Matthew E. Goda

Atmospheric turbulence simulation using liquid crystal spatial light modulators

Laser systems are finding a home in many military applications - such as Space Situational Awareness, imaging and weapons systems. With an increasing focus on programs that entail atmospheric propagations, there is a need for a cost effective method of performing laboratory proof-of-concept demonstrations. The use of one SLM (single phase screen) to model atmospheric effects has been investigated previously with promising results. However, some effects cannot be captured with a single SLM. This paper focuses on the addition of a second SLM and quantifying the results. Multiple screens will allow the user to independently control the Fried parameter, the isoplanatic angle, and Rytov Variance. The research is comprised of simulation and experiment. The simulation demonstrates the ability to accurately model atmospheric effects with two phase screens. Based on the simulation, a hardware implementation was tested in the lab. The results of this research show promise, however some issues remain. This thesis describes the experimental set-up and results based on measurement of phase and intensity of the propagated field. It was noted that while analytic results are replicated in simulation, similar results in the lab were difficult to achieve.

Quantifying surface normal estimation

An inverse algorithm for surface normal estimation from thermal polarimetric imagery was developed and used to quantify the requirements on a priori information. Building on existing knowledge that calculates the degree of linear polarization (DOLP) and the angle of polarization (AOP) for a given surface normal in a forward model (from an objects characteristics to calculation of the DOLP and AOP), this research quantifies the impact of a priori information with the development of an inverse algorithm to estimate surface normals from thermal polarimetric emissions in long-wave infrared (LWIR). The inverse algorithm assumes a polarized infrared focal plane array capturing LWIR intensity images which are then converted to Stokes vectors. Next, the DOLP and AOP are calculated from the Stokes vectors. Last, the viewing angles, θv, to the surface normals are estimated assuming perfect material information about the imaged scene. A sensitivity analysis is presented to quantitatively describe the a priori informations impact on the amount of error in the estimation of surface normals, and a bound is determined given perfect information about an object. Simulations explored the impact of surface roughness (σ) and the real component (n) of a dielectrics complex index of refraction across a range of viewing angles (θv) for a given wavelength of observation.

High-energy laser weapons: technology overview

High energy laser (HEL) weapons are ready for some of today’s most challenging military applications. For example, the Airborne Laser (ABL) program is designed to defend against Theater Ballistic Missiles in a tactical war scenario. Similarly, the Tactical High Energy Laser (THEL) program is currently testing a laser to defend against rockets and other tactical weapons. The Space Based Laser (SBL), Advanced Tactical Laser (ATL) and Large Aircraft Infrared Countermeasures (LAIRCM) programs promise even greater applications for laser weapons. This technology overview addresses both strategic and tactical roles for HEL weapons on the modern battlefield and examines current technology limited performance of weapon systems components, including various laser device types, beam control systems, atmospheric propagation, and target lethality issues. The characteristics, history, basic hardware, and fundamental performance of chemical lasers, solid state lasers and free electron lasers are summarized and compared. The elements of beam control, including the primary aperture, fast steering mirror, deformable mirrors, wavefront sensors, beacons and illuminators will be discussed with an emphasis on typical and required performance parameters. The effects of diffraction, atmospheric absorption, scattering, turbulence and thermal blooming phenomenon on irradiance at the target are described. Finally, lethality criteria and measures of weapon effectiveness are addressed. The primary purpose of the presentation is to define terminology, establish key performance parameters, and summarize technology capabilities.

Enhancing the resolution of spectral images

This research continues the development of the Model-Based Spectral Image Deconvolution (MBSID) algorithm first presented elsewhere. The deconvolution algorithm is based on statistical estimation and is used to spectrally deconvolve images collected from a spectral imaging sensor. The development of the algorithm requires only two key elements, 1) the statistics of the photon arrival and 2) an in-depth knowledge of the spectral imaging sensor. With these two elements, the MBSID algorithm can, through image post-processing, increase the spectral resolution of the images. While MBSID algorithms can be developed for any spectral imaging system, this research focuses on an algorithm developed for ASIS (AEOS Spectral Imaging Sensor), a new spectral imaging sensor installed with the 3.6m Advanced Electro-Optical System (AEOS) telescope at the Maui Space Surveillance Complex (MSSC). The primary purpose of ASIS is to take spatially resolved spectral images of space objects. The stringent requirements associated with imaging these objects, especially the low-light levels and object motion, required a sensor design with less spectral resolution than required for image analysis. However, by applying MBSID to the collected data, the sensor will be capable of achieving a much higher spectral resolution, allowing for better spectral analysis of the space object. Before the algorithm is used on data collected with ASIS, it is proven with data collected using a set-up similar to that of ASIS. The lab data successfully shows that the MBSID algorithm can improve both the spatial and spectral resolution for a collected spectral image.

