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ATLAS Flight Science Receiver Algorithms

This is the basis document for the ATLAS Receiver Algorithms. ATLAS is the single instrument on the ICESat-2 mission. The Receiver (Rx) Algorithms select the signal location in real-time and instruct the hardware to telemeter a vertical band of received time-tags about this signal location. The algorithms are implemented in the Flight Software (FSW) and in the hardware of the Photon Counting Electronics (PCE) cards. The sole purpose of the algorithms is to reduce the telemetry data volume to fit within the downlink constraint while maximizing the probability of downlinking surface signal. All versions of the Receiver Algorithms from version 2.8 onward incorporate our best knowledge of the ATLAS hardware at this time. It presents algorithms that, based on current Simulator testing, satisfy all of the requirements for the Rx Algorithms. Testing during ATLAS Instrument Integration and Testing with the hardware and software implementation of the Rx Algorithms revealed characteristics and responses that required changes to the Rx Algorithms and this document, which are captured in the change record below.All relevant documentation for the Receiver Algorithms can be found on the ICESat-2 Technical Data Management System (TDMS) under the ATLAS Algorithms subsystem.The launch version of the FSW (version 3.1.0) is based upon version 3.7c of this document.

Mcgarry, Jan L.↗

Results of the Compensated Earth-Moon-Earth Retroreflector Laser Link (CEMERLL) Experiment

Adaptive optics techniques can be used to realize a robust low bit-error-rate link by mitigating the atmosphere-induced signal fades in optical communications links between ground-based transmitters and deep-space probes. Phase I of the Compensated Earth-Moon-Earth Retroreflector Laser Link (CEMERLL) experiment demonstrated the first propagation of an atmosphere-compensated laser beam to the lunar retroreflectors. A 1.06-micron Nd:YAG laser beam was propagated through the full aperture of the 1.5-m telescope at the Starfire Optical Range (SOR), Kirtland Air Force Base, New Mexico, to the Apollo 15 retroreflector array at Hadley Rille. Laser guide-star adaptive optics were used to compensate turbulence-induced aberrations across the transmitter's 1.5-m aperture. A 3.5-m telescope, also located at the SOR, was used as a receiver for detecting the return signals. JPL-supplied Chebyshev polynomials of the retroreflector locations were used to develop tracking algorithms for the telescopes. At times we observed in excess of 100 photons returned from a single pulse when the outgoing beam from the 1.5-m telescope was corrected by the adaptive optics system. No returns were detected when the outgoing beam was uncompensated. The experiment was conducted from March through September 1994, during the first or last quarter of the Moon.

Wilson, K. E.↗

Attributes of GRB Pulses: Analysis of BATSE TTE Data

Our extensive program of modeling GRB profiles is aimed at elucidating the physical processes responsible for the burst itself, as well as possible extrinsic phenomena (e.g. time dilation) as discussed in another paper in this Symposium (Norris et al., "GRB PROFILES AS COSMIC PROBES"). We have developed special methods to extract the wealth of short time-scale information contained in the BATSE time-tag event (TTE) data. Our algorithm yields a piecewise-constant representation of the light curve -- using only the raw photon arrival times, and based on Bayesian change-point methods. This representation in effect lets the data determine the bin size and location, and avoids unwanted effects due to arbitrary choices of the bin parameters. We have determined widths, separations, and amplitudes of pulses contained in the bursts, without invoking a specific pulse model. The effect of cosmic time dilation can be easily seen in a direct plot of amplitude vs. time scale for individual pulses, without the need to lump the data into a small number of brightness classes. We are also performing noise equalization on these data (to reduce a well-known bias of pulse width as a function of signal-to-noise ratio), as well as fits of parametric pulse-shape models -- including explicit energy dependence of the pulse parameters. Such refinements are expected to improve the quality and physical significance of these results.

