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NASA NTRS1987

Multiple-angle observations of reflectance anisotropy from an airborne linear array sensor

An airborne pointable imaging multispectral linear array sensor has been developed for the multidirectional observation of surface reflectance anisotropy. The sensor design permits observations up to 45 deg off-nadir in three spectral bands (green, red, and near-infrared). Calibration permits the conversion of sensor data to radiance units with an absolute uncertainty of 6 percent. Observations of five field plots from seven view directions are discussed. Calibration and atmospheric corrections are used to derive hemispherical-directional reflectance factors. A three-term reflectance model is fit to the reflectance factors for each plot to represent the continuous distribution of reflectance factors with view direction. The reflectance model is integrated over all view directions to calculate bihemispherical reflectance factors. The calculated bihemispherical factors differed by 1 to 25 percent from values based on an assumption of isotropic reflectance depending on spectral band and field plot. These calculations demonstrate the technologic and scientific capabilities required for the remote characterization of surface reflectance anisotropy. Remote multidirectional observations are both feasible and needed to fully evaluate land reflectance characteristics.

Irons, James R.↗

NASA NTRS1991

Multiple-mode reconfigurable electro-optic switching network for optical fiber sensor array

This paper reports the first switching network compatible with multimode fibers. A one-to-many cascaded reconfigurable interconnection was built. A thin glass substrate was used as the guiding medium which provides not only higher coupling efficiency from multimode fiber to waveguide but also better tolerance of phase-matching conditions. Involvement of a total-internal-reflection hologram and multimode waveguide eliminates interface problems between fibers and waveguides. The DCG polymer graft has proven to be reliable from -180 C to +200 C. Survivability of such an electrooptic system in harsh environments is further ensured. LiNbO3 was chosen as the E-O material because of its stability at high temperatures (phase-transition temperature of more than 1000 C) and maturity of E-O device technology. Further theoretical calculation was conducted to provide the optimal interaction length and device capacitance.

Chen, Ray T.↗

NASA NTRS2010

Electrochemical Detection of Multiple Bioprocess Analytes

An apparatus that includes highly miniaturized thin-film electrochemical sensor array has been demonstrated as a prototype of instruments for simultaneous detection of multiple substances of interest (analytes) and measurement of acidity or alkalinity in bioprocess streams. Measurements of pH and of concentrations of nutrients and wastes in cell-culture media, made by use of these instruments, are to be used as feedback for optimizing the growth of cells or the production of desired substances by the cultured cells. The apparatus is designed to utilize samples of minimal volume so as to minimize any perturbation of monitored processes. The apparatus can function in a potentiometric mode (for measuring pH), an amperometric mode (detecting analytes via oxidation/reduction reactions), or both. The sensor array is planar and includes multiple thin-film microelectrodes covered with hydrous iridium oxide. The oxide layer on each electrode serves as both a protective and electrochemical transducing layer. In its transducing role, the oxide provides electrical conductivity for amperometric measurement or pH response for potentiometric measurement. The oxide on an electrode can also serve as a matrix for one or more enzymes that render the electrode sensitive to a specific analyte. In addition to transducing electrodes, the array includes electrodes for potential control. The array can be fabricated by techniques familiar to the microelectronics industry. The sensor array is housed in a thin-film liquid-flow cell that has a total volume of about 100 mL. The flow cell is connected to a computer-controlled subsystem that periodically draws samples from the bioprocess stream to be monitored. Before entering the cell, each 100-mL sample is subjected to tangential-flow filtration to remove particles. In the present version of the apparatus, the electrodes are operated under control by a potentiostat and are used to simultaneously measure the pH and the concentration of glucose. It is anticipated that development of procedures for trapping more enzymes into hydrous iridium oxide (and possibly into other electroactive metal oxides) and of means for imparting long-term stability to the transducer layers should make it possible to monitor concentrations of products of many enzyme reactions for example, such key bioprocess analytes as amino acids, vitamins, lactose, and acetate.

