RSSI-Based Localization Schemes for Wireless Sensor Networks Using Outlier Detection

The received signal strength indicator (RSSI) of RF signals is a cost-effective solution for distance estimation, which makes it a practical choice for localization schemes in wireless sensor networks (WSN). However, RF propagation channels in most WSN deployment environments, including dense cities and natural habitats, are commonly affected by shadowing due to obstructions caused by natural and man-made obstacles. RF signal attenuation from shadowing introduces uncharacteristically high errors in RSSI-based distance estimates, which result in large errors in RSSI-based localization schemes. This paper proposes the use of outlier detection methods for removing the effect of such disproportionately erroneous distance estimates in location estimation using RSSI. Three different localization schemes are proposed that apply outlier detection to effectively reduce localization errors in shadowed environments. Performance results of the proposed schemes are obtained using computer simulations and experimental tests.

[1]  Wan-Young Chung,et al.  An Integrated Approach for Position Estimation using RSSI in Wireless Sensor Network , 2008 .

[2]  Francisco Vázquez,et al.  Simulation Tool for the Analysis of Cooperative Localization Algorithms for Wireless Sensor Networks , 2019, Sensors.

[3]  Dharma P. Agrawal,et al.  Range-Free Localization Using Expected Hop Progress in Wireless Sensor Networks , 2009, IEEE Transactions on Parallel and Distributed Systems.

[4]  Shuigeng Zhou,et al.  Distributed Localization Using a Moving Beacon in Wireless Sensor Networks , 2008, IEEE Transactions on Parallel and Distributed Systems.

[5]  Sebastien Glaser,et al.  Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving , 2017, IEEE Transactions on Intelligent Vehicles.

[6]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[7]  Peng Li,et al.  A novel Radio Frequency Identification three-dimensional indoor positioning system based on trilateral positioning algorithm , 2016 .

[8]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[9]  Andrea Gasparri,et al.  An Interlaced Extended Kalman Filter for sensor networks localisation , 2009, Int. J. Sens. Networks.

[10]  Huarui Wu,et al.  The Accurate Location Estimation of Sensor Node Using Received Signal Strength Measurements in Large-Scale Farmland , 2018, J. Sensors.

[11]  J. Ramiro Martinez de Dios,et al.  Range-only SLAM for robot-sensor network cooperation , 2017, Autonomous Robots.

[12]  Pabitra Mohan Khilar,et al.  Geometric Constraint-Based Range-Free Localization Scheme for Wireless Sensor Networks , 2017, IEEE Sensors Journal.