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At least 307 records · Page 17

Digital Image Correlation Techniques Applied to Large Scale Rocket Engine Testing

Rocket engine hot-fire ground testing is necessary to understand component performance, reliability and engine system interactions during development. The J-2X upper stage engine completed a series of developmental hot-fire tests that derived performance of the engine and components, validated analytical models and provided the necessary data to identify where design changes, process improvements and technology development were needed. The J-2X development engines were heavily instrumented to provide the data necessary to support these activities which enabled the team to investigate any anomalies experienced during the test program. This paper describes the development of an optical digital image correlation technique to augment the data provided by traditional strain gauges which are prone to debonding at elevated temperatures and limited to localized measurements. The feasibility of this optical measurement system was demonstrated during full scale hot-fire testing of J-2X, during which a digital image correlation system, incorporating a pair of high speed cameras to measure three-dimensional, real-time displacements and strains was installed and operated under the extreme environments present on the test stand. The camera and facility setup, pre-test calibrations, data collection, hot-fire test data collection and post-test analysis and results are presented in this paper.

Gradl, Paul R.↗

Experimental and Numerical Investigation of Air Radiation in Superorbital Expanding Flow

To investigate air radiation in expanding flows and provide experimental data for validating associated computational models, experiments were conducted in the X2 expansion tunnel facility at the Centre for Hypersonics of the University of Queensland. A 54 turning angle wedge model was employed to generate steady expanding flows with in flow total enthalpies of 50.7, 63.4 and 75.4 MJkg. VUV spectra from 118 to 180 nm were acquired across the wedge at three equispaced distances away from the top of the model, as well as through its top surface. High speed filtered images were also obtained by coupling a Shimadzu 1 MHz high speed camera to a bandpass filter to obtain calibrated images of the 777 nm oxygen triplet. Both the across-wedge VUV spectra and filtered images of the 777 nm atomic oxygen were compared with NEQAIR simulations, which were performed using flow field data from two-dimensional CFD simulations with two-temperature 11-species air chemistry utilizing the in-house Navier-Stokes flow solver Eilmer3. Data extracted from consecutive frames of the filtered high speed images confirmed up to 8 s of available test time for the flow conditions tested. For the strongly radiating 149 and 174 nm atomic nitrogen lines, large disagreement between experimental data and NEQAIR predictions can be observed from the start of the expansion fan where the electron-ion recombination process commences. The spatial extent, or spans of the radiance profiles of the 149 and 174 nm N lines are significantly under predicted by NEQAIR, and are very close to those of N, N+ and electron number density profiles, which follow that of flow density. The electron-ion recombination process is proposed as the main reason for these discrepancies. The comparisons between NEQAIR simulations and filtered images of the 777 nm oxygen triplet show good agreement in the post-shock compression region and the start of the expansion fan for the 63.4 MJkg condition, but with up to a factor of three over prediction by NEQAIR further downstream, which is attributed to electron-impact excitation. Similar trends are found with the 75.4 MJkg condition, with reduced level of agreement in the compression region, which can be due to uncertainties in inflow condition.

Earth entry↗

Experimental and Numerical Investigation of Air Radiation in Superorbital Expanding Flow

To investigate air radiation in expanding flows and provide experimental data for validating associated computational models, experiments were conducted in the X2 expansion tunnel facility at the Centre for Hypersonics of the University of Queensland. A 54deg turning angle wedge model was employed to generate steady expanding flows with in flow total enthalpies of 50.7, 63.4 and 75.4 MJ/kg. VUV spectra from 118 to 180 nm were acquired across the wedge at three equispaced distances away from the top of the model, as well as through its top surface. High speed filtered images were also obtained by coupling a Shimadzu 1 MHz high speed camera to a bandpass filter to obtain calibrated images of the 777 nm oxygen triplet. Both the across-wedge VUV spectra and filtered images of the 777 nm atomic oxygen were compared with NEQAIR simulations, which were performed using flow field data from two-dimensional CFD simulations with two-temperature 11-species air chemistry utilising the in-house Navier-Stokes flow solver Eilmer3. Data extracted from consecutive frames of the filtered high speed images confirmed up to 8 s of available test time for the flow conditions tested. For the strongly radiating 149 and 174 nm atomic nitrogen lines, large disagreement between experimental data and NEQAIR predictions can be observed from the start of the expansion fan where the electron-ion recombination process commences. The spatial extent, or spans of the radiance profiles of the 149 and 174 nm N lines are significantly underpredicted by NEQAIR, and are very close to those of N, N+ and electron number density profiles, which follow that of flow density. The electron-ion recombination process is proposed as the main reason for these discrepancies. The comparisons between NEQAIR simulations and filtered images of the 777 nm oxygen triplet show good agreement in the post-shock compression region and the start of the expansion fan for the 63.4 MJ/kg condition, but with up to a factor of three overprediction by NEQAIR further downstream, which is attributed to electron-impact excitation. Similar trends are found with the 75.4 MJ/kg condition, with reduced level of agreement in the compression region, which can be due to uncertainties in inflow condition.