Atmospheric simulation using a liquid crystal wavefront-controlling device

Test and evaluation of laser warning devices is important due to the increased use of laser devices in aerial applications. This research consists of an atmospheric aberrating system to enable in-lab testing of various detectors and sensors. This system employs laser light at 632.8nm from a Helium-Neon source and a spatial light modulator (SLM) to cause phase changes using a birefringent liquid crystal material. Measuring outgoing radiation from the SLM using a CCD targetboard and Shack-Hartmann wavefront sensor reveals an acceptable resemblance of system output to expected atmospheric theory. Over three turbulence scenarios, an error analysis reveals that turbulence data matches theory. A wave optics computer simulation is created analogous to the lab-bench design. Phase data, intensity data, and a computer simulation affirm lab-bench results so that the aberrating SLM system can be operated confidently.

Multiframe phase-diversity algorithm for active imaging

A multiframe phase-diversity algorithm for imaging through the turbulent atmosphere tailored to the statistics of coherent light is developed and presented. The problem is posed as a maximum likelihood estimation where pupil-plane intensity data and atmospheric statistics are used to regularize the inverse problem. Reconstruction results characterized by residual mean square error are presented for varying detection parameters. The resulting algorithm appears to be robust under detection noise processes and results in significant improvement of processed images.

Enhancing the resolution of spectral images from the Advanced Electro-Optical System Spectral Imaging Sensor

This research develops a model-based spectral image reconstruction (MBSIR) algorithm to reconstruct images collected from the Advanced Electro-Optical System (AEOS) Spectral Imaging Sensor (ASIS). The development of the algorithm requires two key elements: 1. the statistics of the photon arrival and 2. estimates of the spatial and spectral transfer functions. With these two elements, the MBSIR algorithm can, through image postprocessing, dramatically increase the resolution of the images as well as give insight into the performance of the imaging sensor itself. The MBSIR algorithm is designed to simultaneously improve both the spatial and spectral resolution, and is derived for the general case of a spectrally variant imaging system. While MBSIR algorithms can be developed for any spectral imaging system, this research focuses on ASIS, a new spectral imaging sensor installed with the 3.6-m AEOS telescope at the Maui Space Surveillance Complex (MSSC). The primary purpose of ASIS is to take spatially resolved spectral images of space objects. The low-light levels and object motion inherent in imaging some objects in space, such as satellites, lead to a sensor design with less spectral resolution than required for image analysis. However, by applying MBSIR to the collected data, the sensor will be capable of achieving a higher resolution, allowing for better spectral analysis. The algorithm is shown to work with simulated ASIS data and measured data from an ASIS-like sensor.

Emulating bulk turbulence with a liquid-crystal spatial light modulator

We have developed a novel system that emulates the optical effects of bulk atmospheric turbulence in a dynamic, repeatable, and accurate way without moving parts. Such turbulence-emulating systems (TES) are necessary for testing laser systems including laser weapons, free-space optical communications, and atmospheric imaging systems. Most current TESs utilize the layered turbulence model with static phase plates or diffractive optics acting as the turbulent layers. Until now, the only way to emulate bulk turbulence in a laboratory has been by creating real turbulence with a heating element and a fan contained in a miniature wind tunnel. In contrast, the TES that we developed uses phase retrieval-based wavefront control to shape a laser beam into a turbulence-distorted beam. Several important properties of the measured irradiance patterns have shown good agreement with the theoretical expectations.

Polar phase screens: a comparative analysis with other methods of random phase screen generation

Random phase screens are essential elements of simulating light propagation through turbulent media. In order to be effective, they must accurately reflect theory and be implementable by the user. This document explains and evaluates three methods of generating random phase screens: using a Fourier series upon a polar frequency grid with logarithmic spacing; using the fast Fourier transform, with its cartesian frequency grid; and using Zernike polynomials. It provides a comparison of the polar Fourier series technique with the two more common techniques (fast Fourier transform and Zernike), with the end result of giving the users enough information to choose which method best fits their needs. The evaluation criteria used are generation time (usability) and phase structure function (accuracy).

Spectral image deconvolution using sensor models

This research develops a Model-based Spectral Image Deconvolution (MBSID) algorithm based on statistical estimation to spectrally deconvolve images collected from a spectral imaging sensor. The development of the algorithm requires only two key elements, 1) the statistics of the light arrival and 2) an in-depth knowledge of the spectral imaging sensor. With these two elements, the MBSID algorithm can, through image post-processing, dramatically increase the spectral resolution of the images as well as give insight into the performance of the imaging sensor itself. While MBSID algorithms can be developed for any spectral imaging system, for this research an algorithm is developed for ASIS (AEOS Spectral Imaging Sensor), a new spectral imaging sensor installed with the 3.6m Advanced Electro-Optical System (AEOS) telescope at the Maui Space Surveillance Complex (MSSC). The primary purpose of ASIS is to take spatial and spectral images of space objects. The stringent requirements associated with imaging these objects, especially the low-light levels and object motion, required a sensor design with less spectral resolution than required for image analysis. However, by applying MBSID to the collected data, the sensor will be capable of achieving a much higher spectral resolution, allowing for better spectral analysis of the space object.