Improving the Accuracy of Person Localization with Body Area Sensor Networks: An Experimental Study

With the evolution of wireless sensor network, body area sensor networks are expected to realize many realtime monitoring applications. Localization is one of the most important amongst all contexts. In indoor environments signal strength-based localization algorithms usually fail to achieve good accuracy due to deficient antenna coverage and multi-path interference. We propose spatial diversification method, which solves this problem by combining multiple receivers in a body area sensor network to estimate the location with a higher accuracy. This method mitigates the errors caused by antenna orientations and beam forming properties. With a range free localization algorithm that we developed, we show with experimental results that with spatial diversity the localization accuracy is improved compared to using single receiver alone.