Ultra Wideband Channel Estimation Based on Kalman Filter Compressed Sensing

Considering the sparsity of the channel impulse response, a novel time-varying channel estimation approach based on Kalman filter compressed sensing (KF-CS) is proposed to deal with the high sampling problem of ultra wideband (UWB) system. The direct sequence UWB signal is formulated to the mathematical model of compressed sensing after down sampling. The receiver recovers the channel impulse response by Kalman filter compressive sensing algorithm. The simulation results demonstrate that the proposed scheme can reduce the quantity of required sampling points and improve the accuracy of the estimation.