Dr. Santasri R. Bose-Pillai Profile

Dr. Santasri R. Bose-Pillai

Research Assistant Professor at Air Force Institute of Technology

SPIE Involvement:

Conference Chair | Editor | Author

Publications (45)

Proceedings Article | 7 October 2024 Presentation + Paper

Image blur due to aerosols and correlation with aerosol morphology and optical properties

Patricia Byrd, Aaron Goertzen, Santasri Bose-Pillai, Kevin Keefer, Steven Fiorino, Benjamin Wilson

Proceedings Volume 13149, 131491C (2024) https://doi.org/10.1117/12.3028355

KEYWORDS: Aerosols, Modulation transfer functions, Turbulence, Imaging systems, Atmospheric particles, Scattering, Scatter measurement, Optical properties

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Proceedings Article | 7 October 2024 Presentation + Paper

An assessment of the energy balance Bowen ratio method to quantify optical turbulence in the maritime environment

Steven Fiorino, Jaclyn Schmidt, Yogendra Raut, Laura Slabaugh, Benjamin Wilson, Santasri Bose-Pillai, Kevin Keefer

Proceedings Volume 13149, 131490U (2024) https://doi.org/10.1117/12.3028339

KEYWORDS: Aerodynamics, Heat flux, Water, Sensors, Humidity, Thermal stability, Optical turbulence, Temperature metrology, Wind speed, Wind measurement

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Proceedings Article | 3 October 2023 Presentation + Paper

Quantification of surface layer turbulence using sensible heat values from energy balance versus aerodynamic methods

Steven Fiorino, Yogendra Raut, Jack McCrae, Santasri Bose-Pillai, Ben Wilson, Blaine Fourman

Proceedings Volume 12693, 126930N (2023) https://doi.org/10.1117/12.2677352

KEYWORDS: Aerodynamics, Heat flux, Humidity, Turbulence, Thermal stability, Temperature metrology, Convection, Optical surfaces, Sensors, Wind speed

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Proceedings Article | 3 October 2023 Presentation + Paper

Sonic anemometry with simulated and measured atmospheric turbulence

Jack McCrae, Santasri Bose-Pillai, Benjamin Wilson, Steven Fiorino

Proceedings Volume 12693, 126930O (2023) https://doi.org/10.1117/12.2677853

KEYWORDS: Wind speed, Turbulence, Atmospheric turbulence, Temperature metrology, Ultrasonics, Sensors, Refraction, Data modeling, Computer simulations, Ultrasound transducers

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Proceedings Article | 3 October 2023 Presentation + Paper

Attempting to understand the vertical distribution of turbulence in the surface layer from multi-camera time-lapse imagery

Benjamin Wilson, Santasri Bose-Pillai, Robert Freeman, Jack McCrae, Steven Fiorino, Kevin Keefer

Proceedings Volume 12693, 126930L (2023) https://doi.org/10.1117/12.2677937

KEYWORDS: Cameras, Turbulence, Air force, Matrices, Profiling, Instrument modeling, Feature extraction, Windows, Wind speed, Temperature metrology

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Proceedings Article | 3 October 2023 Presentation + Paper

A new approach to profiling atmospheric turbulence using a dynamically ranged Raleigh beacon system

Benjamin Wilson, Santasri Bose-Pillai, Steven Zuraski, Jack McCrae, Steven Fiorino

Proceedings Volume 12693, 126930P (2023) https://doi.org/10.1117/12.2678076

KEYWORDS: Turbulence, Wavefront sensors, Beam path, Profiling, Sensors, Atmospheric modeling, Wavefronts, Rayleigh guide stars, Atmospheric turbulence, Sensing systems

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Proceedings Article | 4 October 2022 Presentation + Paper

Comparison between SODAR and anemometer-based turbulence measurements

Jack McCrae, Santasri Bose-Pillai, Yogendra Raut, Hendrick Raquet, Benjamin Wilson, Steven Fiorino

Proceedings Volume 12239, 1223907 (2022) https://doi.org/10.1117/12.2634206

KEYWORDS: Turbulence, Backscatter, Wind measurement, Temperature metrology, Calibration, Velocity measurements, Transducers, Heat flux, Ultrasonics, Signal processing

