ERLAK: On the Cooperative Estimation of the Real-Time RSSI Based Location and K Constant Term

Nowadays location estimation using WiFi networks in indoor environments has become a hot research topic. Challenging methods without calibration or hardware integration are essentially required for cost-effective and practical solutions. The Received Signal Strength Indicator-based localization methods offer low cost solutions. However, their propagation models are difficult to characterize due to environmental factors in indoor and multiple parameters. There are a number of works over estimation of location and pathloss exponent presented in the literature. This paper introduces a new method shortly named as ERLAK in order to estimate the K constant term using log normal channel model in addition to the location of mobile station in indoor environment. The ERLAK method has been consistently compared to the well-known Least Square and Weighted Least Square methods. It achieves the least errors in distance estimations compared to the classical methods on especially critical measurement points. It remarkably accomplishes less than 5 m mean errors for distance estimation results particularly when signal is received from all of the access points.