Abstract
Among numerous indoor localization systems proposed during the past decades, WiFi fingerprint-based localization has been one of the most attractive solutions, which is known to be free of extra infrastructure and specialized hardware. However, current WiFi fingerprinting suffers from a pivotal problem of RSS fluctuations caused by unpredictable environmental dynamics. The RSS variations lead to severe spatial ambiguity and temporal instability in RSS fingerprinting, both impairing the location accuracy. To overcome such drawbacks, we propose fingerprint spatial gradient (FSG), a more stable and distinctive form than RSS fingerprints, which exploits the spatial relationships among the RSS fingerprints of multiple neighbouring locations. As a spatially relative form, FSG is more resistant to RSS uncertainties. Based on the concept of FSG, we design novel algorithms to construct FSG on top of a general RSS fingerprint database and then propose effective FSG matching methods for location estimation. Unlike previous works, the resulting system, named ViVi, yields performance gain without the pains of introducing extra information or additional service restrictions or assuming impractical RSS models. Extensive experiments in different buildings demonstrate that ViVi achieves great performance, outperforming the best among four comparative start-of-the-art approaches by 29% in mean accuracy and 19% in 95th percentile accuracy and outweighing the worst one by 39% and 24% respectively. We envision FSG as a promising supplement and alternative to existing RSS fingerprinting for future WiFi localization.
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- H. Abdelnasser, R. Mohamed, A. Elgohary, M. F. Alzantot, H. Wang, S. Sen, R. R. Choudhury, and M. Youssef. 2016. SemanticSLAM: Using Environment Landmarks for Unsupervised Indoor Localization. IEEE Transactions on Mobile Computing 15, 7 (July 2016), 1770--1782.Google ScholarCross Ref
- M. Azizyan, I. Constandache, and R. Roy Choudhury. 2009. Surroundsense: mobile phone localization via ambience fingerprinting. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- P. Bahl and V. N Padmanabhan. 2000. RADAR: An in-building RF-based user location and tracking system. In Proceedings of the IEEE INFOCOM.Google ScholarCross Ref
- Yiqiang Chen, Qiang Yang, Jie Yin, and Xiaoyong Chai. 2006. Power-efficient access-point selection for indoor location estimation. Knowledge and Data Engineering, IEEE Transactions on 18, 7 (2006), 877--888. Google ScholarDigital Library
- W. Cheng, K. Tan, V. Omwando, J. Zhu, and P. Mohapatra. 2013. RSS-Ratio for enhancing performance of RSS-based applications. In Proceedings of the IEEE INFOCOM.Google Scholar
- Krishna Chintalapudi, Anand Padmanabha Iyer, and Venkata N. Padmanabhan. 2010. Indoor Localization Without the Pain. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Rizanne Elbakly and Moustafa Youssef. 2016. A Robust Zero-Calibration RF-based Localization System for Realistic Environments. In Proceedings of the IEEE SECON.Google ScholarDigital Library
- A. Eleryan, M. Elsabagh, and M. Youssef. 2011. Synthetic Generation of Radio Maps for Device-Free Passive Localization. In Proceedings of the IEEE GLOBECOM.Google Scholar
- Shih-Hau Fang and Tsungnan Lin. 2012. Principal component localization in indoor wlan environments. Mobile Computing, IEEE Transactions on 11, 1 (2012), 100--110. Google ScholarDigital Library
- Brian Ferris, Dieter Fox, and Neil Lawrence. 2007. WiFi-SLAM using Gaussian process latent variable models. In Proceedings of the IJCAI. Google ScholarDigital Library
- D. Han, S. Jung, M. Lee, and G. Yoon. 2014. Building a Practical Wi-Fi-Based Indoor Navigation System. IEEE Pervasive Computing 13, 2 (Apr 2014), 72--79.Google Scholar
- S. He and S. H. G. Chan. 2016. Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons. IEEE Communications Surveys Tutorials 18, 1 (Firstquarter 2016), 466--490.Google ScholarDigital Library
