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NASA NTRS2014

The Near Earth Object Scout Spacecraft: A Low Cost Approach to in-situ Characterization of the NEO Population

In this paper we describe a micro/nano satellite spacecraft and a supporting mission profile and architecture designed to enable preliminary in-situ characterization of a significant number of Near Earth Objects (NEOs) at reasonable cost. The spacecraft will be referred to as the NEO Scout. NEO Scout spacecraft are to be placed in GTO, GEO, or cis-lunar space as secondary payloads on launch vehicles headed for GTO or beyond and will begin their mission after deployment from the launcher. A distinguishing key feature of the NEO scout system is to design the mission timeline and spacecraft to rendezvous with and land on the target NEOs during close approach to the Earth-Moon system using low-thrust/high- impulse propulsion systems. Mission feasibility and preliminary design analysis are presented along with detailed trajectory calculations. The use of micro/nano satellites in low-cost interplanetary exploration is attracting increasing attention and is the subject of several annual workshops and published design studies (1-4). The NEO population consists of those asteroids and short period comets orbiting the Sun with a perihelion of 1.3 astronomical units or less (5-8). As of July 30, 2013 10065 Near-Earth objects have been discovered. The spin rate, mass, density, surface physical (especially mechanical) properties, composition, and mineralogy of the vast majority of these objects are highly uncertain and the limited available telescopic remote sensing data imply a very diverse population (5-8). In-situ measurements by robotic spacecraft are urgently needed to provide the characterization data needed to support hardware and mission design for more ambitious human and robotic NEO operations. Large numbers of NEOs move into close proximity with the Earth-Moon system every year (9). The JPL Near-Earth Object Human Space Flight Accessible Targets Study (NHATS) (10) has produced detailed mission profile and delta V requirements for various NEO missions ranging from 30 to 420 days in duration and assuming chemical propulsion. Similar studies have been reported assuming high power electric propulsion for manned NEO rendezvous missions (11). The delta V requirement breakdown and mission profile data from references 10 and 11 are used as a basis for sizing the NEO Scout spacecraft and for conducting preliminary feasibility assessments using the Tsiokolvsky rocket equation, a (worst-case) delta V requirement of 10 km/sec, and a maximum spacecraft dry mass of 20 kg. Using chemical propellant for a 10 km/sec delta V drives spacecraft wet mass well above 300 kg so that chemical propulsion is a non-starter for the proposed mission profile and spacecraft wet mass limits. In contrast, a solar electric propulsion system needs only 8 kg of Xe propellant to accelerate the spacecraft to 10 km/sec in 163 days with 0.02 N of thrust and 500 W of power from1.6 sq m of 29% efficient solar panels. In a second example, accelerating a 4 kg payload to 7 km/sec over 180 days requires about 6.7 kg of propellant and 1.2 kg of solar panels (12 kg total spacecraft wet mass).

Koontz, Steven L.↗
NASA NTRS2013

Urban Image Classification: Per-Pixel Classifiers, Sub-Pixel Analysis, Object-Based Image Analysis, and Geospatial Methods: Chapter - 10

Remote sensing methods used to generate base maps to analyze the urban environment rely predominantly on digital sensor data from space-borne platforms. This is due in part from new sources of high spatial resolution data covering the globe, a variety of multispectral and multitemporal sources, sophisticated statistical and geospatial methods, and compatibility with GIS data sources and methods. The goal of this chapter is to review the four groups of classification methods for digital sensor data from space-borne platforms; per-pixel, sub-pixel, object-based (spatial-based), and geospatial methods. Per-pixel methods are widely used methods that classify pixels into distinct categories based solely on the spectral and ancillary information within that pixel. They are used for simple calculations of environmental indices (e.g., NDVI) to sophisticated expert systems to assign urban land covers. Researchers recognize however, that even with the smallest pixel size the spectral information within a pixel is really a combination of multiple urban surfaces. Sub-pixel classification methods therefore aim to statistically quantify the mixture of surfaces to improve overall classification accuracy. While within pixel variations exist, there is also significant evidence that groups of nearby pixels have similar spectral information and therefore belong to the same classification category. Object-oriented methods have emerged that group pixels prior to classification based on spectral similarity and spatial proximity. Classification accuracy using object-based methods show significant success and promise for numerous urban 3 applications. Like the object-oriented methods that recognize the importance of spatial proximity, geospatial methods for urban mapping also utilize neighboring pixels in the classification process. The primary difference though is that geostatistical methods (e.g., spatial autocorrelation methods) are utilized during both the pre- and post-classification steps. Within this chapter, each of the four approaches is described in terms of scale and accuracy classifying urban land use and urban land cover; and for its range of urban applications. We demonstrate the overview of four main classification groups in Figure 1 while Table 1 details the approaches with respect to classification requirements and procedures (e.g., reflectance conversion, steps before training sample selection, training samples, spatial approaches commonly used, classifiers, primary inputs for classification, output structures, number of output layers, and accuracy assessment). The chapter concludes with a brief summary of the methods reviewed and the challenges that remain in developing new classification methods for improving the efficiency and accuracy of mapping urban areas.