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Proceedings Article | 4 October 2022 Presentation + Paper

Profiling atmospheric turbulence using a non-cooperative target and a camera bank and validating with sonic anemometers

Benjamin Wilson, Arjent Imeri, Santasri Bose-Pillai, Cruz Garcia, Jack McCrae, Henry Raquet, Kevin Keefer, Steven Fiorino

Proceedings Volume 12239, 1223905 (2022) https://doi.org/10.1117/12.2633717

KEYWORDS: Cameras, Turbulence, Profiling, Imaging systems, Atmospheric turbulence, 3D metrology, Spherical lenses, Sensors, Receivers, Ranging

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Proceedings Article | 30 September 2022 Presentation + Paper

Comparison of power spectrum and structure function methods to calculate turbulence parameters from sonic anemometer data

Melissa Beason, Stephen Shock, Santasri Bose-Pillai, Jack McCrae, Kevin Keefer, Benjamin Wilson

Proceedings Volume 12237, 122370G (2022) https://doi.org/10.1117/12.2632732

KEYWORDS: Turbulence, Defense and security, Meteorology

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SPIE Journal Paper | 10 September 2022 Open Access

Modeling and simulation of multispectral imaging through anisoplanatic atmospheric optical turbulence

Russell Hardie, Michael Rucci, Santasri Bose-Pillai, Richard Van Hook, Barry Karch

OE, Vol. 61, Issue 09, 093102, (September 2022) https://doi.org/10.1117/12.10.1117/1.OE.61.9.093102

KEYWORDS: Atmospheric modeling, Point spread functions, Multispectral imaging, Turbulence, Modeling and simulation, Optical transfer functions, Atmospheric optics, Optical engineering, Wave propagation, Computer simulations

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Proceedings Article | 4 August 2021 Presentation

Investigating the outer scale of turbulence with time domain processing of anemometer data

Jack McCrae, Steven Fiorino, Santasri Bose-Pillai, Benjamin Wilson

Proceedings Volume 11836, 1183604 (2021) https://doi.org/10.1117/12.2594967

KEYWORDS: Turbulence, Temperature metrology, Refraction, Spatial frequencies, Optical turbulence

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Proceedings Article | 1 August 2021 Presentation + Paper

Profiling atmospheric turbulence along a slant path using LEDs and a camera bank

Santasri Bose-Pillai, Benjamin Wilson, Jonathan Krone, Jack McCrae, Steven Fiorino

Proceedings Volume 11836, 1183601 (2021) https://doi.org/10.1117/12.2595009

KEYWORDS: Cameras, Turbulence, Light emitting diodes, Profiling, Imaging systems, Atmospheric turbulence, Motion measurement

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Proceedings Article | 8 September 2020 Presentation + Paper

Validation of HTS optical turbulence profiling via sonic anemometry

Alexander Boeckenstedt, Jack McCrae, Santasri Bose-Pillai, Benjamin Wilson, Steven Fiorino

Proceedings Volume 11508, 1150805 (2020) https://doi.org/10.1117/12.2568595

KEYWORDS: Turbulence, Profiling, Telescopes, Optical turbulence, Wavefronts, Helium neon lasers, Anisotropy, Atmospheric propagation, Wave propagation

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Proceedings Article | 22 August 2020 Presentation + Paper

Profiling atmospheric turbulence using dual-camera imagery of non-cooperative targets

Santasri Bose-Pillai, Benjamin Wilson, Jonathan Krone, Aaron Archibald, Brannon Elmore, Jack McCrae, Steven Fiorino

Proceedings Volume 11506, 115060J (2020) https://doi.org/10.1117/12.2569048

KEYWORDS: Cameras, Turbulence, Profiling, Atmospheric turbulence, Imaging systems, Motion measurement, Sensors, Receivers

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Proceedings Article | 20 August 2020 Paper

Turbulence profiling with a dual beacon Hartmann turbulence sensor using simulation derived weighting functions

Jack McCrae, Santasri Bose-Pillai, Alexander Boeckenstedt, Ben Wilson, Kevin Keefer, Steven Fiorino

Proceedings Volume 11508, 1150806 (2020) https://doi.org/10.1117/12.2568822

KEYWORDS: Turbulence, Telescopes, Device simulation, Atmospheric propagation, Sensors, Profiling, Computer simulations, Optical simulations, Atmospheric turbulence

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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.

