Parametric Loop Division for 3D Localization in Wireless Sensor Networks

Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m.

[1]  Li Li,et al.  Cooperative node localization using nonlinear data projection , 2009, TOSN.

[2]  Lihua Xie,et al.  Decentralized TDOA Sensor Pairing in Multihop Wireless Sensor Networks , 2013, IEEE Signal Processing Letters.

[3]  Yue Jin,et al.  Wi-Fi/MARG Integration for Indoor Pedestrian Localization , 2016, Sensors.

[4]  Luis Magdalena,et al.  An Open Localization and Local Communication Embodied Sensor , 2008, Sensors.

[5]  Aimin Jiang,et al.  Network localization using angle of arrival , 2008, 2008 IEEE International Conference on Electro/Information Technology.

[6]  Moustafa Youssef,et al.  CoSDEO 2016 Keynote: A decade later — Challenges: Device-free passive localization for wireless environments , 2016, 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops).

[7]  Rong-Hong Jan,et al.  A GPS-less, outdoor, self-positioning method for wireless sensor networks , 2007, Ad Hoc Networks.

[8]  Gulshan Kumar,et al.  An energy efficient and optimized load balanced localization method using CDS with one-hop neighbourhood and genetic algorithm in WSNs , 2017, J. Netw. Comput. Appl..

[9]  M. Tahar Kechadi,et al.  D-LPCN: A distributed least polar-angle connected node algorithm for finding the boundary of a wireless sensor network , 2017, Ad Hoc Networks.

[10]  Tanveer Ahmad,et al.  3D localization based on parametric loop division and subdivision surfaces for wireless sensor networks , 2016, 2016 25th Wireless and Optical Communication Conference (WOCC).

[11]  Jun-Hai Yong,et al.  Loop Subdivision Surface Based Progressive Interpolation , 2009, Journal of Computer Science and Technology.

[12]  Ju Wang,et al.  LCS: Compressive sensing based device-free localization for multiple targets in sensor networks , 2013, 2013 Proceedings IEEE INFOCOM.

[13]  Marco Tagliasacchi,et al.  An integrated system based on wireless sensor networks for patient monitoring, localization and tracking , 2013, Ad Hoc Networks.

[14]  Meng Wu,et al.  Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge , 2017, Sensors.

[15]  Andreas Fink,et al.  RSSI-based indoor positioning using diversity and Inertial Navigation , 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.

[16]  Stergios I. Roumeliotis,et al.  Bayesian estimation and Kalman filtering: a unified framework for mobile robot localization , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[17]  Puneet Gupta,et al.  Experimental analysis of RSSI-based location estimation in wireless sensor networks , 2008, 2008 3rd International Conference on Communication Systems Software and Middleware and Workshops (COMSWARE '08).

[18]  Geng Yang,et al.  Opportunistic broadcasting for low-power sensor networks with adaptive performance requirements , 2018, Wirel. Networks.

[19]  Xue Jun Li.  An analytical method for centroid computing and its application in wireless localization , 2013, 2013 19th IEEE International Conference on Networks (ICON).

[20]  Ilan Ziskind,et al.  Maximum likelihood localization of multiple sources by alternating projection , 1988, IEEE Trans. Acoust. Speech Signal Process..

[21]  Joe-Air Jiang,et al.  A Distributed RSS-Based Localization Using a Dynamic Circle Expanding Mechanism , 2013, IEEE Sensors Journal.

[22]  Zhan Zhao,et al.  Localization in Wireless Sensor Networks with Known Coordinate Database , 2010, EURASIP J. Wirel. Commun. Netw..

[23]  Abdelhamid Tayebi,et al.  THE APPLICATION OF RAY-TRACING TO MOBILE LOCALIZATION USING THE DIRECTION OF ARRIVAL AND RECEIVED SIGNAL STRENGTH IN MULTIPATH INDOOR ENVIRONMENTS , 2009 .

[24]  Qing Zhang,et al.  Location Estimation in Wireless Sensor Networks Using Spring-Relaxation Technique , 2010, Sensors.

[25]  Hao Jiang,et al.  A Robust Indoor Positioning System Based on the Procrustes Analysis and Weighted Extreme Learning Machine , 2016, IEEE Transactions on Wireless Communications.

[26]  Xinyu Yang,et al.  One-Dimensional Localization Algorithm Based on Signal Strength Ratio , 2009 .

[27]  Gianluca Mazzini,et al.  Localization in sensor networks with fading and mobility , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[28]  Moustafa Youssef,et al.  Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments , 2009, IEEE Transactions on Mobile Computing.

[29]  Hyunseung Choo,et al.  An interactive cluster-based MDS localization scheme for multimedia information in wireless sensor networks , 2012, Comput. Commun..

[30]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[31]  Lionel M. Ni,et al.  Fine-Grained Localization for Multiple Transceiver-Free Objects by using RF-Based Technologies , 2014, IEEE Transactions on Parallel and Distributed Systems.

[32]  Neal Patwari,et al.  2008 International Conference on Information Processing in Sensor Networks Effects of Correlated Shadowing: Connectivity, Localization, and RF Tomography , 2022 .

[33]  B. R. Badrinath,et al.  DV Based Positioning in Ad Hoc Networks , 2003, Telecommun. Syst..

[34]  Hao Jiang,et al.  A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine † , 2015, Sensors.

[35]  Yiu-Tong Chan,et al.  Exact and approximate maximum likelihood localization algorithms , 2006, IEEE Trans. Veh. Technol..

[36]  Ying Zhang,et al.  Localization from connectivity in sensor networks , 2004, IEEE Transactions on Parallel and Distributed Systems.

[37]  Tarek F. Abdelzaher,et al.  Range-free localization schemes for large scale sensor networks , 2003, MobiCom '03.

[38]  S. N. Jagadeesha,et al.  Time Of Arrival Based Localization in Wireless Sensor Networks : A Linear Approach , 2013, ArXiv.

[39]  Shen Bo,et al.  Distributed locating algorithm for wireless sensor networks-MDS-MAP(D) , 2008 .

[40]  Amanpreet Kaur,et al.  A weighted centroid localization algorithm for randomly deployed wireless sensor networks , 2017, J. King Saud Univ. Comput. Inf. Sci..

[41]  Fredrik Gustafsson,et al.  Fingerprinting Localization in Wireless Networks Based on Received-Signal-Strength Measurements: A Case Study on WiMAX Networks , 2010, IEEE Transactions on Vehicular Technology.