From relative azimuth to absolute location: pushing the limit of PIR sensor based localization

Pyroelectric infrared (PIR) sensors are considered to be promising devices for device-free localization due to its advantages of low cost, energy efficiency, and the immunity from multi-path fading. However, most of the existing PIR-based localization systems only utilize the binary information of PIR sensors and therefore require a large number of carefully deployed PIR sensors. A few works directly map the raw data of PIR sensors to one's location using machine learning approaches. However, these data-driven approaches require abundant training data and suffer from environmental change. In this paper, we propose PIRATES, a PIR-based device-free localization system based on the raw data of PIR sensors. The key of PIRATES is to extract a new type of location information called azimuth change. The extraction of the azimuth change relies on the physical properties of PIR sensors. Therefore, no abundant training data are needed and the system is robust to environmental change. Through experiments, we demonstrate that PIRATES can achieve higher localization accuracy than the state-of-the-art approaches. In addition, the information of the azimuth change can be easily incorporated with other information of PIR signals (e.g. amplitude) to improve the localization accuracy.

[1]  Qi Hao,et al.  Human Tracking With Wireless Distributed Pyroelectric Sensors , 2006, IEEE Sensors Journal.

[2]  Jeffrey B. Carruthers,et al.  Wireless infrared communications , 2003, Proc. IEEE.

[3]  Xiangdong Huang,et al.  An Accurate Geometrical Multi-Target Device-Free Localization Method Using Light Sensors , 2018, IEEE Sensors Journal.

[4]  Arnaud Doucet,et al.  A survey of convergence results on particle filtering methods for practitioners , 2002, IEEE Trans. Signal Process..

[5]  Mounir Ghogho,et al.  Enhanced-Range Intrusion Detection Using Pyroelectric Infrared Sensors , 2016, 2016 Sensor Signal Processing for Defence (SSPD).

[6]  Moustafa Youssef,et al.  New insights into wifi-based device-free localization , 2013, UbiComp.

[7]  Suk Lee,et al.  A pyroelectric infrared sensor-based indoor location-aware system for the smart home , 2006, IEEE Transactions on Consumer Electronics.

[8]  Fresnel lens array with spatial filtering for passive infrared motion sensor applications , 2006 .

[9]  Arjan Kuijper,et al.  Platypus: Indoor Localization and Identification through Sensing of Electric Potential Changes in Human Bodies , 2016, MobiSys.

[10]  Moe Z. Win,et al.  NLOS identification and mitigation for localization based on UWB experimental data , 2010, IEEE Journal on Selected Areas in Communications.

[11]  Neal Patwari,et al.  Radio Tomographic Imaging with Wireless Networks , 2010, IEEE Transactions on Mobile Computing.

[12]  Oliver Amft,et al.  A Distributed PIR-based Approach for Estimating People Count in Office Environments , 2012, 2012 IEEE 15th International Conference on Computational Science and Engineering.

[13]  Ashish Pandharipande,et al.  Indoor user zoning and tracking in passive infrared sensing systems , 2012, 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO).

[14]  Yoram Singer,et al.  Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers , 2000, J. Mach. Learn. Res..

[15]  Yukang Guo,et al.  Localising speech, footsteps and other sounds using resource-constrained devices , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[16]  Yunhao Liu,et al.  Widar2.0: Passive Human Tracking with a Single Wi-Fi Link , 2018, MobiSys.

[17]  Yasamin Mostofi,et al.  Magnitude-Based Angle-of-Arrival Estimation, Localization, and Target Tracking , 2018, 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[18]  Chen Wang,et al.  Low Human-Effort, Device-Free Localization with Fine-Grained Subcarrier Information , 2018, IEEE Transactions on Mobile Computing.

[19]  S. Lang Pyroelectricity: From Ancient Curiosity to Modern Imaging Tool , 2005 .

[20]  Eleni Stroulia,et al.  The Smart-Condo: Optimizing Sensor Placement for Indoor Localization , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[21]  Shaojie Tang,et al.  iLight: Indoor device-free passive tracking using wireless sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.

[22]  Xuemei Guo,et al.  Human tracking using ceiling pyroelectric infrared sensors , 2009, 2009 IEEE International Conference on Control and Automation.

[23]  Jun Li,et al.  A Cramer–Rao Lower Bound of CSI-Based Indoor Localization , 2018, IEEE Transactions on Vehicular Technology.

[24]  Rob Miller,et al.  3D Tracking via Body Radio Reflections , 2014, NSDI.

[25]  Jie Xiong,et al.  mD-Track: Leveraging Multi-Dimensionality for Passive Indoor Wi-Fi Tracking , 2018, MobiCom.

[26]  Neal Patwari,et al.  Never Use Labels: Signal Strength-Based Bayesian Device-Free Localization in Changing Environments , 2018, IEEE Transactions on Mobile Computing.

[27]  Simon J. Godsill,et al.  An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo , 2007, Proceedings of the IEEE.

[28]  Masato Miyoshi,et al.  Inverse filtering of room acoustics , 1988, IEEE Trans. Acoust. Speech Signal Process..

[29]  Jie Xiong,et al.  Phaser: enabling phased array signal processing on commodity WiFi access points , 2014, MobiCom.

[30]  A. Odon Modelling and Simulation of the Pyroelectric Detector Using MATLAB/Simulink , 2010 .

[31]  J. Krumm,et al.  Multi-camera multi-person tracking for EasyLiving , 2000, Proceedings Third IEEE International Workshop on Visual Surveillance.

[32]  Qi Hao,et al.  Preprocessing Design in Pyroelectric Infrared Sensor-Based Human-Tracking System: On Sensor Selection and Calibration , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[33]  Lei Meng,et al.  A people counting system based on head-shoulder detection and tracking in surveillance video , 2010, 2010 International Conference On Computer Design and Applications.

[34]  R. Venkatesha Prasad,et al.  PIR sensors: characterization and novel localization technique , 2015, IPSN.

[35]  Xiang Li,et al.  Dynamic-MUSIC: accurate device-free indoor localization , 2016, UbiComp.

[36]  Antonio Torralba,et al.  RF-based 3D skeletons , 2018, SIGCOMM.

[37]  Qi Hao,et al.  Distributed multiple human tracking with wireless binary pyroelectric infrared (PIR) sensor networks , 2010, 2010 IEEE Sensors.

[38]  Michael S. Brandstein,et al.  A practical methodology for speech source localization with microphone arrays , 1997, Comput. Speech Lang..

[39]  WymeerschHenk,et al.  NLOS identification and mitigation for localization based on UWB experimental data , 2010 .

[40]  Tao Yang,et al.  Robust People Detection and Tracking in a Multi-Camera Indoor Visual Surveillance System , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[41]  Paul Congdon,et al.  Avoiding multipath to revive inbuilding WiFi localization , 2013, MobiSys '13.

[42]  Upamanyu Madhow,et al.  Multiple-Target Tracking With Binary Proximity Sensors , 2011, TOSN.