Rauh, R. David↗

DOE OSTI2024

Point Sensor Networks Struggle to Detect and Quantify Short Controlled Releases at Oil and Gas Sites

This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of the mixing ratio readings at downwind sensors were greater than the site’s baseline plus two standard deviations. Four of seven total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from −100% to 24% for solution D, −100% to −43% for solution E, −25% for solution F (solution F was only at one site), and −99% to 430% for solution G, with an overall average of −29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within ±2.5 kg/h of the study team’s best estimate of site-level emissions at the time of the releases.

42 ENGINEERING↗

NASA NTRSDate not supplied

Planning Satellite Swarm Measurements for Climate Models: Comparing Dynamic Constraint Processing and MILP Methods

We present D-SHIELD, a challenging climate science application to plan coordinated measurements (observations) for a constellation of satellites, each containing two different sensors, each with 61 pointing angle options. The L-band and P-band radar sensors collect data fed into a soil moisture model which tracks and predicts soil moisture across 1.67 million Ground Positions (GP). Soil moisture is an important predictor of wildfires, and then a predictor of floods, landslides and debris flow after a fire. Each measurement covers multiple GP due to the sensor footprint. Each GP has a "model error" which represents the uncertainty of the the soil moisture state prediction. Model error changes at different rates for each GP as the time since last observation increases and after significant events like rain. The planner's goal is to select measurements which maximize soil moisture model improvement (reduce model uncertainty). This problem is combinatorically explosive, involving many degrees of freedom for planner choices. Good domain heuristics can find solutions within a reasonable time for our application needs but cannot be proven optimal. In this paper we compare two different planning approaches to this problem: Dynamic Constraint Processing (DCP) and Mixed Integer Linear Programming (MILP). We match inputs and metrics for both DCP and MILP algorithms to enable a direct apples-to-apples comparison. We demonstrate and discuss the trades between DCP flexibility and performance vs. MILP's promise of provable optimality.

Rich Levinson↗

NASA NTRS1988

A figure control sensor for the Large Deployable Reflector (LDR)

A sensing and control system is required to maintain high optical figure quality in a segmented reflector. Upon detecting a deviation of the segmented surface from its ideal form, the system drives segment mounted actuators to realign the individual segments and thereby return the surface to its intended figure. When the reflector is in use, a set of figure sensors will determine positions of a number of points on the back surface of each of the reflector's segments, each sensor being assigned to a single point. By measuring the positional deviations of these points from previously established nominal values, the figure sensors provide the control system with the information required to maintain the reflector's optical figure. The optical lever, multiple wavelength interferometer, and electronic capacitive sensor, the most promising technologies for the development of the figure sensor, are illustrated. It is concluded that to select a particular implementation of the figure sensors, performance requirement will be refined and relevant technologies investigated further.

Bartman, R.↗

NASA NTRS2001

Video-Based Sensor for Robotic Position and Attitude determination

NASA's Marshall Space Flight Center (MSFC) has, for the last ten years, developed various video-based sensors for use in automated docking systems. The latest generation of sensor will operate at rates of up to 100 Hz, determining the relative position (X, Y, and Z) and attitude (Roll, Pitch, and Yaw) between the sensor and a small 3-dimensional target, making it suitable for applications in robotic sensing. The Advanced Video Guidance Sensor (AVGS) is designed to track multiple targets at different ranges and determine the position and attitude of each one. The previous generation of video sensor, the Video Guidance Sensor (VGS), was flown twice on the Space Shuttle to test its performance on orbit. One of the tests performed was determining the relative positions and attitudes between the VGS and its target, which was moved to various positions using the Remote Manipulator System (RMS). The RMS position data and VGS measured data were analyzed after the flights, with good correlation between the position and attitude data of the two data sets. The test using the RMS gives a good idea of the ability of the use of the AVGS as a sensor for end-effector position and attitude determination.