SPIE Journal Paper | 17 July 2020 Open Access

Implications of four-dimensional weather cubes for improved cloud-free line-of-sight assessments of free-space optical communications link performance

Steven Fiorino, Santasri Bose-Pillai, Jaclyn Schmidt, Brannon Elmore, Kevin Keefer

OE, Vol. 59, Issue 08, 081808, (July 2020) https://doi.org/10.1117/12.10.1117/1.OE.59.8.081808

KEYWORDS: Free space optics, Clouds, Atmospheric optics, Receivers, Optical engineering, Data modeling, Atmospheric modeling, Climatology, Atmospheric propagation

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SPIE Journal Paper | 22 June 2020 Open Access

Measurements of optical turbulence over 149-km path

Jack McCrae, Santasri Bose-Pillai, Steven Fiorino, Aaron Archibald, Joel Meoak, Brannon Elmore, Thomas Kesler, Christopher Rice

OE, Vol. 59, Issue 08, 081806, (June 2020) https://doi.org/10.1117/12.10.1117/1.OE.59.8.081806

KEYWORDS: Turbulence, Cameras, Optical testing, Optical turbulence, Light emitting diodes, Optical engineering, Wavefronts, Ocean optics, Temperature metrology, Composites

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Proceedings Article | 14 May 2019 Presentation + Paper

Profiling atmospheric turbulence using time-lapse imagery from two cameras

Santasri Bose-Pillai, Jack McCrae, Aaron Archibald, Christopher Rice, Steven Fiorino

Proceedings Volume 11001, 1100112 (2019) https://doi.org/10.1117/12.2519022

KEYWORDS: Turbulence, Cameras, Light emitting diodes, Profiling, Atmospheric turbulence, Wavefronts, Motion estimation, Atmospheric modeling, Sensors

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Proceedings Article | 13 May 2019 Paper

Implications of 4D weather cubes for improved cloud free line of sight assessments of free space optical communications link performance

Steven Fiorino, Santasri Bose-Pillai, Jaclyn Schmidt, Brannon Elmore, Kevin Keefer

Proceedings Volume 10981, 109810S (2019) https://doi.org/10.1117/12.2522344

KEYWORDS: Clouds, Free space optics, Atmospheric propagation, Atmospheric modeling, Receivers, Atmospheric optics, Climatology, Atmospheric particles, Meteorology, Free space optical communications

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This study advances the benefits of previously reported 4D Weather Cubes towards creation of high fidelity cloud free line of sight (CFLOS) beam propagation for realistic assessment of auto-tracked/dynamically routed free space optical communication datalink concepts. 4D Weather Cubes are the product of efficient processing of large, computationally intensive, National Oceanic and Atmospheric Administration (NOAA) gridded numerical weather prediction (NWP) data coupled with embedded physical relationships governing cloud, fog, and precipitation formation to render highly realistic 4D cloud free line of sight analytical environments. The Weather Cubes accrue parameterization of optical effects and custom atmospheric resolution through implementation of the verified and validated Laser Environmental Effects Definition and Reference (LEEDR) atmospheric characterization and radiative transfer code. 4D Weather Cube analyses have recently been expanded to accurately assess Directed Energy weapons and sensor performance (probabilistic climatologies and performance forecasts) at any wavelength/frequency or spectral band in the absence of field test and employment data. The 4D Weather Cubes initialize the High Energy Laser End to End Operational Simulation (HELEEOS) propagation code, which provides a means to dynamically point the communication link. HELEEOS’ calculation of irradiance at the detector as a function of transmission, optical turbulence, and noise sources such as path radiance was the basis for comparative percentile performance binning of FSO communication bit error rates as a function of wide-ranging azimuth/elevation, earth-to-space uplinks. The aggregated, comparative bit error rate binning analyses for different regions, times of day, and seasons using a full year of data provided numerous occasions of clouds, fogs, and precipitation events, thus demonstrating the relevance of 4D Weather Cubes for adroit management of CFLOS opportunities to enhance performance analyses of point-to-point as well as evolving multilayer wireless network concepts.

