Location estimation of mobile user in wireless sensor network based on Unscented Kalman Filter

A strength prediction algorithm based on unscented Kalman filter (SPKF) is proposed to fuse the mobile localization estimation obtained from received signal strength in wireless sensor network. The algorithm is particularly suitable for indoor applications where the presence of furniture, objects, walls and the induced diffraction, reflection and multi-path effects. The unscented Kalman filter is used to predict the tendency of received signal strength, and cooperates with dynamic triangular location algorithm achieves an improved accuracy and provides a lower fluctuation of received signal strength than the grey prediction when mobile user is moving. It is also proved to grey prediction when mobile user is moving. It is also proved to be able to dramatically outperform and reduce the fluctuation of received signal strength when mobile user is moving.