This PDF file contains the front matter associated with SPIE Proceedings Volume 11508, including the Title Page, Copyright information, and Table of Contents.

Rayleigh beacons used to sense the strength of the turbulence along an optical path are subject to undesirable effects on a measurement due to focal anisoplanatism. It is commonly referred to as the cone effect and manifests from unsampled turbulence at the edges of the pupil. The evaluation of focal anisoplanatism is fairly well understood for traditional Rayleigh beacon systems. However, for a dynamically ranged Rayleigh beacon system that utilizes beacon measurements from many varied finite ranges to build a tomographic profile of the turbulence strength, the understanding of focal anisoplanatism becomes all the more important and has not been thoroughly investigated. Focal anisoplanatism effects on a dynamically ranged Rayleigh beacon measurement system are presented to quantify the resultant influence on the accuracy of the beacon system’s ability to produce tomographic turbulence strength profile estimations.

Previous turbulence measurements along a near-ground, 500 m, horizontal path using two helium-neon laser beacons and a Hartmann Turbulence Sensor (HTS) yielded profiles of Cn^2 by measuring local aberrated wavefront tilts. The profiles were consistent with Cn^2 values collected along the same path by a BLS900 scintillometer. Further validation of the HTS profiling method is necessary to produce accurate optical turbulence profiles for wavefront correction. To add confidence to the HTS dual-beacon profiling method, four sonic anemometers were added along the path to indirectly measure values of Cn^2. Comparison of the independently measured data sets helps legitimize the HTS turbulence profiling method. Propagation over an equal parts grass and concrete path ensured the turbulence profile is more varied. Cn^2 profiles in this work derived from HTS data captured on 25 and 26 July 2019 agreed strongly with the collocated anemometer and BLS measurements.

Atmospheric turbulence profiles were estimated for a horizontal path based upon measurements made with a dual beacon Hartmann Turbulence Sensor (HTS) using simulation derived weighting functions. These results are compared to estimates made using a weighting functions computed from theory. These results are further compared to anemometer and scintillometer based turbulence estimates for the same path. The previously published theoretical weighting functions for this situation are based upon some presumptions of geometric optics and thus ignore both diffraction and scintillation effects. All of these weighting functions quantify how turbulence at different distances along the path contributes to the expected value of the differential tilt variances measured by the HTS. In the experiment, the HTS used a 16” Meade telescope with 700 subapertures along a 511 m path roughly 2 meters above the ground. Two HeNe lasers separated by 11 cm served as beacons, each was beam expanded to well overfill the telescope aperture. The same situation was simulated with wave optics. To create simulated weighting functions, a single (usually weak) random turbulence screen was inserted at a single plane perpendicularly to the propagation path. Light from one beacon was then numerically propagated to the telescope aperture where the tilts were computed over each subaperture and saved. This propagation was then carried out for the second beacon. This random phase screen was then inserted at a different propagation plane and this procedure was repeated. When all the desired positions along the beam path had been sampled a new random phase screen was generated and this whole procedure was repeated hundreds of times. The desired weighting functions were then generated by computing the differential tilt variance between the beacons and all pairs of horizontally separated subapertures for each path position. All equivalent subaperture separations within each range bin were then averaged together to produce weighting functions which depend on path position and subaperture separation distance. The weighting functions produced in this fashion showed some differences from the theoretical ones. They were a little weaker far from the telescope, and they showed a somewhat broadened notch where the beacons overlapped compared to the theoretical ones. The effect of these differences on the resulting turbulence profile estimates will be discussed.

For the laser beam propagation through strong and deep turbulence, a discrepancy between the wave optics simulation and existing theoretical predication has been reported. In this paper, from the perspective of short-exposure and long-exposure point spread functions and optical transfer functions, the instantaneous speckle profiles that accurately reflect turbulence features and diffraction effect are generated. their statistical behaviors, from average short exposure beam sizes, on-axis scintillation indices and to the corresponding probability density functions, are carefully examined and favorably compared with their analytical counterparts. We believe this work will be helpful in a better understanding of the optical properties of deep turbulence and wave optics simulation and bridging the gap between them.

The performance of a modern multi-frame blind deconvolution (MFBD) technique is characterized versus Strehl ratio utilizing a wave-optics simulation. Modern MFBD performs a nonlinear optimization of the likelihood of the data by varying the underlying image, constrained by positivity and support constraints. Because such algorithms are not believed to be amenable to analysis, the characterization is performed utilizing a wave-optics simulation with varying turbulence strengths, a variety of adaptive optics (AO) configurations in up-looking geometries, and diverse objects. The imaging performance of the MFBD algorithm is characterized in terms of normalized cross-correlation. The results indicate that utilizing both MFBD and low-resolution AO can provide acceptable images that are up to 3 Mv dimmer than either MFBD alone or high-resolution AO alone.

Digital holography and image sharpening have been used increasingly in recent years for wavefront sensing and imaging. Compared to conventional imaging and wavefront sensing techniques, digital holography and image sharpening require significantly fewer and simpler optical components to retrieve the complex field (i.e., both the amplitude and phase) and produce a focused image from an estimate of the phase aberrations present in the imaging system. A drawback for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high-speed imaging for target tracking systems, is the fact that digital holography and image sharpening are computationally intensive, requiring iterative virtual wavefront propagation to optimize sharpness criteria. Recently, it was shown that minimum variance wavefront prediction can be integrated with digital holography and image sharpening to reduce significantly the large number of costly sharpening iterations required to achieve near-optimal wavefront correction. This paper demonstrates further gains in computational efficiency with a new subspace sharpening method in conjunction with predictive dynamic digital holography for real-time applications. The method sharpens local regions of interest in an image plane by parallel independent wavefront correction on reduced-dimension subspaces of the complex field in a pupil plane. Results in this paper from wave-optics simulations show that the new subspace method produces results comparable to that from conventional global and local sharpening, and that subspace wavefront estimation and sharpening coupled with wavefront prediction achieves order-of-magnitude increases in processing speed.