expansion tube↗

Ultra-Stable Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (5STAR)

The Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) combines airborne sun tracking and sky scanning with diffraction spectroscopy to improve knowledge of atmospheric constituents and their links to airpollution and climate. Direct beam hyperspectral measurement of optical depth improves retrievals of gas constituentsand determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution.Hyperspectral cloud-transmitted radiance measurements enable the retrieval of cloud properties from below clouds.These measurements tighten the closure between satellite and ground-based measurements. 4STAR incorporates amodular sun-tracking sky-scanning optical head with optical fiber signal transmission to rack mounted spectrometers,permitting miniaturization of the external optical tracking head, and future detector evolution.4STAR has supported a broad range of flight experiments since it was first flown in 2010. This experience provides thebasis for a series of improvements directed toward reducing measurement uncertainty and calibration complexity, andexpanding future measurement capabilities, to be incorporated into a new 5STAR instrument. A 9-channel photodioderadiometer with AERONET-matched bandpass filters will be incorporated to improve calibration stability. A wide dynamic range tracking camera will provide a high precision solar position tracking signal as well as an image of sky conditions around the solar axis. An ultrasonic window cleaning system design will be tested. A UV spectrometer tailored for formaldehyde and SO2 gas retrievals will be added to the spectrometer enclosure. Finally, expansion capability for a 4 channel polarized radiometer to measure the Stokes polarization vector of sky light will be incorporated. This paper presents initial progress on this next-generation 5STAR instrument.

atmosphere↗

A detailed analysis of Mariner nine TV navigation data.

Mariner 9 data analysis showed a good performance of the Mars probe planetary approach navigation systems and a good agreement between measured and predicted probe-approach characteristics. It was found that all operations were completed on time and that the calibration of the instruments and the observation of a greater-than-planned number of stars resulted in a higher-than-expected measurement accuracy. The key instruments of the Mariner were TV cameras taking pictures of Phobos and Deimos against a background of stars, calibrated sun and star sensors, and a scan platform. The error models used for optical navigation system elements, the calibration of the scan platform and of the TV cameras, and the image detection and location techniques are discussed in detail.

Breckenridge, W. G.↗

The Hubble Space Telescope extragalactic distance scale key project. 2: Photometry of WFC images of M81

The Extragalactic Distance Scale (H(sub o)) Key Project for Hubble Space Telescope (HST) aims to employ the Cepheid period-luminosity (P-L) relation to measure galaxy distances out as far as the Virgo Cluster. The vital steps in this program are (1) to obtain precise photometry of stellar images from the Wide Field Camera (WFC) exposures of selected galaxies, and (2) to calibrate this photometry to obtain reliable distances to these galaxies from the Cepheid P-L relation. We have used the DAOPHOT II and ALLFRAME programs to determine 28 instrumental magnitudes -- 22 of F555W (of about V) and six of F785LP (of about I) -- of all stars brighter than V of about 25 in each of two 2.56 arcmin x 2.56 arcmin WFC fields of M81. The reductions use a varying point-spread function to account for the field effects in the WFC optics and yield instrumental magnitudes with single epoch precision ranging from 0.09 to 0.24 mag, at V of about 21.8 to 23.8 -- the magnitude range of the 30 Cepheids that we have now identified in M81. For brighter stars (V of about 22), single epoch magnitudes are precise to 0.09 mag. The photometric calibration onto the Johnson V and Kron-Cousins I systems was determined from independent ground-based CCD observing at the Canada-France-Hawaii Telescope (CFHT) 3.6 m (confirmed by the Kitt Peak National Observatory (KPNO) 4.0 m) and from the Palomar 5.0 m (using the wide-field COSMIC camera) and 1.5 m telescopes. Secondary standards, taken from the COSMIC and CFHT frames, were established in each of the WFC fields in V and I, allowing a direct transformation from ALLFRAME magnitudes to calibrated V and I magnitudes, giving mean V of about 23 magnitudes accurate to of about +/- 0.1 mag. The stellar populations in M81 have been analyzed in terms of the luminosity functions and color magnitude diagrams (CMD) derived from these data, from which we identify numerous supergiants, and a CMD morphology similar to M33.

