Iterative Kalman-AR Method for Doppler Spread Estimation in Flat Fading Channels

The knowledge of Doppler spread is very important in many channel estimation (tracking) algorithms for flat fading channels. Recently, doppler spread estimators based on the profile of the power spectral density (psd) have been published. They make use of the fact that there is an abrupt change in the psd around the maximum Doppler frequency. However, this assumption is invalid in low signal-to-noise ratios (SNRs). In this paper, we introduce an iterative Kalman autoregressive (IKAR) estimator which overcomes this drawback. In doing so, we also study the excellent detection properties of the IKAR detector and demonstrate its superiority over some of the conventional detectors. The IKAR estimator performance is studied for two low SNR scenarios.