RSSI based location estimation in wireless sensors networks

Location estimation of sensor nodes is a key component in many wireless sensor networks' (WSN) applications such as target tracking, rescue operations, disaster relief and environmental monitoring. The accuracy of the localization algorithm is a vital component to the success of the localization technique. The RSSI ranged based localization algorithm is a simple and cost effective localization technique that relies on measuring the Receive Signal Strength Indicator (RSSI) for distance estimation. In this paper we present experimental results that are carried out to analyze the sensitivity of RSSI measurements in an outdoor and indoor environment. A calibration model that characterized the RF radio channel will be derived and used for distance estimation. The validity of the estimated distance will be verified to track the position of a sensor node within an indoor environment. The results of this study reveal the feasibility of RSSI based localization algorithm in designing correct real-time position monitoring system.

[1]  Joon-Goo Park,et al.  An Enhanced Indoor Localization Algorithm Based on IEEE 802.11 WLAN Using RSSI and Multiple Parameters , 2010, 2010 Fifth International Conference on Systems and Networks Communications.

[2]  Frankie K. W. Chan,et al.  Accurate Distributed Range-Based Positioning Algorithm for Wireless Sensor Networks , 2009, IEEE Transactions on Signal Processing.

[3]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[4]  Henry L. Bertoni,et al.  Radio Propagation for Modern Wireless Systems , 1999 .

[5]  Jiannong Cao,et al.  Accurate and Energy-Efficient Range-Free Localization for Mobile Sensor Networks , 2010, IEEE Transactions on Mobile Computing.

[6]  I. J. Sorkin,et al.  A Method of Using Audio Signal-to-Noise Measurements to Obtain Criterion Contours for the Probability Scoring Model for Scoring Voice Communications Reception , 1968 .

[7]  Jean Bacon,et al.  A survey of Wireless Sensor Network technologies: research trends and middleware’s role , 2005 .

[8]  Eric A. Wan,et al.  RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers , 2009, IEEE Journal of Selected Topics in Signal Processing.

[9]  Brian D. O. Anderson,et al.  Wireless sensor network localization techniques , 2007, Comput. Networks.

[10]  Feng Dong-qin,et al.  Mean LQI and RSSI based link evaluation algorithm and the application in frequency hopping mechanism in wireless sensor networks , 2011, 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet).

[11]  Guangjie Han,et al.  A Novel Reference Node Selection Algorithm Based on Trilateration for Indoor Sensor Networks , 2007, 7th IEEE International Conference on Computer and Information Technology (CIT 2007).

[12]  Boon-Hee Soong,et al.  A New Lower Bound on Range-Free Localization Algorithms in Wireless Sensor Networks , 2011, IEEE Communications Letters.