SPIE Journal Paper | 20 October 2018 Open Access

Estimation of atmospheric turbulence using differential motion of extended features in time-lapse imagery

Santasri Bose-Pillai, Jack McCrae, Christopher Rice, Ryan Wood, Connor Murphy, Steven Fiorino

OE, Vol. 57, Issue 10, 104108, (October 2018) https://doi.org/10.1117/12.10.1117/1.OE.57.10.104108

KEYWORDS: Turbulence, Motion estimation, Cameras, Atmospheric turbulence, Optical engineering, Image analysis, Error analysis, Medical imaging, Clouds, Atmospheric optics

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Proceedings Article | 18 September 2018 Presentation + Paper

Global tilt removal on a Hartmann turbulence sensor

Jack McCrae, Santasri Bose-Pillai, Christopher Rice, Steven Fiorino

Proceedings Volume 10770, 107700V (2018) https://doi.org/10.1117/12.2321214

KEYWORDS: Turbulence, Sensors, Telescopes, Optics manufacturing, Atmospheric turbulence, Cameras, Statistical analysis, Numerical integration, Raster graphics, Array processing

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Proceedings Article | 18 September 2018 Presentation + Paper

Profiling of atmospheric turbulence along a path using two beacons and a Hartmann turbulence sensor

Santasri Bose-Pillai, Jack McCrae, Matthew Wilson, Andrew Back, Christopher Rice, Steven Fiorino

Proceedings Volume 10772, 107720C (2018) https://doi.org/10.1117/12.2321719

KEYWORDS: Turbulence, Profiling, Wavefronts, Atmospheric turbulence, Telescopes, Laser sources, Wavefront sensors, Atmospheric modeling

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Proceedings Article | 11 May 2018 Presentation + Paper

Characterizing atmospheric turbulence over long paths using time-lapse imagery

Santasri Bose-Pillai, Jack McCrae, Ryan Wood, Connor Murphy, Christopher Rice, Steven Fiorino

Proceedings Volume 10650, 106500A (2018) https://doi.org/10.1117/12.2305077

KEYWORDS: Turbulence, Cameras, Motion estimation, Atmospheric turbulence, Atmospheric propagation, Imaging systems, Image analysis, Detection and tracking algorithms

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SPIE Journal Paper | 24 August 2017 Open Access

Fresnel spatial filtering of quasihomogeneous sources for wave optics simulations

Milo Hyde, Santasri Bose-Pillai

OE, Vol. 56, Issue 08, 083107, (August 2017) https://doi.org/10.1117/12.10.1117/1.OE.56.8.083107

KEYWORDS: Spatial filters, Optical simulations, Phased array optics, Diffusers, Scattering, Imaging systems, Light wave propagation, Optical filters, Optical engineering, Geometrical optics

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SPIE Journal Paper | 7 February 2017 Open Access

Estimation of turbulence from time-lapse imagery

Jack McCrae, Santasri Bose-Pillai, Steven Fiorino

OE, Vol. 56, Issue 07, 071504, (February 2017) https://doi.org/10.1117/12.10.1117/1.OE.56.7.071504

KEYWORDS: Turbulence, Cameras, Optical engineering, Atmospheric turbulence, Spherical lenses, Image analysis, Wavefronts, Refractive index, Coherence (optics), Data processing

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Atmospheric turbulence parameters are estimated for an imaging path based on time-lapse imaging results. Atmospheric turbulence causes frame-to-frame shifts of the entire image as well as parts of the image. The statistics of these shifts encode information about the turbulence strength (as characterized by Cn2, the refractive index structure function constant) along the optical path. The shift variance observed is simply proportional to the variance of the tilt of the optical field averaged over the area being tracked and averaged over the camera aperture. By presuming this turbulence follows the Kolmogorov spectrum, weighting functions, which relate the turbulence strength along the path to the shifts measured, are derived. These weighting functions peak at the camera and fall to zero at the object. The larger the area observed, the more quickly the weighting function decays. One parameter we would like to estimate is r0 (the Fried parameter or atmospheric coherence diameter.) The weighting functions derived for pixel sized or larger parts of the image all fall faster than the weighting function appropriate for estimating the spherical wave r0. If we were to presume that Cn2 is constant along the path, then an estimate for r0 could be obtained for each area tracked, but since the weighting function for r0 differs substantially from that for every realizable tracked area, it can be expected that this approach would yield a poor estimate. Instead, the weighting functions for a number of different patch sizes can be combined through the Moore–Penrose pseudoinverse to create a weighting function that yields the least-squares optimal linear combination of measurements for the estimation of r0. This approach is carried out for one example and is shown to give noisy results. A modified version of this approach that creates larger patches by averaging several smaller patches together solves this noise issue. This approach can also work to estimate other atmospheric parameters.

