An Indoor Location Algorithm Based on Taylor Series Expansion and Maximum Likelihood Estimation

Abstract

With Taylor series expansion, the effect of indoor shadowing fading is approximate to additional Gaussian errors of measured propagation distances. Further the average of multiple measurements is expected to decrease the variance of the Gaussian errors. By this means, the key issue in wireless indoor location, large shadowing fading, can be handled. Both simulations and experimental results reveal that this algorithm is effective