Hughes, Shaun M. G.↗

Full calibration of the tomographic redshift distribution from the HSC PDR3 Shape Catalog with DESI

The calibration of tomographic redshift distributionsis essential for cosmological analysis of weak lensing data.In this work, we calibrate all four tomographic bins of the Hyper Suprime Camera (HSC) weak lensing catalog with the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 and 2 using the clustering redshifts technique. We include z > 1.2 redshift sources such as emission line galaxies (ELG) and quasars (QSO) sources in our calibration, which were not available in the previous HSC calibration (Rau et al. (2022), Mon. Not. Roy. Astron. Soc. 524 (2023) 5109), allowing a complete calibration of all the redshift bins. We find the first tomographic bin exhibits a small shift towards low redshifts. The second bin is in good agreement with the photometric calibration, while third and fourth bin exhibit a shift towards higher redshifts. However, these shifts are considerably smaller than the shifts obtained in the HSC Year 3 cosmic shear analyses. We evaluate the impact of galaxy bias and magnification effects from all the samples on the measurements, finding them to be small, and we propose corrections to reduce them further. Specifically, we relax the assumption of linear bias and only assume no redshift evolution of the cross-correlation coefficient, allowing us to leverage smaller clustering scales. We model the redshift distributions with splines and compare our results to previous analyses as well as to other parameterizations found in literature. For the two high-redshift tomographic bins, we find the shifts to higher redshifts with respect to the measurements performed in Rau+2022 to be Δz$_{3}$ =-0.039$^{+0.020}$$_{-0.021}$ and Δz$_{4}$ = -0.048$^{+0.012}$$_{-0.012}$.

Choppin de Janvry, J. [LBL, Berkeley; UC, Berkeley↗

The Low Energy Effective Area of the Chandra Low Energy Transmission Grating Spectrograph

The Chandra X-ray Observatory was successfully launched on July 23, 1999, and subsequently began an intensive calibration phase. We present the preliminary results from the in-flight calibration of the low energy response of the High Resolution Camera spectroscopic readout (HRC-S) combined with the Low Energy Transmission Grating (LETG) aboard Chandra. These instruments comprise the Low Energy Transmission Grating Spectrograph (LETGS). For this calibration study, we employ a pure hydrogen non-LTE white dwarf emission model (T = 25000 K and log g = 9.0) for comparison with the Chandra observations of Sirius B. The pre-flight calibration of the LETGS effective area only covered wavelengths shortward of 44 A (E less than 277 eV). Our Sirius B analysis shows that the HRC-S quantum efficiency (QE) model assumed for longer wavelengths leads to an overestimate of the effective area by an average factor of about 1.6. We derive a correction to the low energy HRC-S QE model to match the predicted and observed Sirius B spectra over the wavelength range of 44-185 A. We make an independent test of our results by the comparison of a Chandra LETGS observation of HZ 43 with pure hydrogen model atmosphere predictions and find good agreement.

Pease, D.↗

A Consistent EPIC Visible Channel Calibration using VIIRS and MODIS as a Reference

The Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite constantly images the sunlit disk of Earth from the Lagrange-1 (L1) point in 10 spectral channels spanning the UV, VIS, and NIR spectrums. Recently, the DSCOVR EPIC team has publicly released version 2 dataset, which has implemented improved navigation, stray-light correction, and flat-fielding of the CCD array. The EPIC 2-year data record must be well-calibrated for consistent cloud, aerosol, trace gas, land use and other retrievals. Because EPIC lacks onboard calibrators, the observations made by EPIC channels must be calibrated vicariously using the coincident measurements from radiometrically stable instruments that have onboard calibration systems. MODIS and VIIRS are best-suited instruments for this task as they contain similar spectral bands that are well-calibrated onboard using solar diffusers and lunar tracking. We have previously calibrated the EPIC version 1 dataset by using EPIC and VIIRS angularly matched radiance pairs over both all-sky ocean and deep convective clouds (DCC). We noted that the EPIC image required navigations adjustments, and that the EPIC stray-light correction provided an offset term closer to zero based on the linear regression of the EPIC and VIIRS ray-matched radiance pairs. We will evaluate the EPIC version 2 navigation and stray-light improvements using the same techniques. In addition, we will monitor the EPIC channel calibration over the two years for any temporal degradation or anomalous behavior. These two calibration methods will be further validated using desert and DCC invariant Earth targets. The radiometric characterization of the selected invariant targets is performed using multiple years of MODIS and VIIRS measurements. Results of these studies will be shown at the conference.

Haney, C. O.↗

MISR Level 1B1 Radiance Data (MI1B1_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, about 15 orbits/day, Daily - < Weekly].