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SPIE Journal Paper | 6 February 2017 Open Access

Simulation of anisoplanatic imaging through optical turbulence using numerical wave propagation with new validation analysis

Russell Hardie, Jonathan Power, Daniel LeMaster, Douglas Droege, Szymon Gladysz, Santasri Bose-Pillai

OE, Vol. 56, Issue 07, 071502, (February 2017) https://doi.org/10.1117/12.10.1117/1.OE.56.7.071502

KEYWORDS: Point spread functions, Cameras, Optical turbulence, Computer simulations, Wave propagation, Device simulation, Optical imaging, Turbulence, Statistical analysis, Optical engineering

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We present a numerical wave propagation method for simulating imaging of an extended scene under anisoplanatic conditions. While isoplanatic simulation is relatively common, few tools are specifically designed for simulating the imaging of extended scenes under anisoplanatic conditions. We provide a complete description of the proposed simulation tool, including the wave propagation method used. Our approach computes an array of point spread functions (PSFs) for a two-dimensional grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. The degradation includes spatially varying warping and blurring. To produce the PSF array, we generate a series of extended phase screens. Simulated point sources are numerically propagated from an array of positions on the object plane, through the phase screens, and ultimately to the focal plane of the simulated camera. Note that the optical path for each PSF will be different, and thus, pass through a different portion of the extended phase screens. These different paths give rise to a spatially varying PSF to produce anisoplanatic effects. We use a method for defining the individual phase screen statistics that we have not seen used in previous anisoplanatic simulations. We also present a validation analysis. In particular, we compare simulated outputs with the theoretical anisoplanatic tilt correlation and a derived differential tilt variance statistic. This is in addition to comparing the long- and short-exposure PSFs and isoplanatic angle. We believe this analysis represents the most thorough validation of an anisoplanatic simulation to date. The current work is also unique that we simulate and validate both constant and varying Cn2(z) profiles. Furthermore, we simulate sequences with both temporally independent and temporally correlated turbulence effects. Temporal correlation is introduced by generating even larger extended phase screens and translating this block of screens in front of the propagation area. Our validation analysis shows an excellent match between the simulation statistics and the theoretical predictions. Thus, we think this tool can be used effectively to study optical anisoplanatic turbulence and to aid in the development of image restoration methods.

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SPIE Journal Paper | 6 September 2016 Open Access

Estimation of temporal variations in path-averaged atmospheric refractive index gradient from time-lapse imagery

Santasri Basu, Jack McCrae, Steven Fiorino, Jared Przelomski

OE, Vol. 55, Issue 09, 090503, (September 2016) https://doi.org/10.1117/12.10.1117/1.OE.55.9.090503

KEYWORDS: Refractive index, Atmospheric modeling, Turbulence, Cameras, Physics, Digital cameras, Atmospheric turbulence, Motion models, Meteorology, Refraction

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Proceedings Article | 13 May 2016 Paper

Estimation of atmospheric parameters from time-lapse imagery

Jack McCrae, Santasri Basu, Steven Fiorino

Proceedings Volume 9833, 983303 (2016) https://doi.org/10.1117/12.2223986

KEYWORDS: Turbulence, Atmospheric propagation, Coherence (optics), Atmospheric turbulence, Cameras, Spherical lenses, Gold, Wavefronts, Image analysis, Atmospheric physics

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SPIE Journal Paper | 10 December 2015 Open Access

Generating partially coherent Schell-model sources using a modified phase screen approach

Milo Hyde, Santasri Basu, David Voelz, Xifeng Xiao

OE, Vol. 54, Issue 12, 120501, (December 2015) https://doi.org/10.1117/12.10.1117/1.OE.54.12.120501

