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A time domain algorithm for the computation of the maximum likelihood estimate of the location of a known scattering object from wide-band scattering data obtained in a suite of scattering experiments is proposed. It consists of a three-step procedure that includes data filtering, time-domain backpropagation and coherent summation. Results confirm that the log likelihood function for estimation of the location of a known scattering object from noisy wideband scattering data can be calculated through a time-domain, filtered backpropagation algorithm.

Thermophysical algebraic invariance formulation is a robust method for interpretation of invariant features of radiometrically uncalibrated infrared (IR) imagery for ATR and site change detection. The approach focuses on internal object composition and thermophysical properties of imaged objects. Invariance to ambient scene conditions, ability to classify objects and focus on phenomena affecting long-wave IR imagery are the special features of the method. Symmetric alphastable models can adequately model all these features. Results of real IR imagery and ground truth data are presented.

The Born series was used as the data-generating model in scattering experiments to generalize the usual propagation transform of diffraction tomography into higher order propagation transforms.