Three-dimensional (3D) remote imaging may improve target characterization and help improve tracking and aim-point maintenance. Digital holography (DH) has been shown to be very effective in generating 3D images of objects using frequency diversity. The digital holographic nature of the process can eliminate the need for imaging lenses when the pupil-plane is used for the detection plane. In fact, this approach is the optical analog of the widely used frequencymodulation (FM) radar imaging. The current implementation of the holographic FM 3D imaging involves forming a set of holographic 2D images each at a different temporal frequency and then inverse Fourier transform to recover the actual 3D image. In this paper we present results from both laboratory and simulations of a coherent 3D holographic imaging method based on continuous frequency chirping of a laser. Laboratory 3D imaging results were obtained in both the pupilplane using a spatial heterodyne method, and in the image-plane using a temporal heterodyne method.

We evaluate a novel wavefront sensing technique using digital holography. This technique divides the aperture plane into multiple subapertures with a unique digital holographic image created in each subaperture. This reduces the complexity and allows for parallelization of the total wavefront computation. This is a key result, as the associated decrease in the processing latency will increase the available bandwidth of an adaptive optics system. We demonstrate this technique through laboratory testing and show that the wavefront sensor can accurately measure phase degradations on a sample target image.

An adaptive optical system that implements a phase conjugation algorithm designed to compensate for the effect of atmospheric turbulence the propagating laser beam is presented. The system allows compensating for the influence of atmospheric disturbances up to 200 Hz (in terms of sine). To achieve the compensation effect system operates at a frequency of 2000 Hz (in terms of fps - frames per second). Such high performance can be achieved only when using FPGA as the master control element of the system. The results of correction of disturbances obtained by using a heat fan, simulating the turbulence to frequencies of 200 Hz, are presented.

The application of precision interferometers is generally restricted to expensive and smooth high-quality surfaces. Here, we offer a route to ultimate miniaturization of interferometer by integrating beam splitter, reference mirror and light collector into a single optical element, an interference lens (iLens), which produces stable high-contrast fringes from in situ surface of paper, wood, plastic, rubber, human skin, etc. The principle of iLens interferometry has been exploited to build a variety of compact devices, such as a paper-based optical pico-balance, having 1000 times higher sensitivity and speed, when compared with a high-end seven-digit electronic balance. Furthermore, we used cloth, paper, polymer-films to readily construct broadband acoustic sensors possessing matched or higher sensitivity when compared with piezo and electromagnetic sensors. Our work opens path for affordable yet ultra-precise frugal photonic devices and universal micro-interferometers for imaging.

Image sharpening is a state-of-the-art phase-retrieval estimation algorithm used in coherent imaging that has demonstrated strong performance under various imaging conditions. However, computational overhead makes these iterative algorithms difficult to enable in real-time and dynamic applications such as high-energy laser and target-tracking systems. Recently, time-invariant, minimum-variance prediction filters have been shown to improve the convergence speed of image-sharpening algorithms during phase retrieval. The research presented here proposes a neural network with on-line adaptive learning to predict a priori wavefront errors for temporally correlated dynamic coherently imaged measurements. The method bootstraps the a priori prediction computed from past samples and updates with the phase-retrieval image-sharpening estimate at the current time step. Testing performed using wave-optics simulations demonstrates that this procedure improves the estimation of dynamic phase retrieval compared to conventional image sharpening, without being bound to a time-invariant constraint. Results also show the capacity for this approach to operate on a cycle that periodically circumvents the process of iterative conjugate-gradient phase retrieval in real-time, achieving order-of-magnitude gains in computational performance compared to current image-sharpening methods.

Event-Based Sensors (EBSs) are passive electro-optical (EO) imaging sensors which have read-out hardware that only outputs when and where temporal changes in scene brightness are detected. In the case of a static background and platform, this hardware ideally implements background clutter cancellation, leaving only moving object data to be read out. This data reduction leads to a bandwidth reduction, which is equivalent to increasing spatio-temporal resolution. This advantage can be exploited in multiple ways, using trade-offs between spatial and temporal resolution, and between spatial resolution and field-of-view. In this paper, we introduce the EBS concept and our previous experiments and analysis. We discuss important EBS properties, followed by discussion of applications where the EBS could provide significant benefit over conventional frame-based EO sensors. Finally, we present a method for analyzing EBS technology for specific applications (i.e. determine performance compared to conventional technology). This approach involves abstraction of EBS and conventional imaging technology and provides a way to determine the value of EBSs over conventional imaging technology for facilitating future EBS application development.

Hyperspectral imaging microscopy is a powerful analytical tool for spatial identification and spectral feature extraction in chemical and biological complex systems. Inspired by super-resolution microscopy, structured programmable projection coupled with spectral image reconstruction techniques is employed to improve the spatial resolution of spectroscopic imaging microscopy. In this work, a line-scan hyperspectral imaging microscope implemented with a digital light projector (DLP) was demonstrated. The DLP with a digital micromirror device (DMD) was used to project sinusoidal fringes with three angular orientations and three phase shifts. After synchronization of fringe projection, stage movement, and image acquisition, hyperspectral data sets were acquired, and image reconstruction was conducted using the nine-frame images for improved spatial resolution over the full wavelength range. This work contributes to the progress in microscale and nanoscale imaging using line-scan hyperspectral microscopy.