A Fusion Approach of RSSI and LQI for Indoor Localization System Using Adaptive Smoothers

Due to the ease of development and inexpensiveness, indoor localization systems are getting a significant attention but, with recent advancement in context and location aware technologies, the solutions for indoor tracking and localization had become more critical. Ranging methods play a basic role in the localization system, in which received signal strength indicator- (RSSI-) based ranging technique gets the most attraction. To predict the position of an unknown node, RSSI measurement is an easy and reliable method for distance estimation. In indoor environments, the accuracy of the RSSI-based localization method is affected by strong variation, specially often containing substantial amounts of metal and other such reflective materials that affect the propagation of radio-frequency signals in nontrivial ways, causing multipath effects, dead spots, noise, and interference. This paper proposes an adaptive smoother based location and tracking algorithm for indoor positioning by making fusion of RSSI and link quality indicator (LQI), which is particularly well suited to support context aware computing. The experimental results showed that the proposed mathematical method can reduce the average error around 25%, and it is always better than the other existing interference avoidance algorithms.

[1]  Marco Zuniga,et al.  Analyzing the transitional region in low power wireless links , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[2]  JongSuk Choi,et al.  Indoor Mobile Localization System and Stabilization of Localization Performance using Pre-filtering , 2008 .

[3]  Hyun Myung,et al.  Indoor localization using particle filter and map-based NLOS ranging model , 2011, 2011 IEEE International Conference on Robotics and Automation.

[4]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[5]  Andreas Fink,et al.  RSSI-based indoor localization using antenna diversity and plausibility filter , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[6]  C. Regazzoni,et al.  A STATISTICAL MODELLING BASED LOCATION DETERMINATION METHOD USING FUSION TECHNIQUE IN WLAN , 2005 .

[7]  Joon-Goo Park,et al.  On-Line Ranging for Mobile Objects Using ZIGBEE RSSI Measurement , 2008, 2008 Third International Conference on Pervasive Computing and Applications.

[8]  Michael Beigl,et al.  Using fine-grained infrared positioning to support the surface-based activities of mobile users , 2005, 25th IEEE International Conference on Distributed Computing Systems Workshops.

[9]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[10]  Gergely V. Záruba,et al.  A Bayesian sampling approach to in-door localization of wireless devices using received signal strength indication , 2005, Third IEEE International Conference on Pervasive Computing and Communications.

[11]  Tae Young Choi,et al.  Enhanced ranging using adaptive filter of ZIGBEE RSSI and LQI measurement , 2008, iiWAS.

[12]  Pau Closas,et al.  Bayesian filters for indoor localization using wireless sensor networks , 2010, 2010 5th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC).

[13]  Hiroyuki Morikawa,et al.  DOLPHIN: an autonomous indoor positioning system in ubiquitous computing environment , 2003, Proceedings IEEE Workshop on Software Technologies for Future Embedded Systems. WSTFES 2003.

[14]  J.-E. Berg,et al.  Path loss and fading models for microcells at 900 MHz , 1992, [1992 Proceedings] Vehicular Technology Society 42nd VTS Conference - Frontiers of Technology.

[15]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).