- Suining He, Tianyang Hu, and S.-H. Gary Chan. 2015. Contour-based Trilateration for Indoor Fingerprinting Localization. In Proceedings of the ACM SenSys. Google ScholarDigital Library
- Sebastian Hilsenbeck, Dmytro Bobkov, Georg Schroth, Robert Huitl, and Eckehard Steinbach. 2014. Graph-based Data Fusion of Pedometer and WiFi Measurements for Mobile Indoor Positioning. In Proceedings of the ACM UbiComp. Google ScholarDigital Library
- J Huang, D Millman, M Quigley, and D Stavens. 2011. Efficient, generalized indoor WiFi GraphSLAM. In Proceedings of the IEEE International Conference on Robotics and Automation.Google ScholarCross Ref
- Yifei Jiang, Yun Xiang, Xin Pan, Kun Li, Qin Lv, Robert P. Dick, Li Shang, and Michael Hannigan. 2013. Hallway Based Automatic Indoor Floorplan Construction Using Room Fingerprints. In Proceedings of the ACM UbiComp. Google ScholarDigital Library
- Junghyun Jun, Yu Gu, Long Cheng, Banghui Lu, Jun Sun, Ting Zhu, and Jianwei Niu. 2013. Social-Loc: Improving Indoor Localization with Social Sensing. In Proceedings of the ACM SenSys. Google ScholarDigital Library
- Manikanta Kotaru, Kiran Joshi, Dinesh Bharadia, and Sachin Katti. 2015. SpotFi:Decimeter Level Localization Using WiFi. In Proceedings of the ACM SIGCOMM. Google ScholarDigital Library
- Parameshwaran Krishnan, AS Krishnakumar, Wen-Hua Ju, Colin Mallows, and Sachin Ganu. 2004. A system for LEASE: Location estimation assisted by stationary emitters for indoor RF wireless networks. In Proceedings of the IEEE INFOCOM.Google ScholarCross Ref
- Liqun Li, Guobin Shen, Chunshui Zhao, Thomas Moscibroda, Jyh-Han Lin, and Feng Zhao. 2014. Experiencing and Handling the Diversity in Data Density and Environmental Locality in an Indoor Positioning Service. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, and Hong Mei. 2016. Dynamic-Music: accurate device-free indoor localization. In Proceedings of ACM UbiComp. Google ScholarDigital Library
- Hongbo Liu, Yu Gan, Jie Yang, Simon Sidhom, Yan Wang, Yingying Chen, and Fan Ye. 2012. Push the limit of WiFi based localization for smartphones. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Kaikai Liu, Xinxin Liu, and Xiaolin Li. 2013. Guoguo: Enabling Fine-grained Indoor Localization via Smartphone. In Proceedings of the ACM MobiSys. Google ScholarDigital Library
- Dimitrios Lymberopoulos, Jie Liu, Xue Yang, Romit Roy Choudhury, Vlado Handziski, and Souvik Sen. 2015. A Realistic Evaluation and Comparison of Indoor Location Technologies: Experiences and Lessons Learned. In Proceedings of ACM/IEEE IPSN. Google ScholarDigital Library
- Piotr Mirowski, Philip Whiting, Harald Steck, Ravishankar Palaniappan, Michael MacDonald, Detlef Hartmann, and TinKam Ho. 2012. Probability Kernel Regression for WiFi Localisation. Journal of Location Based Services 6, 2 (June 2012), 81--100. Google ScholarDigital Library
- Rajalakshmi Nandakumar, Krishna Kant Chintalapudi, and Venkata N. Padmanabhan. 2012. Centaur: Locating Devices in an Office Environment. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Jun Geun Park, Ben Charrow, Dorothy Curtis, Jonathan Battat, Einat Minkov, Jamey Hicks, Seth Teller, and Jonathan Ledlie. 2010. Growing an organic indoor location system. In Proceedings of the ACM MobiSys. Google ScholarDigital Library
- Anshul Rai, Krishna Kant Chintalapudi, Venkata N. Padmanabhan, and Rijurekha Sen. 2012. Zee: Zero-effort Crowdsourcing for Indoor Localization. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Souvik Sen, Bo Radunovic, Romit Roy Choudhury, and Tom Minka. 2012. You are facing the Mona Lisa: spot localization using PHY layer information. In Proceedings of the ACM MobiSys. Google ScholarDigital Library
- Guobin Shen, Zhuo Chen, Peichao Zhang, Thomas Moscibroda, and Yongguang Zhang. 2013. Walkie-Markie: indoor pathway mapping made easy. In Proceedings of the USENIX NSDI. Google ScholarDigital Library