KEYWORDS: Spatial light modulators, Diffraction gratings, Speckle pattern, Diffraction, Light sources, Speckle, Global system for mobile communications, Optical engineering, Cameras, Coherence (optics)

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Proceedings Article | 4 September 2015 Paper

Experimental method of generating electromagnetic Gaussian Schell-model beams

Matthew Gridley, Milo Hyde, Mark Spencer, Santasri Basu

Proceedings Volume 9617, 96170C (2015) https://doi.org/10.1117/12.2192049

KEYWORDS: Spatial light modulators, Polarization, Electromagnetism, Iris, Correlation function, Sensors, Optical simulations, Liquid crystals, Visualization, Atmospheric propagation

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Proceedings Article | 19 May 2015 Paper

Estimation of the path-averaged atmospheric refractive index structure constant from time-lapse imagery

Santasri Basu, Jack McCrae, Steven Fiorino

Proceedings Volume 9465, 94650T (2015) https://doi.org/10.1117/12.2177330

KEYWORDS: Turbulence, Refractive index, Cameras, Motion estimation, Image analysis, Atmospheric turbulence, Digital cameras, Receivers, Motion analysis, Atmospheric physics

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Proceedings Article | 3 October 2014 Paper

Examining the validity of using a Gaussian Schell model for modeling an extended beacon on a rough perfectly reflecting surface

Santasri Basu, Milo Hyde, Jack McCrae, Mark Spencer, Steven Fiorino

Proceedings Volume 9224, 92240L (2014) https://doi.org/10.1117/12.2062153

KEYWORDS: Turbulence, Scattering, Atmospheric propagation, Laser scattering, Global system for mobile communications, Speckle, Beam propagation method, Atmospheric turbulence, 3D modeling, Atmospheric modeling

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Proceedings Article | 5 September 2014 Paper

The scattering of partially coherent electromagnetic beam illumination from a statistically rough surface modeled as a perfect electrical conductor

Mark Spencer, Milo Hyde, Santasri Basu, Michael Marciniak

Proceedings Volume 9205, 92050J (2014) https://doi.org/10.1117/12.2060895

KEYWORDS: Scattering, Laser scattering, Electromagnetic scattering, Electromagnetism, Global system for mobile communications, Statistical analysis, Remote sensing, Statistical modeling, Atmospheric propagation, Polarization

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Proceedings Article | 17 May 2013 Paper

Scattering from a rough surface in presence of atmospheric turbulence

Santasri Basu, Milo Hyde, Jack McCrae, Steven Fiorino

Proceedings Volume 8732, 87320G (2013) https://doi.org/10.1117/12.2016105

KEYWORDS: Atmospheric propagation, Global system for mobile communications, Scattering, Atmospheric turbulence, Turbulence, Laser scattering, Light scattering, Spatial coherence, Atmospheric modeling, Wave propagation

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SPIE Journal Paper | 4 March 2013 Open Access

Examining the validity of using a Gaussian Schell-model source to model the scattering of a fully coherent Gaussian beam from a rough impedance surface

Santasri Basu, Milo Hyde, Salvatore Cusumano, Michael Marciniak, Steven Fiorino

OE, Vol. 52, Issue 03, 038001, (March 2013) https://doi.org/10.1117/12.10.1117/1.OE.52.3.038001

KEYWORDS: Scattering, Global system for mobile communications, Laser scattering, Gaussian beams, Statistical analysis, Adaptive optics, Optical engineering, Magnetism, Profilometers, Physics

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Proceedings Article | 18 December 2012 Paper

Scalar wave solution for the scattering of a partially coherent beam from a statistically rough metallic surface

Milo Hyde, Santasri Basu, Salvatore Cusumano, Mark Spencer

Proceedings Volume 8550, 85503A (2012) https://doi.org/10.1117/12.979947

KEYWORDS: Scattering, Light scattering, Monte Carlo methods, Laser scattering, Analytical research, Statistical analysis, Einsteinium, Solids, Optical simulations, Polarization

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SPIE Journal Paper | 10 October 2012 Open Access

Comparison of coherent and incoherent laser beam combination for tactical engagements

Noah Van Zandt, Salvatore Cusumano, Richard Bartell, Santasri Basu, Jack McCrae, Steven Fiorino