Norris, J. P.↗

Interpreting Broad Double-Peaked Emission Lines in Active Galactic Nuclei

The principal objectives of this project were to probe the inner regions of active galactic nuclei and to test general relativity in the strong-field limit. The approach takes advantage of broad atomic line emission observed from material deep in the potential well of an active galactic nucleus which contains key information as to the physics of the system. Line profiles in a wide range of wavebands from optical to X-ray have provided compelling evidence of the existence of a relativistic accretion disk around a supermassive black hole in a number of galaxies. The simplest model posits a geometrically thin disk in Keplerian orbit, with general relativistic effects in evidence. This model is the point of departure for the proposed work. We developed a high-performance numerical code to calculate photon trajectories in a Schwarzschild or Kerr metric and implemented it on parallel supercomputers. This code includes a general purpose ray tracer that calculates line profiles, light curves, and other observable quantities for a wide variety of emitter configurations. The versatility comes from the fact that the ray tracing algorithm does not depend on any symmetries regarding emitter locations. The speed comes from parallel implementation which enables us to sample hitherto unattainable volumes of disk model parameter space. During the period 1 March 1997 through 28 February 1998, two papers, supported in whole or in part by this grant, were published in refereed journals. They are reproduced in their entirety in the next two sections of this report.

Halpern, Jules↗

ICESat-2 Meltwater Depth Estimates: Application to Surface Melt on Amery Ice Shelf, East Antarctica

Surface melting occurs during summer on the Antarctic and Greenland ice sheets, but the volume of meltwater stored has been difficult to quantify due to a lack of accurate depth estimates. NASA’s ICESat-2 laser altimeter brings a new capability: photons penetrate water and are reflected from both the water and the underlying ice; the difference provides a depth estimate. ICESat-2 sampled Amery Ice Shelf on 2 January 2019 and showed double returns from surface depressions, indicating meltwater. For four melt features, we compared depth estimates from eight algorithms: six based on ICESat-2 and two from coincident Landsat-8 and Sentinel-2 imagery. All algorithms successfully identified surface water at the same locations. Algorithms based on ICESat-2 produced the most accurate depths; the image-based algorithms underestimated depths (by 30-70%). This implies that ICESat-2 depths can be used to tune image-based algorithms, moving us closer to quantifying stored meltwater volumes across Antarctica and Greenland.

ICESat-2↗

Zernike Wavefront Sensor Modeling Development for LOWFS on WFIRST-AFTA

WFIRST-AFTA design makes use of an existing 2.4m telescope for direct imaging of exoplanets. To maintain the high contrast needed for the coronagraph, wavefront error (WFE) of the optical system needs to be continuously sensed and controlled. Low Order Wavefront Sensing (LOWFS) uses the rejected starlight from an immediate focal plane to sense wavefront changes (mostly thermally induced low order WFE) by combining the LOWFS mask (a phase plate located at the small center region with reflective layer) with the starlight rejection masks, i.e. Hybrid Lyot Coronagraph (HLC)'s occulter or Shaped Pupil Coronagraph (SPC)'s field stop. Zernike wavefront sensor (ZWFS) measures phase via the phase-contrast method and is known to be photon noise optimal for measuring low order aberrations. Recently, ZWFS was selected as the baseline LOWFS technology on WFIST/AFTA for its good sensitivity, accuracy, and its easy integration with the starlight rejection mask. In this paper, we review the theory of ZWFS operation, describe the ZWFS algorithm development, and summarize various numerical sensitivity studies on the sensor performance. In the end, the predicted sensor performance on SPC and HLC configurations are presented.

Zernike phase contrast↗

Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures

Lightweight, electromagnetic interference (EMI) immune, fiber-optic, sensor- based structural health monitoring (SHM) will play an increasing role in aerospace structures ranging from aircraft wings to jet engine vanes. Fiber Bragg Grating (FBG) sensors for SHM include advanced signal processing, system and damage identification, and location and quantification algorithms. Potentially, the solution could be developed into an autonomous onboard system to inspect and perform non-destructive evaluation and SHM. A novel method has been developed to massively multiplex FBG sensors, supported by a parallel processing interrogator, which enables high sampling rates combined with highly distributed sensing (up to 96 sensors per system). The interrogation system comprises several subsystems. A broadband optical source subsystem (BOSS) and routing and interface module (RIM) send light from the interrogation system to a composite embedded FBG sensor matrix, which returns measurand-dependent wavelengths back to the interrogation system for measurement with subpicometer resolution. In particular, the returned wavelengths are channeled by the RIM to a photonic signal processing subsystem based on powerful optical chips, then passed through an optoelectronic interface to an analog post-detection electronics subsystem, digital post-detection electronics subsystem, and finally via a data interface to a computer. A range of composite structures has been fabricated with FBGs embedded. Stress tensile, bending, and dynamic strain tests were performed. The experimental work proved that the FBG sensors have a good level of accuracy in measuring the static response of the tested composite coupons (down to submicrostrain levels), the capability to detect and monitor dynamic loads, and the ability to detect defects in composites by a variety of methods including monitoring the decay time under different dynamic loading conditions. In addition to quasi-static and dynamic load monitoring, the system can capture acoustic emission events that can be a prelude to structural failure, as well as piezoactuator-induced ultrasonic Lamb-waves-based techniques as a basis for damage detection.

Moslehi, Behzad↗

An Efficient, FPGA-Based, Cluster Detection Algorithm Implementation for a Strip Detector Readout System in a Time Projection Chamber Polarimeter

A fundamental challenge in a spaceborne application of a gas-based Time Projection Chamber (TPC) for observation of X-ray polarization is handling the large amount of data collected. The TPC polarimeter described uses the APV-25 Application Specific Integrated Circuit (ASIC) to readout a strip detector. Two dimensional photoelectron track images are created with a time projection technique and used to determine the polarization of the incident X-rays. The detector produces a 128x30 pixel image per photon interaction with each pixel registering 12 bits of collected charge. This creates challenging requirements for data storage and downlink bandwidth with only a modest incidence of photons and can have a significant impact on the overall mission cost. An approach is described for locating and isolating the photoelectron track within the detector image, yielding a much smaller data product, typically between 8x8 pixels and 20x20 pixels. This approach is implemented using a Microsemi RT-ProASIC3-3000 Field-Programmable Gate Array (FPGA), clocked at 20 MHz and utilizing 10.7k logic gates (14% of FPGA), 20 Block RAMs (17% of FPGA), and no external RAM. Results will be presented, demonstrating successful photoelectron track cluster detection with minimal impact to detector dead-time.

Polarimeter↗

Performance Analysis of Airborne Photon-Counting Lidar Data in Preparation for the ICESat-2 Mission

Two airborne photon-counting laser altimeters have been deployed in direct support of National Aeronautics and Space Adminsitration (NASA's) upcoming Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. Multiple Altimeter Beam Experimental Lidar (MABEL) was developed specifically for ICESat-2 testing and development. MABEL data are used to simulate key aspects of the ICESat-2 measurement strategy and are critical to the development of the algorithms for geophysical data-product generation. Slope Imaging Multipolarization Photon-counting Lidar (SIMPL) is a NASA Goddard Space Flight Center instrument that has also been deployed in support of ICESat-2 performance discovery. Both instruments are photon-counting, small footprint laser altimeters that sample in both the 532- and 1064-nm wavelengths. And both instruments serve as a proxy for ICESat-2 operational performance and error assessment and a basis for the development of potential validation strategies. This paper provides an overview of how data from MABEL and SIMPL overflights have specifically provided the foundation for understanding the quality of ICESat-2 data and how we can plan to evaluate ICESat-2 products through comparison with other modalities of lidar data and/or groundtruth locations using ground fiducials.

MABEL↗

Validation of ICESat-2 ATLAS Bathymetry and Analysis of ATLAS’s Bathymetric Mapping Performance

NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched in September, 2018. The satellite carries a single instrument, ATLAS (Advanced Topographic Laser Altimeter System), a green wavelength, photon-counting lidar, enabling global measurement and monitoring of elevation with a primary focus on the cryosphere. Although bathymetric mapping was not one of the design goals for ATLAS, pre-launch work by our research team showed the potential to map bathymetry with ICESat-2, using data from MABEL (Multiple Altimeter Beam Experimental Lidar), NASA’s high-altitude airborne ATLAS emulator, and adapting the laser-radar equation for ATLAS specific parameters. However, many of the sensor variables were only approximations, which limited a full assessment of the bathymetric mapping capabilities of ICESat-2 during pre-launch studies. Following the successful launch, preliminary analyses of the geolocated photon returns have been conducted for a number of coastal sites, revealing several salient examples of seafloor detection in water depths of up to ~40 m. The geolocated seafloor photon returns cannot be taken as bathymetric measurements, however, since the algorithm used to generate them is not designed to account for the refraction that occurs at the air–water interface or the corresponding change in the speed of light in the water column. This paper presents the first early on-orbit validation of ICESat-2 bathymetry and quantification of the bathymetric mapping performance of ATLAS using data acquired over St. Thomas, U.S. Virgin Islands. A refraction correction, developed and tested in this work, is applied, after which the ICESat-2 bathymetry is compared against high-accuracy airborne topo-bathymetric lidar reference data collected by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). The results show agreement to within 0.43—0.60 m root mean square error (RMSE) over 1 m grid resolution for these early on-orbit data. Refraction-corrected bottom return photons are then inspected for four coastal locations around the globe in relation to Visible Infrared Imaging Radiometer Suite (VIIRS) K(d)(490) data to empirically determine the maximum depth mapping capability of ATLAS as a function of water clarity. It is demonstrated that ATLAS has a maximum depth mapping capability of nearly 1 Secchi in depth for water depths up to 38 m and K(d)(490) in the range of 0.05–0.12 per m. Collectively, these results indicate the great potential for bathymetric mapping with ICESat-2, offering a promising new tool to assist in filling the global void in nearshore bathymetry.

ICESat-2↗

SLR data screening; location of peak of data distribution

At the 5th Laser Ranging Instrumentation Workshop held at Herstmonceux in 1984, consideration was given to the formation of on-site normal points by laser stations, and an algorithm was formulated. The algorithm included a recommendation that an iterated 3.0 x rms rejection criterion should be used to screen the data, and that arithmetic means should be formed within the normal point bins of the retained data. From Sept. 1990 onwards, this algorithm and screening criterion have been brought into effect by various laser stations for forming on-site normal points, and small variants of the algorithm are used by most analysis centers for forming normal points from full-rate data, although the data screening criterion they use ranges from about 2.5 to 3.0 x rms. At the CSTG Satellite Laser Ranging (SLR) Subcommission, a working group was set up in Mar. 1991 to review the recommended screening procedure. This paper has been influenced by the discussions of this working group, although the views expressed are primarily those of this author. The main thrust of this paper is that, particularly for single photon systems, a more important issue than data screening is the determination of the peak of a data distribution and hence, the determination of the bias of the peak from the mean. Several methods of determining the peak are discussed.

