Nonlinear tomographic reconstruction algorithms are developed for inversion of data measured in scattering experiments in which the scattered wavefields are modeled by an arbitrarily large number of terms in the Born series. The algorithms attain the form of a Volterra series of nonlinear operators, with the usual filtered backpropagation algorithm of diffraction tomography as the leading linear term.

Nonlinear tomographic reconstruction algorithms are developed for inversion of traveltime measurements in scattering experiments in which data models are derived from an arbitrarily large (possibly infinite) number of terms in the perturbation solution to the ray or eikonal equations. The algorithms attain the form of a Volterra series of nonlinear operators, with the usual linear reconstruction algorithm of traveltime tomography as the leading term. A computer simulation study is included to illustrate the performance of the algorithms for the case of scattering objects with cylindrical symmetry.

The usual propagation transform of diffraction tomography is generalized into higher-order (nonlinear) propagation transforms via use of the Born series as the data-generating model in scattering experiments. Nonlinear tomographic reconstruction algorithms are developed for inversion of scattered field data modeled up to an arbitrarily large (possibly infinite) number of terms in the Born series. A computer simulation study is included to illustrate the performance of the algorithms for the case of scattering objects with cylindrical symmetry.

Nonlinear tomographic reconstruction algorithms are developed for inversion of data measured in scattering experiments in which the complex phase of the wavefields is modeled by an arbitrarily large (possibly infinite) number of terms in the Rytov series. The algorithms attain the form of a Volterra series of nonlinear operators, with the usual filtered backpropagation algorithm of diffraction tomography as the leading linear term. A computer simulation study is included to illustrate the performance of the algorithms for the case of scattering objects with cylindrical symmetry.

We present a time domain algorithm for computation of the maximum likelihood estimate of the location of a known scattering object from wide-band scattering data acquired in a suite of scattering experiments. The algorithm consists of a three-step procedure: (1) data filtering, (2) time-domain backpropagation, and (3) coherent summation and is implemented via a number of forward and inverse Radon transforms integrated into a tomographic scheme. A computer simulation is included for illustration purposes.

We present an efficient algorithm for computation of the maximum likelihood estimate of the location of a known target from short pulse scatter data. The algorithm constitutes a three step procedure: (i) data filtering, (ii) time-domain backpropagation, and (iii) coherent summation and consists of a number of projection and backprojection operations integrated in a tomographic scheme. A computer simulation is included for illustration purposes and relevant applications in radar target identification and buried object detection are discussed.

A recently proposed approach to the inverse problem of detecting the presence and estimating the location of a known object from data collected in a set of diffraction tomographic experiments is evaluated. Experimental data are used to validate of the filtered backpropagation algorithms used, and their robustness to modeling errors and to severe limitations in the angular coverage of the tomographic data is demonstrated. A potential application to medical imaging of soft tissue is illustrated.

The problem of reconstructing the complex index of refraction of a weakly inhomogeneous scattering object from measurements of the magnitude (intensity) of the transmitted wavefields in a set of scattering experiments within the context of diffraction tomography (DT) is addressed. It is shown that high quality approximate reconstructions can be obtained from such intensity data using standard reconstruction procedures of DT. The physical basis for the success of these procedures when applied to intensity data is discussed and computer simulations are presented comparing the approximate reconstructions generated from intensity data with the optimum reconstructions generated from both the magnitude and phase of the transmitted wavefields.