- Y. Shu, Y. Huang, J. Zhang, P. Cou, P. Cheng, J. Chen, and K. G. Shin. 2016. Gradient-Based Fingerprinting for Indoor Localization and Tracking. IEEE Transactions on Industrial Electronics 63, 4 (April 2016), 2424--2433.Google ScholarCross Ref
- Wei Sun, Junliang Liu, Chenshu Wu, Zheng Yang, Xinglin Zhang, and Yunhao Liu. 2013. MoLoc: on distinguishing fingerprint twins. In Proceedings of the IEEE ICDCS. Google ScholarDigital Library
- Deepak Vasisht, Swarun Kumar, and Dina Katabi. 2016. Decimeter-level localization with a single WiFi access point. In Proceedings of the USENIX NSDI. Google ScholarDigital Library
- He Wang, Souvik Sen, Ahmed Elgohary, Moustafa Farid, Moustafa Youssef, and Romit Roy Choudhury. 2012. No need to war-drive: unsupervised indoor localization. In Proceedings of the ACM MobiSys. Google ScholarDigital Library
- Ju Wang, Hongbo Jiang, Jie Xiong, Kyle Jamieson, Xiaojiang Chen, Dingyi Fang, and Binbin Xie. 2016. LiFS: Low Human Effort, Device-Free Localization with Fine-Grained Subcarrier Information. In Proceedings of ACM MobiCom. Google ScholarDigital Library
- Jue Wang and Dina Katabi. 2013. Dude, Where’s My Card? RFID Positioning That Works with Multipath and Non-Line of Sight. In Proceedings of the ACM SIGCOMM. Google ScholarDigital Library
- Chenshu Wu, Zheng Yang, Chaowei Xiao, Chaofan Yang, Yunhao Liu, and Mingyan Liu. 2015. Static Power of Mobile Devices: Self-updating Radio Maps for Wireless Indoor Localization. In Proceedings of the IEEE INFOCOM.Google ScholarCross Ref
- Kaishun Wu, J Xiao, Youwen Yi, Min Gao, andL. MNi. 2012. FILA: Fine-grained indoor localization. In Proceedings of the IEEE INFOCOM.Google ScholarCross Ref
- Yaxiong Xie, Zhenjiang Li, and Mo Li. 2015. Precise power delay profiling with commodity wifi. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Jie Xiong and Kyle Jamieson. 2013. ArrayTrack: A Fine-Grained Indoor Location System.. In Proceedings of the USENIX NSDI. Google ScholarDigital Library
- Jie Xiong, Karthikeyan Sundaresan, and Kyle Jamieson. 2015. Tonetrack: Leveraging frequency-agile radios for time-based indoor wireless localization. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, and Yunhao Liu. 2015. Enhancing Wifi-based Localization with Visual Clues. In Proceedings of the ACM UbiComp. Google ScholarDigital Library
- Zheng Yang, Chenshu Wu, and Yunhao Liu. 2012. Locating in Fingerprint Space: Wireless Indoor Localization with Little Human Intervention. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
- Zheng Yang, Chenshu Wu, Zimu Zhou, Xinglin Zhang, Xu Wang, and Yunhao Liu. 2015. Mobility Increases Localizability: A Survey on Wireless Indoor Localization Using Inertial Sensors. Comput. Surveys 47, 3, Article 54 (April 2015), 34 pages. Google ScholarDigital Library
- Xuehan Ye, Yongcai Wang, Wei Hu, Lei Song, Zhaoquan Gu, and Deying Li. 2016. WarpMap: Accurate and Efficient Indoor Location by Dynamic Warping in Sequence-Type Radio-Map. In Proceedings of the IEEE SECON.Google ScholarDigital Library
- Jie Yin, Qiang Yang, and Lionel M Ni. 2008. Learning adaptive temporal radio maps for signal-strength-based location estimation. Mobile Computing, IEEE Transactions on 7, 7 (2008), 869--883. Google ScholarDigital Library
- Moustafa Youssef and Ashok Agrawala. 2008. The Horus Location Determination System. Wireless Networks 14, 3 (June 2008), 357--374. Google ScholarDigital Library
- Yuanqing Zheng, Guobin Shen, Liqun Li, Chunshui Zhao, Mo Li, and Feng Zhao. 2014. Travi-Navi: Self-deployable Indoor Navigation System. In Proceedings of the ACM MobiCom. Google ScholarDigital Library
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- Gain Without Pain: Accurate WiFi-based Localization using Fingerprint Spatial Gradient
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