Advanced models of targets and disturbances and related radar signal processors

The first part of the paper provides flexible and reliable stochastic models for the radar signals scattered by target and clutter sources. The models make it possible to consider any shape of autocorrelation function between consecutive pulse echoes and any probability density function for their in-phase and quadrature components. The second part of the paper revises the theory of detecting targets, with any type of probability density and autocorrelation function, embedded in a disturbance having any type of probability density and autocorrelation function. In the third part of the paper, the theory is applied to the cases in which target and/or disturbance may have a log-normal probability density for the amplitudes. Several processing schemes are suggested and corresponding detection performances evaluated. Finally, adaptive implementation schematics are suggested for some of the processors presented.