John Phillips Garcia

Snapshot imaging spectropolarimeter

We present and analyze a technique for snapshot imaging spectropolarimetry. The technique involves the combination of channeled spectropolarimetry with computed tomography imaging spectrometry (CTlS). Channeled spectropolarimetry uses sideband modulation to encode the spectral dependence of all four Stokes parameters in a single spectrum. CTIS is a snapshot imaging spectrometry method in which a computer-generated holographic disperser is employed to acquire dispersed images of the target scene, and both spatial and spectral information is reconstructed using the mathematics of computed tomography. The combination of these techniques provides the basis for a snapshot imaging complete Stokes spectropolarimeter that can be implemented with no moving parts. We review design considerations for the spectropolarimeter and present preliminary simulation results.

Figures of merit for complete Stokes polarimeter optimization

Figures of merit for optimization of a complete Stokes polarimeter based on its measurement matrix are described which are not limited in their application to cases in which four measurements are used in the determination of a single Stokes vector. Singular value decomposition and probability theory are used to investigate the behavior and significance of these figures of merit. Their use to optimize a system consisting of a rotatable retarder and fixed polarizer indicates that a retardance of 132° (approximately three-eighths wave) and retarder orientation angles of ±51.7° and ±15.1° are favorable when four measurements are used. The performance of this system is demonstrated with experimental data.

Midwave-infrared snapshot imaging spectrometer

We report results from a demonstration of a midwave-infrared, nonscanning, high-speed imaging spectrometer capable of simultaneously recording spatial and spectral data from a rapidly varying target scene. We demonstrated high-speed spectral imaging by collecting spectral and spatial snapshots of blackbody targets and combustion products. The instrument is based on computed tomography concepts and operates in a midwave-infrared band of 3.0-5.0 mum. We record raw images at a frame rate of 60 frames/s, using a 512 x 512 InSb focal-plane array. Reconstructed object cube estimates were sampled at 46 x 46 x 21 (x, y, lambda) elements, or 0.1-mum spectral sampling. Reconstructions of several objects are presented.

Lateral Diffusion Length Changes in HgCdTe Detectors in a Proton Environment

This paper presents a study of the performance degradation in a proton environment of long wavelength infrared (LWIR) HgCdTe detectors. The energy dependence of the Non-Ionizing Energy Loss (NIEL) in HgCdTe provides a framework for estimating the responsivity degradation in LWIR HgCdTe detectors due to on-orbit exposure from protons. Banded detector arrays of different detector designs were irradiated at proton energies of 7, 12, and 63 MeV. These banded detector arrays allowed insight into how the fundamental detector parameters degraded in a proton environment at the three different proton energies. Measured data demonstrated that the detector responsivity degradation at 7 MeV is 5 times larger than the degradation at 63 MeV. Comparison of the responsivity degradation at the different proton energies suggests that the atomic Columbic interaction of the protons with the HgCdTe detector is likely the primary mechanism responsible for the degradation in responsivity at proton energies below 30 MeV.

Mixed-expectation image-reconstruction technique

An iterative method of reconstructing degraded images is developed from consideration of a mixed-noise imaging situation. Both photon noise in the image itself and postdetection Gaussian noise are combined by use of the standard maximum-likelihood method to produce a mixed-expectation reconstruction technique that demonstrates good performance in the presence of both noise sources. The new algorithm is evaluated through computer simulations.

Measurements of midwave and longwave infrared polarization from water

In the largely unpolarized natural IR environment, water stands out as a notably polarized source. Water surfaces appear partially polarized in the IR through both reflection and emission. This polarization can be significant in environmental and military remote sensing applications where the water is either the intended source or possibly a false target. In this paper we show and interpret measurements in midwave and longwave IR bands. The midwave images show up to 7 percent s polarization in regions where warm objects reflect from the water. The longwave data also show s polarization in regions of sunglint, but elsewhere exhibit p polarization. Where the background is clear sky, the longwave signal is p polarized by up to 5 percent at large incidence angles.

Computational modeling of the imaging system matrix for the CTIS imaging spectrometer

Imaging systems such as the Computed Tomographic Imaging Spectrometer (CTIS) are modeled by the matrix equation g = Hf, which is the discretized form of the general imaging integral equation.. The matrix H describes the contribution to each element of the image g from each element of the hyperspectral object cube f. The vector g is the image of the spatial/spectral projections of f on a focal plane array (FPA). The matrix H is enormous, sparse and rectangular. It is extremely difficult to discretize the integral operator to obtain the matrix operator H. Normally H is constructed empirically from a series of monochromatic calibration images, which is a time consuming process. However we have been able to synthetically construct H by numerically modeling how the optical and diffractive elements in the CTIS project monochromatic point source data onto the FPA. We can evaluate a CTIS system by solving the imaging equation for f using both the empirical and synthetic H from some test data g. Comparison between the two results provides a means to evaluate and improve CTIS system calibration procedures noting that the synthetic system matrix H represents a baseline ideal system.

MWIR computed-tomography imaging spectrometer: calibration and imaging experiments

We report results of experimentation with a MWIR non-scanning, high speed imaging spectrometer capable of simultaneously recording spatial and spectral data from a rapidly varying target scene. High speed spectral imaging was demonstrated by collecting spectral and spatial snapshots of filtered blackbodies, combustion products and a coffee cup. The instrument is based on computed tomography concepts and operates in a mid-wave infrared band of 3.0 to 4.6 micrometer. Raw images were recorded at a video frame rate of 30 fps using a 160 X 120 InSb focal plane array. Reconstructions of simple objects are presented.

Extrinsic silicon photodetector characterization

A gallium doped silicon (Si:Ga) extrinsic photoconductive detector was tested for sensitivity and quickness of response. The developmental goal for this detector material was high speed operation without compromised detectivity (D*). The high speed, p-type infrared photoconductor, with photoconductive gain less than unity, was tested at 10.5 microm to determine an experimental value for the detectivity-bandwidth product of D*f* = 3.69 x 10(18)cm-Hz(3/2)/W. Subsequently a theoretical model taking into account the optical absorption profile and majority-carrier-transport processes within the detector was developed. It agreed with experimental data and corroborated the theory.

Ranging-imaging spectrometer

An imaging spectrometer that can simultaneously obtain 3-D spatial and hyperspectral data has been developed. The Ranging-Imaging Spectrometer (RIS) is based on the Computed Tomographic Imaging Spectrometer (CTIS) developed at the Optical Science Center, and the Scannerless Laser Radar (LADAR) architecture developed at Sandia National Labs. The instrument acquires hyperspectral data in a single snapshot and spatial data in a series of snapshots. The system has 29 spectral bands, 1024 range samples, and approximately 80 x 80 spatial sampling. The RIS is discussed along with analysis of test data.