Adaptive selection of Anchors in the Extended Kalman Filter tracking algorithm

Abstract

In many localization systems, the Mobile Node (MN) takes distance measurements with reference nodes called Anchors (ANs) in order to estimate its position. In general, the MN can obtain a better estimation when it takes measurements with multiple ANs. Unfortunately, this can lead to consume more energy and generate more traffic in the network. In this paper, we present an adaptive mechanism for the localization algorithm Extended Kalman Filter. Here, the MN decides the number of ANs to use according to measurable error indicators, which can be used to have an idea about the MN's position error. In this way, if the error indicator suggests that the position error was high in previous periods, then our Selective Extended Kalman Filter (S-EKF) will take measurements with more ANs in the next periods to improve the position accuracy.