An Integrated RSS Approach for an Improved Location Estimation in Wireless Sensor Networks
Received Signal Strength (RSS) based localization represents a simple and cost effective approach in Wireless sensor networks. However, the accuracy of sensor locations is significantly deteriorated as a result the uncertainties of pair-wise RSS measurements. This paper discusses the use of the transmitter-receiver Correlation, or Link Quality Indicator (LQI), along with RSS measurements in order to increase the reliability of the measured RSS and then obtain better location estimation. The proposed technique can be efficiently adopted by sensor nodes in a completely distributed manner. In addition, this research demonstrates the performance of the RSS measurements in a typical indoor environment, including obstructions, reflectors and people in motion. The validity of the proposed RSS localization model is verified for some location estimation methods, e.g. centroid, Ecolocation and Least Square Estimator (LSE) along with the corresponding Cramer´-Rau Bound (CRB). The results of this paper showed better, and CRB comparable, localization performance by using the proposed RSS enhancement approach with these algorithms.