A Kalman Filtering Channel Estimation Method Based on State Transfer Coefficient Using Threshold Correction for UWB Systems

Abstract

Aimed at the divergence problem in the traditional Kalman Filtering (KF) channel estimation algorithm due to the inaccurate state transfer coefficient (STC), this paper proposes a novel KF channel estimation method using the STC with threshold correction. By setting a reasonable threshold, the estimation performance of STC can be greatly improved in the time-varying Ultra-Wideband (UWB) channel environment. The simulation results demonstrate that, compared with the traditional estimation methods, the proposed channel estimation method can not only significantly improve the estimation performance but also effectively restrain the traditional KF’s divergence problem.