OE, Vol. 51, Issue 10, 104301, (October 2012) https://doi.org/10.1117/12.10.1117/1.OE.51.10.104301

KEYWORDS: Adaptive optics, Turbulence, Optical simulations, Error analysis, Optical engineering, Thermal blooming, Fiber lasers, Atmospheric optics, Thermal effects, Beam propagation method

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Proceedings Article | 5 May 2012 Paper

Validity of using Gaussian Schell model for extended beacon studies

Santasri Basu, Salvatore Cusumano, Milo Hyde, Michael Marciniak, Steven Fiorino

Proceedings Volume 8380, 83800E (2012) https://doi.org/10.1117/12.918946

KEYWORDS: Adaptive optics, Statistical analysis, Global system for mobile communications, Magnetism, Correlation function, Electromagnetism, Scattering, Atmospheric propagation, Atmospheric turbulence, Optical simulations

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Proceedings Article | 25 September 2007 Paper

Tracking in a ground to satellite optical link: effects due to lead-ahead and aperture mismatch

Santasri Basu, David Voelz

Proceedings Volume 6709, 670914 (2007) https://doi.org/10.1117/12.731510

KEYWORDS: Satellites, Optical tracking, Atmospheric turbulence, Optical communications, Adaptive optics, Telecommunications, Free space optical communications, Turbulence, Transmitters, Error analysis

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Proceedings Article | 7 September 2006 Paper

Estimation of beam pointing parameters using return signal statistics: atmospheric turbulence effects

Sathyanarayana Prabhu Adepu, David Voelz, Shashank Avula, Santasri Basu

Proceedings Volume 6307, 630705 (2006) https://doi.org/10.1117/12.682397

KEYWORDS: Turbulence, Atmospheric propagation, Atmospheric turbulence, Beam propagation method, Error analysis, Wave propagation, Optical simulations, Beam analyzers, Statistical analysis, Gaussian beams

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Proceedings Article | 1 September 2006 Paper

Analysis of a ground to satellite optical link with a cooperative satellite beacon

Santasri Basu, David Voelz

Proceedings Volume 6304, 63041M (2006) https://doi.org/10.1117/12.681363

KEYWORDS: Satellites, Turbulence, Optical communications, Satellite communications, Free space optical communications, Wavefronts, Atmospheric turbulence, Lead, Transmitters, Wave propagation

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Proceedings Article | 23 August 2005 Paper

Adaptive beam control based on return statistics: laboratory real-time simulation

Santasri Basu, David Voelz, Susan Chandler, Gordon Lukesh

Proceedings Volume 5895, 58950M (2005) https://doi.org/10.1117/12.618842

KEYWORDS: Error analysis, Beam controllers, Statistical analysis, Adaptive control, Sensors, Mirrors, Laser systems engineering, Control systems, Telescopes, Computer simulations

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Proceedings Article | 11 November 2004 Paper

Model-based beam control for illumination of remote objects

Susan Chandler, Gordon Lukesh, David Voelz, Santasri Basu, Jon Sjogren

Proceedings Volume 5572, (2004) https://doi.org/10.1117/12.563360

KEYWORDS: Laser systems engineering, Mirrors, Satellites, Reflectivity, Sensors, Receivers, Beam controllers, Photons, Statistical analysis, Signal detection

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Proceedings Article | 18 October 2004 Paper

Model-based beam control for illumination of remote objects, part I: theory and near real-time feasibility

Susan Chandler, Gordon Lukesh, David Voelz, Santasri Basu, Jon Sjogren

Proceedings Volume 5552, (2004) https://doi.org/10.1117/12.558742

KEYWORDS: Laser systems engineering, Satellites, Error analysis, Beam controllers, Model-based design, Receivers, Feedback control, Excel, Transmitters, Optical sensors

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Proceedings Article | 18 October 2004 Paper

Model-based beam control for illumination of remote objects, part II: laboratory testbed

Santasri Basu, David Voelz, Susan Chandler, Gordon Lukesh, Jon Sjogren

Proceedings Volume 5552, (2004) https://doi.org/10.1117/12.558746

KEYWORDS: Sensors, Mirrors, Error analysis, Statistical analysis, Signal detection, Algorithm development, Detection and tracking algorithms, Reflectivity, Target detection, Model-based design

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