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Concentrated photovoltaic (PV) technology represents a growing market in the field of terrestrial solar energy production. As the demand for renewable energy technologies increases, further importance is placed upon the modeling, design, and simulation of these systems. Given the U.S. Air Force cultural shift towards energy awareness and conservation, several concentrated PV systems have been installed on Air Force installations across the country. However, there has been a dearth of research within the Air Force devoted to understanding these systems in order to possibly improve the existing technologies. This research presents a new model for a simple concentrated PV system. This model accurately determines the steady state operating temperature as a function of the concentration factor for the optical part of the concentrated PV system, in order to calculate the optimum concentration that maximizes power output and efficiency. The dynamic thermal model derived is validated experimentally using a commercial polysilicon solar cell, and is shown to accurately predict the steady state temperature and ideal concentration factor.

Projection-based chromotomographic spectrometers are sensors that collect both spatial and spectral information with fairly simple optical as well as electronic hardware. Efforts to utilize them for remote sensing applications have met with obstacles primarily due to the fact that the impulse response of the imaging system as a function of wavelength must be know in order to reconstruct the spatial/spectral content of the scene under study. This paper reports a blind deconvolution algorithm specifically designed to reconstruct the spectrum of the scene under study as well as an estimate of the wavelength dependent atmospheric transfer function of the system. The method is tested using simulated data with realistic turbulence and noise factors in order to demonstrate its effectiveness.

Polarimetric SAR imaging is a direct-detection LADAR imaging technique designed to synthesize a large aperture made up of independent detectors all sensing a common beam of light that is polarized in nature. The aperture synthesis allows the array of detectors to achieve spatial resolution consistent with a monolithic aperture of a similar size. Unanswered questions remain about the use of this technique including how much power/aperture product is required in order to achieve a specified degree of spatial resolution. Also of concern is how much speckle averaging is necessary to overcome noise inherent in this type of synthetic aperture system. This paper addresses these questions by formulating relationships between array size, target size, laser energy per pulse, number of pulses required in averaging and the desired resolution of the system. Computer simulations are presented which demonstrate these relationships for a common resolution target.

The goal of this work is to develop an algorithm to enhance the utility of 3D FLASH laser radar sensors through accurate ranging to multiple surfaces per image pixel. Using this algorithm it will be possible to realize numerous enhancements over both traditional Gaussian mixture modeling and single surface range estimation. While traditional Gaussian mixture modeling can effectively model the received pulse, we know that the received pulse is likely corrupted due to optical aberrations from the imaging system and the medium through which it is imaging. Additionally, only identifying a single surface per pulse may result in the loss of valuable information about partially obscured surfaces. Ultimately, this algorithm in conjunction with other recent research may allow for techniques that enhance the spatial resolution of an image, improve image registration and enable the detection of obscured targets with a single pulse.