Surface characterization using regularity models and frequency-diverse measurements

Regularity models are parametric point-process models used to stochastically describe surfaces on which scatterers are regularly spaced to some degree. The authors develop closed form approximations to the mean power spectrum of surface measurements and show how they may be used in an optimized parameter estimation algorithm utilizing frequency-diverse measurements. The general performance limitations of such an optimization procedure suggest that such a procedure can provide sub-resolution information when used with sparse narrow-band frequency measurements