Kevin J. Webb

Characterization and imaging in optically scattering media by use of laser speckle and a variable-coherence source

We demonstrate the application of laser-speckle statistics formed by a variable-coherence source illuminating a scattering medium, for determining the scattering parameter mu;(s)>(?) of a diffusion model for the medium. Furthermore, we apply this technique to visualize laterally localized inhomogeneities embedded within a highly scattering sample.

A temperature-dependent nonlinear analytic model for AlGaN-GaN HEMTs on SiC

A temperature-dependent large-signal model for continuous-wave (CW) and pulsed-mode operation is presented and applied to aluminum gallium nitride, gallium nitride (AlGaN-GaN) high electron-mobility transistors (HEMTs) on silicon-carbide (SiC) substrates. The model includes thermal, RF dispersion, and bias-dependent capacitance model elements, and is suitable for application with a harmonic-balance simulator. Temperature- and bias-dependent on-wafer pulsed I-V and S-parameter measurements from 27/spl deg/C to 200/spl deg/C are used to examine trapping and thermal effects, and to determine temperature- and bias-dependent parameterized model coefficients for the nonlinear model. Large-signal measurement and model results are presented for 2 /spl times/ 0.35 /spl mu/m /spl times/ 125 /spl mu/m and 12 /spl times/ 0.35 /spl mu/m /spl times/ 125 /spl mu/m GaN HEMTs fabricated on SiC. The nonlinear model shows good agreement with measured CW power sweep data at an elevated temperature of 150/spl deg/C under more than 5-W power dissipation, and with measured pulsed load-pull data.

Optical diffusion tomography by iterative-coordinate-descent optimization in a Bayesian framework

Frequency-domain diffusion imaging uses the magnitude and phase of modulated light propagating through a highly scattering medium to reconstruct an image of the spatially dependent scattering or absorption coefficients in the medium. An inversion algorithm is formulated in a Bayesian framework and an efficient optimization technique is presented for calculating the maximum a posteriori image. In this framework the data are modeled as a complex Gaussian random vector with shot-noise statistics, and the unknown image is modeled as a generalized Gaussian Markov random field. The shot-noise statistics provide correct weighting for the measurement, and the generalized Gaussian Markov random field prior enhances the reconstruction quality and retains edges in the reconstruction. A localized relaxation algorithm, the iterative-coordinate-descent algorithm, is employed as a computationally efficient optimization technique. Numerical results for two-dimensional images show that the Bayesian framework with the new optimization scheme outperforms conventional approaches in both speed and reconstruction quality.

Nonlinear multigrid algorithms for Bayesian optical diffusion tomography

Optical diffusion tomography is a technique for imaging a highly scattering medium using measurements of transmitted modulated light. Reconstruction of the spatial distribution of the optical properties of the medium from such data is a difficult nonlinear inverse problem. Bayesian approaches are effective, but are computationally expensive, especially for three-dimensional (3-D) imaging. This paper presents a general nonlinear multigrid optimization technique suitable for reducing the computational burden in a range of nonquadratic optimization problems. This multigrid method is applied to compute the maximum a posteriori (MAP) estimate of the reconstructed image in the optical diffusion tomography problem. The proposed multigrid approach both dramatically reduces the required computation and improves the reconstructed image quality.

A general framework for nonlinear multigrid inversion

A variety of new imaging modalities, such as optical diffusion tomography, require the inversion of a forward problem that is modeled by the solution to a three-dimensional (3D) partial differential equation. For these applications, image reconstruction is particularly difficult because the forward problem is both nonlinear and computationally expensive to evaluate. We propose a general framework for nonlinear multigrid inversion that is applicable to a wide variety of inverse problems. The multigrid inversion algorithm results from the application of recursive multigrid techniques to the solution of optimization problems arising from inverse problems. The method works by dynamically adjusting the cost functionals at different scales so that they are consistent with, and ultimately reduce, the finest scale cost functional. In this way, the multigrid inversion algorithm efficiently computes the solution to the desired fine-scale inversion problem. Importantly, the new algorithm can greatly reduce computation because both the forward and inverse problems are more coarsely discretized at lower resolutions. An application of our method to Bayesian optical diffusion tomography with a generalized Gaussian Markov random-field image prior model shows the potential for very large computational savings. Numerical data also indicates robust convergence with a range of initialization conditions for this nonconvex optimization problem.

High-power broad-band AlGaN/GaN HEMT MMICs on SiC substrates

Broadband, high power cascode AlGaN/GaN HEMT MMIC amplifiers with high gain and power-added efficiency (PAE) have been fabricated on high-thermal conductivity SiC substrates. A cascode gain cell exhibiting 5 W of power at 8 GHz with a small signal gain of 19 dB was realized. A broadband amplifier MMIC using these cascode cells in conjunction with a lossy-match input matching network was designed, fabricated, and evaluated, showing a useful operating range of DC-8 GHz with an output power of 5-7.5 W and a PAE of 20-33% respectively. A nonuniform distributed amplifier (NDA) based on this same process yielded an output power of 3-6 W over a DC-8 GHz bandwidth with an associated PAE of 13-31%.

Subwavelength imaging with a multilayer silver film structure

A Ag/SiO2 multilayer imaging structure is shown to have subwavelength performance. Loss is the major limitation, and selection of low-loss materials and suitable operating wavelengths has a significant impact on performance. The influence of the variables is presented, and vortices are shown to exist.

Modified distorted Born iterative method with an approximate Fréchet derivative for optical diffusion tomography

In frequency-domain optical diffusion imaging, the magnitude and the phase of modulated light propagated through a highly scattering medium are used to reconstruct an image of the scattering and absorption coefficients in the medium. Although current reconstruction algorithms have been applied with some success, there are opportunities for improving both the accuracy of the reconstructions and the speed of convergence. In particular, conventional integral equation approaches such as the Born iterative method and the distorted Born iterative method can suffer from slow convergence, especially for large spatial variations in the constitutive parameters. We show that slow convergence of conventional algorithms is due to the linearized integral equations’ not being the correct Frechet derivative with respect to the absorption and scattering coefficients. The correct Frechet derivative operator is derived here. However, the Frechet derivative suffers from numerical instability because it involves gradients of both the Green’s function and the optical flux near singularities, a result of the use of near-field imaging data. To ameliorate these effects we derive an approximation to the Frechet derivative and implement it in an inversion algorithm. Simulation results show that this inversion algorithm outperforms conventional iterative methods.

Diffusive media characterization with laser speckle

The statistical properties of laser speckle with partially coherent light are related to the scattering characteristics of an optically diffuse material. A diffusion equation model is shown to yield a speckle contrast ratio that agrees well with measurements of opaque plastics of varying thicknesses. We show that partially coherent light can be used to determine material parameters for highly scattering media. Measured data for stratified materials with differing scattering properties indicate that this technique may be useful in detecting inhomogeneities.

Intrinsic noise equivalent-circuit parameters for AlGaN/GaN HEMTs

Intrinsic noise sources and their correlation in gallium-nitride high electron-mobility transistors (HEMTs) are extracted and studied. Microwave noise measurements have been performed over the frequency range of 0.8-5.8 GHz. Using measured noise and scattering parameter data, the gate and drain noise sources and their correlation are determined using an equivalent-circuit representation. This model correctly predicts the frequency-dependent noise for two devices having different gate length. Three noise mechanisms are identified in these devices, namely, those due to velocity fluctuation, gate leakage, and traps.