特殊的定位算法将被推导出来，以确定独特的人类行为，是不同于其他对象。这个奖项反映了NSF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。

项目成果

Violin Gesture Recognition Using FMCW Radars

• DOI: 10.1109/wisnet56959.2023.10046213
• 发表时间: 2023-01
• 期刊: 2023 IEEE Topical Conference on Wireless Sensors and Sensor Networks
• 作者: Hannah Gao;Christopher Williams;V. G. R. Varela;Changzhi Li

A Spectrum-Efficient FSK Radar Solution for Stationary Human Subject Localization Based on Vital Sign Signals

基于生命体征信号的静态人体定位的频谱效率 FSK 雷达解决方案

• DOI: 10.1109/mwsym.2019.8700837
• 发表时间: 2019
• 期刊: 2019 IEEE MTT-S International Microwave Symposium (IMS
• 作者: Wang, Jing;Karp, Tanja;Munoz-Ferreras, Jose-Maria;Gomez-Garcia, Roberto;Li, Changzhi
• 通讯作者: Li, Changzhi

Wireless Power Transfer Sensing Approach for Milk Adulteration Detection Using Supervised Learning

使用监督学习进行牛奶掺假检测的无线功率传输传感方法

• DOI: 10.1109/rws53089.2022.9719981
• 发表时间: 2022
• 期刊: 2022 IEEE Radio and Wireless Symposium (RWS
• 作者: Montoya, Natalia Vallejo;Rodriguez, Daniel;Li, Changzhi
• 通讯作者: Li, Changzhi

Spoofing Attacks to Radar Motion Sensors with Portable RF Devices

使用便携式射频设备对雷达运动传感器进行欺骗攻击

• DOI: 10.1109/rws50353.2021.9360393
• 发表时间: 2021
• 期刊: 2021 IEEE Radio and Wireless Symposium (RWS
• 作者: Rodriguez, Daniel;Wang, Jing;Li, Changzhi
• 通讯作者: Li, Changzhi

Wind-Induced Displacement Analysis for a Traffic Light Structure Based on a Low-Cost Doppler Radar Array

基于低成本多普勒雷达阵列的交通灯结构风致位移分析

• DOI: 10.1109/tim.2021.3098380
• 发表时间: 2021
• 期刊: IEEE Transactions on Instrumentation and Measurement
• 影响因子: 5.6
• 作者: Rodrigues, Davi V.;Zuo, Delong;Li, Changzhi
• 通讯作者: Li, Changzhi