Kalman filter based UWB TOA estimation via PCA

An accurate estimation of signal arrival time is considerable essential in many applications, such as in time-based wireless and indoor location systems. In this paper, we propose a time of arrival (TOA) estimation algorithm for the ultra-wideband (UWB) systems, which is based on principal component analysis (PCA) combined with Kalman filtering. In order to reduce the computational load, a predefined window is applied to the received signal samples in a frame, and then the TOA is estimated by PCA over the data within the window. The center of the window in current frame is predicted with Kalmam filtering during previous frame interval. Extensive experimental results show that, in comparison with similar existing techniques, the proposed algorithm achieves superiority measured by the normalized mean square error (NMSE) and the cumulative distribution function (CDF) of the normalized mean absolute errors of the path delay estimation.