EOSDIS↗

Infrared Measurements of Forward Heat Conduction during Simulated Microgravity Flame Spread in the Narrow Channel Apparatus

An infrared (IR) camera provides a way of examining temperature trends associated with simulated microgravity flame spread in the Narrow Channel Apparatus (NCA). The IR camera measures the surface temperature of solid poly methyl methacrylate (PMMA) fuel. These tests examine the forward conduction of heat ahead of the flame front in the non-thermally thin fuel.The NCA is a combustion wind tunnel that simulates a microgravity flame spread environment by employing a narrow gap between the fuel and ceiling of the device, limiting the effects of buoyancy. Test conditions of a 5 mm gap, mean opposed flow velocity of 15 cm/s, and fuel thickness of 3 mm are used.PMMA is selected as the fuel due to repeatability of test results, ease of computational modeling, and known combustion mechanics. Using specific lens and bandpass filter combinations the PMMA can be imaged as effectively opaque. The spectral emissivity for PMMA was calculated and incorporated into the calibration of the camera.Surface temperatures from the IR camera are compared to results from thermocouples embedded in the surface of the fuel. The IR camera results show that nontrivial forward conduction occurs during tests, and therefore must be included in computational models of the process.

Berry, Michael↗

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=about 15 orbits/day].

NEAR IR IMAGERY↗

Multi-Angle Imager for Aerosols (MAIA) spectral and radiometric calibration

The Multi-angle Imaging SpectroRadiometer (MISR) was launched as part of NASA’s Terra satellite suite of instruments. Still operational, it makes use of observations from multiple view angles to retrieve aerosol abundance and particle properties. The Multi-Angle Imager for Aerosols (MAIA) instrument improves on this heritage by incorporating polarimetry and an expanded spectral range. Combining these data with surface measurements, the relationship between pollution and human health will be explored. MAIA has just completed camera testing, building on the experience from MISR. Spectral calibration now makes use of a double subtractive monochromator, built with the intent to allow the exit slit output to be uniform in spectral content. For radiometric testing, hardware upgrades have included adding UV lamps to the 1.65 cm (65") integrating sphere, use of a NIST-traceable sphere to establish absolute radiances, and the addition of a UV transfer spectrometer to support characterization of the sphere output from 300 to 2500 nm. During camera build, Newton’s rings were observed in the detector Quantum Efficiency (QE) measurements. This is due to etaloning within the detector itself. Etaloning was also evident in the spectral and radiometric characterizations performed on the completed camera. Spectral metrics, including center wavelength and width, are presented here using a moment’s analysis. This better represents the band properties, particularly in bands where fringing is observed, as compared to a full-width at half-maximum determination. It is believed that the MAIA camera has been carefully characterized, and meet its spectral and radiometric requirements.

Harten, Gerard Van↗

MISR Level 1B1 Radiance Data (MI1B1_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

AM-1↗

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Temporal_Resolution=about 15 orbits/day].

AM-1↗

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy for rapid, label-free biological imaging

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a label-free imaging approach that provides detailed chemical information at high spatial resolution in a sample through nonlinear, coherent excitation of molecular vibrations and detection of Raman spectra. While its utility for biological imaging has been demonstrated, many aspects of this technique must mature before it can be widely adopted. One of the areas of required improvement is imaging speed—most BCARS implementations involve sample rastering, which limits imaging speed. Beam scanning can provide faster BCARS imaging but presents some unique challenges. Here, we describe a beam-scanning BCARS microscopy system that improves spatial resolution twofold and imaging speed by fivefold over a previous beam-scanning implementation. These enhancements were enabled by an improvement in supercontinuum power and the use of a sCMOS camera for its high data transfer rate and low read noise. Implementation of the sCMOS camera required correction for the significant pixel-to-pixel background and photon response nonuniformity. Here, we report on the method that we implemented for calibrating and correcting the pixel-to-pixel differences in sCMOS camera noise.

Dixon, Jessica Z. [Georgia Institute of Technology↗

(Almost) Featureless Stereo: Calibration and Dense 3D Reconstruction Using Whole Image Operations

The conventional approach to shape from stereo is via feature extraction and correspondences. This results in estimates of the camera parameters and a typically spare estimate of the surface. Given a set of calibrated images, a dense surface reconstruction is possible by minimizing the error between the observed image and the image rendered from the estimated surface with respect to the surface model parameters. Given an uncalibrated image and an estimated surface, the camera parameters can be estimated by minimizing the error between the observed and rendered images a function of the camera parameters. We use a very small dense set of matched features to provide camera parameter estimates for the initial dense surface estimate. We then re-estimate the camera parameters as described above, and then re-estimate the surface. This process is iterated. Whilst it can not be proven to converge, we have found that around three iterations results in excellent surface and camera parameters estimates.

Smelyanskiy, V. N.↗

Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.

42 ENGINEERING↗