On adaptive implementation of optimum MTI in severely nonhomogeneous environments

The problem of achieving the optimum MTI (moving target indicator) detection performance in strong clutter of unknown spectrum when the set of data available for the estimation of clutter statistics is small due to a severely nonhomogeneous environment is studied. A new adaptive implementation, called the Doppler domain localized generalized likelihood ratio processor (DDL-GLR), is proposed, and its detection performance derived. It is shown that the DDL-GLR is a data-efficient implementation of the high-order optimum detector, and that it has several advantages of practical importance over other adaptive processors