Howard, Richard T.↗

DOE OSTI2021

Characterization of a selective, zero power sensor for distributed sensing of hydrogen in energy applications

The use of hydrogen as a clean and renewable energy source is increasing rapidly for both vehicle and stationary applications. There are safety concerns for the locations in which hydrogen is made, used, and transported (i.e., pipelines and tanker trucks). Sensors are needed to comply with safety regulations and to enable a smooth and safe rollout of hydrogen as an alternative energy. However, hydrogen sensors do not yet exist that have the combined features of small size and low power for easy deployment coupled with high-volume manufacturability and low cost. This is necessary to accommodate the emerging fixed and mobile markets while retaining critical metrological metrics, including measurement range, detection limits, selectivity, fast response, stability, and long lifetime. An amperometric gas sensor for hydrogen (AGS) has been developed using an innovative manufacturing method. The sensor was designed using scalable fabrication strategies based on “Printed Electronics” (PE) methodology which are compatible with large-scale production. Prototype sensors were batch fabricated with multiple individual elements on a substrate compatible in size with a standard 8-inch wafer to enable high-volume, low-cost manufacturing, thereby leveraging PE and semiconductor fabrication infrastructure. This novel AGS was instrumented with control circuitry and evaluated for hydrogen detection in the range of 0–5000 ppmv H2 in air. Specific performance evaluations included assessment of the sensor measurement range, repeatability, and selectivity.

08 HYDROGEN↗

NASA NTRS1982

Multispectral linear array

The Multispectral Linear Array (MLA) is a solid-state earth imagery radiometer operating in the 'push-broom' mode and using a focal plane containing multiple spectral band linear detector arrays. The MLA sensor offers the capability for increased spatial and spectral resolution with multiple selectable bands and in-orbit operation flexibility. Both free-flyer (satellite) and Shuttle-attached instrument designs have been studied. Four Shuttle-attached MLA instrument design studies were initiated in 1982, and the concepts resulting from these studies are described.

Richard, H. L.↗

NASA NTRS1981

Control theoretics for large structural systems

The areas of research addressed include modeling identification for both the purposes of analysis and controls, design of structural control systems actuator sensor placement, and distributed sensing and actuation as opposed to co-located sensor and actuators. Also investigated are adaptive/learning processes that could more specifically be referred to as inflight testing procedures where a structure is tested during its deployment or assembly and during its orbital life at specific points where the characteristics of the structure for the purpose of tuning the control system are identified. Another area is redundancy management techniques for structural systems. This is important because of the reliability issue for managing multiple very large numbers of sensors and actuators.

Montgomery, R. C.↗

NASA NTRS2013

Remote Observations of Reentering Spacecraft Including the Space Shuttle Orbiter

Flight measurement is a critical phase in development, validation and certification processes of technologies destined for future civilian and military operational capabilities. This paper focuses on several recent NASA-sponsored remote observations that have provided unique engineering and scientific insights of reentry vehicle flight phenomenology and performance that could not necessarily be obtained with more traditional instrumentation methods such as onboard discrete surface sensors. The missions highlighted include multiple spatially-resolved infrared observations of the NASA Space Shuttle Orbiter during hypersonic reentry from 2009 to 2011, and emission spectroscopy of comparatively small-sized sample return capsules returning from exploration missions. Emphasis has been placed upon identifying the challenges associated with these remote sensing missions with focus on end-to-end aspects that include the initial science objective, selection of the appropriate imaging platform and instrumentation suite, target flight path analysis and acquisition strategy, pre-mission simulations to optimize sensor configuration, logistics and communications during the actual observation. Explored are collaborative opportunities and technology investments required to develop a next-generation quantitative imaging system (i.e., an intelligent sensor and platform) with greater capability, which could more affordably support cross cutting civilian and military flight test needs.

Horvath, Thomas J.↗

NASA NTRS2008

Integrated Software Systems for Crew Management During Extravehicular Activity in Planetary Terrain Exploration

