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. >

[1]  Norman Morrison,et al.  Introduction to Sequential Smoothing and Prediction , 1969 .

[2]  A. P. Clark,et al.  Near-maximum-likelihood detectors for voiceband channels , 1987 .

[3]  A. P. Clark,et al.  Adaptive Detectors for Digital Modems , 1989 .

[4]  M. Morf,et al.  Ladder forms for identification and speech processing , 1977, 1977 IEEE Conference on Decision and Control including the 16th Symposium on Adaptive Processes and A Special Symposium on Fuzzy Set Theory and Applications.

[5]  C. C. Watterson,et al.  An ionospheric channel simulator , 1969 .

[6]  T. Kailath,et al.  Fast, recursive-least-squares transversal filters for adaptive filtering , 1984 .

[7]  Thomas Kailath,et al.  Windowed fast transversal filters adaptive algorithms with normalization , 1985, IEEE Trans. Acoust. Speech Signal Process..

[8]  George Carayannis,et al.  A fast sequential algorithm for least-squares filtering and prediction , 1983 .

[9]  M. Morf,et al.  Recursive least squares ladder estimation algorithms , 1981 .

[10]  L. Ljung,et al.  Fast calculation of gain matrices for recursive estimation schemes , 1978 .

[11]  C. C. Watterson,et al.  Experimental Confirmation of an HF Channel Model , 1970 .

[12]  Lennart Ljung,et al.  Application of Fast Kalman Estimation to Adaptive Equalization , 1978, IEEE Trans. Commun..

[13]  G. A. Richards Implementation of Kalman filters for process identification , 1983 .

[14]  S. Hariharan Channel estimators for HF radio links , 1988 .

[15]  S. F. Hau,et al.  Adaptive adjustment of receiver for distorted digital signals , 1984 .

[16]  Dirk T. M. Slock,et al.  Numerically stable fast recursive least-squares transversal filters , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[17]  Adrian P. Clark,et al.  Assessment of Kalman-filter channel estimators for an HF radio link , 1986 .

[18]  John M. Cioffi,et al.  Limited-precision effects in adaptive filtering , 1987 .

[19]  S. Thomas Alexander,et al.  Adaptive Signal Processing , 1986, Texts and Monographs in Computer Science.

[20]  A. P. Clark,et al.  Fast start-up channel estimation , 1984 .

[21]  John G. Proakis,et al.  Digital Communications , 1983 .

[22]  A. P. Clark,et al.  Channel estimation for an HF radio link , 1981 .

[23]  S. T. Alexander,et al.  Adaptive Signal Processing: Theory and Applications , 1986 .

[24]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .