HF channel estimation using a fast transversal filter algorithm

The estimation of the sampled impulse response of a time-varying HF channel using a fast transversal filter (FTF) algorithm is studied. The latter is a computationally efficient implementation of the recursive least squares (RLS) algorithm, developed from the conventional Kalman filter. The application is that of digital data transmission. A novel stabilization technique is proposed to overcome the problem caused by the accumulation of roundoff errors, and, in addition, degree-one prediction is incorporated into the algorithm to improve the effectiveness of the estimation process. Various estimators are described, the results of a series of computer-simulation tests are presented, and the accuracies of the channel estimates given by the different systems are compared. The new FTF algorithm gives a substantially better performance than the conventional algorithm from which it is derived, and it involves only a small increase in complexity