Initial planetary explorations with the Apollo program had a veritable ground support army monitoring the safety and health of the 12 astronauts who performed lunar surface extravehicular activities (EVAs). Given the distances involved, this will not be possible on Mars. A spacesuit for Mars must be smart enough to replace that army. The next generation suits can do so using 2 software systems serving as virtual companions, LEGACI (Life support, Exploration Guidance Algorithm and Consumable Interrogator) and VIOLET (Voice Initiated Operator for Life support and Exploration Tracking). The system presented in this study integrates data inputs from a suite of sensors into the MIII suit s communications, avionics and informatics hardware for distribution to remote managers and data analysis. If successful, the system has application not only for Mars but for nearer term missions to the Moon, and the next generation suits used on ISS as well. Field tests are conducted to assess capabilities for next generation spacesuits at Johnson Space Center (JSC) as well as the Mars and Lunar analog (Devon Island, Canada). LEGACI integrates data inputs from a suite of noninvasive biosensors in the suit and the astronaut (heart rate, suit inlet/outlet lcg temperature and flowrate, suit outlet gas and dewpoint temperature, pCO2, suit O2 pressure, state vector (accelerometry) and others). In the Integrated Walkback Suit Tests held at NASA-JSC and the HMP tests at Devon Island, communication and informatics capabilities were tested (including routing by satellite from the suit at Devon Island to JSC in Houston via secure servers at VCU in Richmond, VA). Results. The input from all the sensors enable LEGACI to compute multiple independent assessments of metabolic rate, from which a "best" met rate is chosen based on statistical methods. This rate can compute detailed information about the suit, crew and EVA performance using test-derived algorithms. VIOLET gives LEGACI voice activation capability, allowing the crew to query the suit, and receive feedback and alerts that will lead to corrective action. LEGACI and VIOLET can also automatically control the astronaut's cooling and consumable use rate without crew input if desired. These findings suggest that non-invasive physiological and environmental sensors supported with data analysis can allow for more effective management of mission task performance during EVA. Integrated remote and local view of data metrics allow crewmember to receive real time feedback in synch with mission control in preventing performance shortcomings for EVA in exploration missions.

Kuznetz, Lawrence↗

NASA NTRS1999

Electric Field Double Probe Measurements for Ionospheric Space Plasma Experiments

Double probes represent a well-proven technique for gathering high quality DC and AC electric field measurements in a variety of space plasma regimes including the magnetosphere, ionosphere, and mesosphere. Such experiments have been successfully flown on a variety of spacecraft including sounding rockets and satellites. Typical instrument designs involve a series of trades, depending on the science objectives, type of platform (e.g., spinning or 3-axis stabilized), expected plasma regime where the measurements will be made, available telemetry, budget, etc. In general, ionospheric DC electric field instruments that achieve accuracies of 0.1 mV/m or better, place spherical sensors at large distances (10m or more) from the spacecraft body in order to extend well beyond the spacecraft wake and sheath and to achieve large signal-to-noise ratios for DC and long wavelength measurements. Additional sets of sensors inboard of the primary, outermost sensors provide useful additional information, both for diagnostics of the plasma contact potentials, which particularly enhance the DC electric field measurements on non-spinning spacecraft, and for wavelength and phase velocity measurements that use the spaced receiver or "interferometer" technique. Accurate attitude knowledge enables B times V contributions to be subtracted from the measured potentials, and permits the measured components to be rotated into meaningful geophysical reference frames. We review the measurement technique for both DC and wave electric field measurements in the ionosphere discussing recent advances involving high resolution burst memories, multiple baseline double probes, new sensor surface materials, biasing techniques, and other considerations.