Sinclair, Andrew T.↗

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Joiner, J.↗

X-Ray Detection and Processing Models for Spacecraft Navigation and Timing

The current primary method of deepspace navigation is the NASA Deep Space Network (DSN). High-performance navigation is achieved using Delta Differential One-Way Range techniques that utilize simultaneous observations from multiple DSN sites, and incorporate observations of quasars near the line-of-sight to a spacecraft in order to improve the range and angle measurement accuracies. Over the past four decades, x-ray astronomers have identified a number of xray pulsars with pulsed emissions having stabilities comparable to atomic clocks. The x-ray pulsar-based navigation and time determination (XNAV) system uses phase measurements from these sources to establish autonomously the position of the detector, and thus the spacecraft, relative to a known reference frame, much as the Global Positioning System (GPS) uses phase measurements from radio signals from several satellites to establish the position of the user relative to an Earth-centered fixed frame of reference. While a GPS receiver uses an antenna to detect the radio signals, XNAV uses a detector array to capture the individual xray photons from the x-ray pulsars. The navigation solution relies on detailed xray source models, signal processing, navigation and timing algorithms, and analytical tools that form the basis of an autonomous XNAV system. Through previous XNAV development efforts, some techniques have been established to utilize a pulsar pulse time-of-arrival (TOA) measurement to correct a position estimate. One well-studied approach, based upon Kalman filter methods, optimally adjusts a dynamic orbit propagation solution based upon the offset in measured and predicted pulse TOA. In this delta position estimator scheme, previously estimated values of spacecraft position and velocity are utilized from an onboard orbit propagator. Using these estimated values, the detected arrival times at the spacecraft of pulses from a pulsar are compared to the predicted arrival times defined by the pulsar s pulse timing model. A discrepancy provides an estimate of the spacecraft position offset, since an error in position will relate to the measured time offset of a pulse along the line of sight to the pulsar. XNAV researchers have been developing additional enhanced approaches to process the photon TOAs to arrive at an estimate of spacecraft position, including those using maximum-likelihood estimation, digital phase locked loops, and "single photon processing" schemes that utilize all available time data associated with each photon. Using pulsars from separate, non-coplanar locations provides range and range-rate measurements in each pulsar s direction. Combining these different pulsar measurements solves for offsets in position and velocity in three dimensions, and provides accurate overall navigation for deep space vehicles.

Sheikh, Suneel↗

Geoscience Laser Altimeter System (GLAS) for the ICESat Mission

The Geoscience Laser Altimeter System (GLAS) is a new generation lidar and is the primary science payload for NASA's ICESat Mission. The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, establish a grid of accurate height profiles of the Earth's land topography, and profile the vertical distribution of clouds and aerosols on a global scale. GLAS will be integrated onto a small spacecraft built by Ball Aerospace, and will be launched into a polar orbit with a 590-630 km altitude at an inclination of 94 degrees. ICESat is is currently planned to launch in winter 2002/03 and GLAS is designed to operate continuously in space for a minimum of 3 years. GLAS will measure the vertical distance from orbit to the Earth's surface with pulses from a ND:YAG laser at a 40 Hz rate. Each 6 nsec wide 1064 nm laser pulse is used to produce a single range measurement. On the surface, the laser footprints have 66 m diameter and approx. 170 m center-center spacings. The GLAS receiver uses a I m diameter telescope to detect laser backscatter and a Si APD to detect the 1064 nm signals. The detector's output is sampled by a digital ranging receiver, which records each transmitted pulse and surface echo waveform with 1 nsec (15 cm) resolution. Each echo pulse is digitized and is reported to ground with a record length of from 200 to 544 samples, depending on the spacecraft's location . The GLAS location and epoch times are measured by a precision GPS receiver carried on the ICESat spacecraft. Initial processing of the echo waveforms within GLAS permits discrimination between cloud and surface echoes for selecting appropriate waveform samples. This selection is guided by an on-board DEM which is used to set the boundaries for the echo pulse search algorithm. Subsequent ground-based echo pulse analysis, along with GPS-based clock frequency estimates, permit final determination of the range to the surface, degree of pulse spreading, and vertical distribution of any vegetation illuminated by the laser. Accurate knowledge of the laser beam's pointing angle is needed to prevent height biases when measuring over tilted surfaces, such as near the boundaries of ice sheets. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam's centroid angle to better than 10 urad is needed. GLAS uses a stellar reference system (SRS) to measure the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith and a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser is measured pulse relative to the star camera with a laser reference system (LRS). GLAS will also measure the vertical distributions of clouds and aerosols by recording the vertical profiles of laser pulse backscatter at both 1064 and 532 nm. The 1064 rim measurements use the Si APD detector and will be used to measure the height and echo pulse shape from thicker clouds. The lidar receiver at 532 nm uses a narrow bandwidth etalon filter and highly sensitive photon counting detectors. The 532 nm backscatter profiles will be used to measure the vertical extent of thinner clouds and the atmospheric boundary layer. The GLAS instrument component development is complete and the instrument is undergoing final testing and qualification at NASA-Goddard. The GLAS "as-built" characteristics and its expected measurement performance will be discussed.

Abshire, James B.↗