The maximum entropy method and its application to clutter cancellation

Two high resolution techniques for spectral estimation of random processes are described. The estimate is obtained from samples of the autocorrelation function or directly from samples of the process. These techniques are based on the Maximum Entropy Method (MEM). After a review of the main points of this method, an application to radar system is shown in detail. First, the estimation of clutter spectrum is considered; then, this estimate is exploited to shape a filter for clutter cancellation and target echo enhancement. The processing algorithm is an adaptive one, and its performances are evaluated, by means of computer simulation, in term of Improvement Factor and speed of adaptation.

[1]  Irving S. Reed,et al.  Optimum Processing of Unequally Spaced Radar Pulse Trains for Clutter Rejection , 1968, IEEE Transactions on Aerospace and Electronic Systems.

[2]  A. Papoulis.  Maximum entropy and spectral estimation: A review , 1981 .

[3]  H. Akaike.  Fitting autoregressive models for prediction , 1969 .

[4]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[5]  S. Haykin,et al.  Computer simulation study of a radar Doppler processor using the maximum-entropy method , 1980 .

[6]  S.M. Kay,et al.  Spectrum analysis—A modern perspective , 1981, Proceedings of the IEEE.

[7]  I. Reed,et al.  Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.