Pfaff, R.↗

DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

NASA NTRS2000

Video Based Sensor for Tracking 3-Dimensional Targets

Video-Based Sensor for Tracking 3-Dimensional Targets The National Aeronautics and Space Administration's (NASAs) Marshall Space Flight Center (MSFC) has been developing and testing video-based sensors for automated spacecraft guidance for several years, and the next generation of video sensor will have tracking rates up to 100 Hz and will be able to track multiple reflectors and targets. The Video Guidance Sensor (VGS) developed over the past several years has performed well in testing and met the objective of being used as the terminal guidance sensor for an automated rendezvous and capture system. The first VGS was successfully tested in closed-loop 3-degree-of-freedom (3- DOF) tests in 1989 and then in 6-DOF open-loop tests in 1992 and closed-loop tests in 1993-4. Development and testing continued, and in 1995 approval was given to test the VGS in an experiment on the Space Shuttle. The VGS flew in 1997 and in 1998, performing well for both flights. During the development and testing before, during, and after the flight experiments, numerous areas for improvement were found. The VGS was developed with a sensor head and an electronics box, connected by cables. The VGS was used in conjunction with a target that had wavelength-filtered retro-reflectors in a specific pattern, The sensor head contained the laser diodes, video camera, and heaters and coolers. The electronics box contained a frame grabber, image processor, the electronics to control the components in the sensor head, the communications electronics, and the power supply. The system works by sequentially firing two different wavelengths of laser diodes at the target and processing the two images. Since the target only reflects one wavelength, it shows up well in one image and not at all in the other. Because the target's dimensions are known, the relative positions and attitudes of the target and the sensor can be computed from the spots reflected from the target. The system was designed to work from I meter out to I 10 meters. The VGS was mounted on the Space Shuttle while its target was mounted on the Spartan free-flyer carried on the same Shuttle flight. The VGS tracked the Spartan at ranges up to 170m, and the VGS range data very closely matched the range data from the Hand-Held Laser- Rangefinder used by the astronauts on board the Shuttle. While the VGS was designed primarily as a terminal guidance sensor for an automated spacecraft, it could be applied to other uses. It could be used as an alignment aid for an operator of a remote system (giving position and attitude feedback data, as well as a camera view of the target), as a feedback system for a robotic arm, or for automated vehicle guidance. The next generation VGS, with its higher tracking rates, smaller size, and lower power could be used in more places than the original VGS, and by using LED's instead of laser diodes, the system would be eye-safe at any range. Other possible uses include tracking 3-dimensional objects with retro-reflectors mounted at various locations or motion analysis by placing several retro-reflectors on the moving object and tracking them at high speeds. There are few sensors capable of performing tasks similar to those the VGS can perform, and the next generation VGS will be even more capable than the original. Some of this work is previously presented in the papers.

Howard, R. T.↗

NASA NTRS2020

Excess Heat Capacity in Mo/Au Transition Edge Sensor Bolometric Detectors

Excessheat capacity in a bolometric detector has the consequence of increasing or leading to multiple device time con-stants.The Mo/Au bilayer transition edge sensor (TES) bolo-metric detectors intended for the high resolution mid-infrared spectrometer (HIRMES) have two response time, one of which is a few times longer than that estimated from materials used in the design. The relative contribution of this settling time to the overall time response of the detectors is roughly proportional with the pixel area, which ranges between ~0.3 and 2.6 mm2.Use of laser ablation to remove sections of the silicon membranes comprising the pixels results in a detector response with a smaller contribution from the secondary time constant.Additional information about the nature of this excess heat capacity is gleaned from glancing in-cidence x-ray diffraction, which reveals the presence of molyb-denum silicides near the silicon surface from the bi-layer deposi-tion.Quantitative analysis of the concentration of excess molyb-denum, estimated with secondary ion mass spectroscopy, is com-mensurate to the additional heat capacity needed to explain the anomalous time response of the detectors.

HIRMES↗

NASA NTRS2008

On Certain New Methodology for Reducing Sensor and Readout Electronics Circuitry Noise in Digital Domain

NASA Hubble Space Telescope (HST) and upcoming cosmology science missions carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection, and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensors. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed by the Hubble Space Telescope and the James Webb Space Telescope Projects. These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active (non-reference) pixel signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert- Huang Transform Data Processing System (HHT-DPS) for reference pixel information processing and its utilization in reconfigurable hardware on-board a spaceflight instrument or post-processing on the ground. The methodology examines signal processing for a 2-D domain, in which high-variance components of the thermal noise are carried by both active and reference pixels, similar to that in processing of low-voltage differential signals and subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the aforementioned statistical parameters in the digital domain (such as statistical averaging of the reference pixels themselves) zeroes out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast-varying noise components using the Hilbert-Huang Transform Data Processing System tool (HHT-DPS) developed at NASA and the high-level programming language MATLAB (Trademark of MathWorks Inc.), as well as alternative methods for correcting for the high-variance noise component, using an HgCdTe sensor data. The NASA Hubble Space Telescope data post-processing, as well as future deep-space cosmology projects on-board instrument data processing from all the sensor channels, would benefit from this effort.

Kizhner, Semion↗