Design of a Practical WSN Based Fingerprint Localization System

Fingerprint positioning technology is among the most promising choices for seamless localization and is anticipated to be the future of seamless-locating services. The convenience of deployment and the high density signal source of wireless sensor networks (WSN) make them an ideal infrastructure for fingerprint positioning. In related researches, most WSN based fingerprint positioning systems are experimental demos that focus on the algorithm effectiveness and ignore the system reliability. This work proposes a practical WSN based fingerprint localization system. The system covers both indoor and outdoor scenarios and fulfills the demand for seamless localization. This paper work presents four measures that improve fault tolerance and system efficiency: a traffic regulation based radiomap (TRRM) establishing method, a full-overlapping clustering strategy, an adaptive feature space (AFS) algorithm, and a praxeological tracking algorithm. The proposed system is verified by hardware experiments on smart phones. Positioning accuracy is within 5 m in pedestrian tests and 10 m in driving tests.

[1]  Yang Lei,et al.  Situation and development tendency of indoor positioning , 2013, China Communications.

[2]  Shiwen Mao,et al.  DeepML: Deep LSTM for Indoor Localization with Smartphone Magnetic and Light Sensors , 2018, 2018 IEEE International Conference on Communications (ICC).

[3]  Chang Liu,et al.  Reliable and Cooperative Target Tracking Based on WSN and WiFi in Indoor Wireless Networks , 2018, IEEE Access.

[4]  Shih-Hau Fang,et al.  Indoor Location System Based on Discriminant-Adaptive Neural Network in IEEE 802.11 Environments , 2008, IEEE Transactions on Neural Networks.

[5]  Lijun Chen,et al.  Fingerprint localisation algorithm for noisy wireless sensor network based on multi-objective evolutionary model , 2017, IET Commun..

[6]  Deyue Zou,et al.  A Testbed of Performance Evaluation for Fingerprint Based WLAN Positioning System , 2016, KSII Trans. Internet Inf. Syst..

[7]  Shih-Hau Fang,et al.  A Novel Algorithm for Multipath Fingerprinting in Indoor WLAN Environments , 2008, IEEE Transactions on Wireless Communications.

[8]  Lijun Chen,et al.  Multi-channel fingerprint localisation algorithm for wireless sensor network in multipath environment , 2017, IET Commun..

[9]  Lijun Chen,et al.  Optimal weighted K-nearest neighbour algorithm for wireless sensor network fingerprint localisation in noisy environment , 2018, IET Commun..

[10]  Shueng-Han Gary Chan,et al.  Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons , 2016, IEEE Communications Surveys & Tutorials.

[11]  Jun Tian,et al.  Power delay profile based indoor fingerprinting localization system , 2016, 2016 18th International Conference on Advanced Communication Technology (ICACT).

[12]  Konstantinos N. Plataniotis,et al.  Kernel-Based Positioning in Wireless Local Area Networks , 2007, IEEE Transactions on Mobile Computing.

[13]  Marco Di Felice,et al.  WI-LO: Wireless indoor localization through multi-source radio fingerprinting , 2018, 2018 10th International Conference on Communication Systems & Networks (COMSNETS).

[14]  Ai Chen,et al.  SparseLoc: Indoor Localization Using Sparse Representation , 2017, IEEE Access.

[15]  Lijun Chen,et al.  Noise-aware fingerprint localization algorithm for wireless sensor network based on adaptive fingerprint Kalman filter , 2017, Comput. Networks.

[16]  Peter Sincak,et al.  Phone Application for Indoor Localization Based on Ble Signal Fingerprint , 2018, 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS).

[17]  Min Zhang,et al.  A Fingerprint Localization Method Based on Weighted KNN Algorithm , 2018, 2018 IEEE 18th International Conference on Communication Technology (ICCT).

[18]  P. Sooraksa,et al.  Soft-clustering Technique for Fingerprint-based Localization , 2018, Sensors and Materials.

[19]  Ridha Bouallegue,et al.  Adaptive Neuro-Fuzzy Location Indicator in Wireless Sensor Networks , 2017, Wirel. Pers. Commun..

[20]  Shiwen Mao,et al.  BiLoc: Bi-Modal Deep Learning for Indoor Localization With Commodity 5GHz WiFi , 2017, IEEE Access.

[21]  Santiago Mazuelas,et al.  Robust Indoor Positioning Provided by Real-Time RSSI Values in Unmodified WLAN Networks , 2009, IEEE Journal of Selected Topics in Signal Processing.

[22]  Xinbing Wang,et al.  Temporal correlation of the RSS improves accuracy of fingerprinting localization , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[23]  Fernando Seco Granja,et al.  Indoor Positioning Using Efficient Map Matching, RSS Measurements, and an Improved Motion Model , 2015, IEEE Transactions on Vehicular Technology.

[24]  Xinbing Wang,et al.  Improve Accuracy of Fingerprinting Localization with Temporal Correlation of the RSS , 2018, IEEE Transactions on Mobile Computing.

[25]  S. Y. Cho.  Localization of the arbitrary deployed APs for indoor wireless location-based applications , 2010, IEEE Transactions on Consumer Electronics.

[26]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[27]  Matt W. Mutka,et al.  CRISP: cooperation among smartphones to improve indoor position information , 2015, Wireless Networks.

[28]  Ming-Hui Jin,et al.  Intelligent Fusion of Wi-Fi and Inertial Sensor-Based Positioning Systems for Indoor Pedestrian Navigation , 2014, IEEE Sensors Journal.

[29]  Haixia Wang,et al.  Received Signal Strength Based Indoor Positioning Using a Random Vector Functional Link Network , 2018, IEEE Transactions on Industrial Informatics.

[30]  Xiangyu Wang,et al.  Deep Convolutional Neural Networks for Indoor Localization with CSI Images , 2020, IEEE Transactions on Network Science and Engineering.

[31]  Shiwen Mao,et al.  CSI-Based Fingerprinting for Indoor Localization: A Deep Learning Approach , 2016, IEEE Transactions on Vehicular Technology.

[32]  Deyue Zou,et al.  Toward Ubiquitous LBS: Multi-Radio Localization and Seamless Positioning , 2016, IEEE Wireless Communications.

[33]  Shahrokh Valaee,et al.  Orientation-aware indoor localization using affinity propagation and compressive sensing , 2009, 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[34]  K.J.R. Liu,et al.  Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs , 2005, IEEE Signal Processing Magazine.

[35]  José Sérgio da Rocha Neto,et al.  WSN integrated to a virtual instrument for partial discharges detection and localization , 2018, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[36]  Majid Ahmadi,et al.  Robust indoor positioning using differential wi-fi access points , 2010, IEEE Transactions on Consumer Electronics.

[37]  Monica Nicoli,et al.  A Jump Markov Particle Filter for Localization of Moving Terminals in Multipath Indoor Scenarios , 2008, IEEE Transactions on Signal Processing.

[38]  Shiwen Mao,et al.  CSI Phase Fingerprinting for Indoor Localization With a Deep Learning Approach , 2016, IEEE Internet of Things Journal.

[39]  Shih-Hau Fang,et al.  Cooperative multi-radio localization in heterogeneous wireless networks , 2010, IEEE Transactions on Wireless Communications.