Myint, Soe W.↗
NASA NTRS2013

Hierarchical Robot Control System and Method for Controlling Select Degrees of Freedom of an Object Using Multiple Manipulators

A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type.

Abdallah, Muhammad E.↗
NASA NTRS2014

Systems and Methods for Imaging of Falling Objects

Imaging of falling objects is described. Multiple images of a falling object can be captured substantially simultaneously using multiple cameras located at multiple angles around the falling object. An epipolar geometry of the captured images can be determined. The images can be rectified to parallelize epipolar lines of the epipolar geometry. Correspondence points between the images can be identified. At least a portion of the falling object can be digitally reconstructed using the identified correspondence points to create a digital reconstruction.

Garrett, Tim↗
NASA NTRS2014

Imparting Motion to a Test Object Such as a Motor Vehicle in a Controlled Fashion

An apparatus imparts motion to a test object such as a motor vehicle in a controlled fashion. A base has mounted on it a linear electromagnetic motor having a first end and a second end, the first end being connected to the base. A pneumatic cylinder and piston combination have a first end and a second end, the first end connected to the base so that the pneumatic cylinder and piston combination is generally parallel with the linear electromagnetic motor. The second ends of the linear electromagnetic motor and pneumatic cylinder and piston combination being commonly linked to a mount for the test object. A control system for the linear electromagnetic motor and pneumatic cylinder and piston combination drives the pneumatic cylinder and piston combination to support a substantial static load of the test object and the linear electromagnetic motor to impart controlled motion to the test object.

Southward, Stephen C.↗
NASA NTRS2010

Multi-Objective Multi-User Scheduling for Space Science Missions

We have developed an architecture called MUSE (Multi-User Scheduling Environment) to enable the integration of multi-objective evolutionary algorithms with existing domain planning and scheduling tools. Our approach is intended to make it possible to re-use existing software, while obtaining the advantages of multi-objective optimization algorithms. This approach enables multiple participants to actively engage in the optimization process, each representing one or more objectives in the optimization problem. As initial applications, we apply our approach to scheduling the James Webb Space Telescope, where three objectives are modeled: minimizing wasted time, minimizing the number of observations that miss their last planning opportunity in a year, and minimizing the (vector) build up of angular momentum that would necessitate the use of mission critical propellant to dump the momentum. As a second application area, we model aspects of the Cassini science planning process, including the trade-off between collecting data (subject to onboard recorder capacity) and transmitting saved data to Earth. A third mission application is that of scheduling the Cluster 4-spacecraft constellation plasma experiment. In this paper we describe our overall architecture and our adaptations for these different application domains. We also describe our plans for applying this approach to other science mission planning and scheduling problems in the future.

science planning↗
NASA NTRS2016

Proving Ground Potential Mission and Flight Test Objectives and Near Term Architectures

NASA is developing a Pioneering Space Strategy to expand human and robotic presence further into the solar system, not just to explore and visit, but to stay. NASA's strategy is designed to meet technical and non-technical challenges, leverage current and near-term activities, and lead to a future where humans can work, learn, operate, and thrive safely in space for an extended, and eventually indefinite, period of time. An important aspect of this strategy is the implementation of proving ground activities needed to ensure confidence in both Mars systems and deep space operations prior to embarking on the journey to the Mars. As part of the proving ground development, NASA is assessing potential mission concepts that could validate the required capabilities needed to expand human presence into the solar system. The first step identified in the proving ground is to establish human presence in the cis-lunar vicinity to enable development and testing of systems and operations required to land humans on Mars and to reach other deep space destinations. These capabilities may also be leveraged to support potential commercial and international objectives for Lunar Surface missions. This paper will discuss a series of potential proving ground mission and flight test objectives that support NASA's journey to Mars and can be leveraged for commercial and international goals. The paper will discuss how early missions will begin to satisfy these objectives, including extensibility and applicability to Mars. The initial capability provided by the launch vehicle will be described as well as planned upgrades required to support longer and more complex missions. Potential architectures and mission concepts will be examined as options to satisfy proving ground objectives. In addition, these architectures will be assessed on commercial and international participation opportunities and on how well they develop capabilities and operations applicable to Mars vicinity missions.

Smith, R. Marshall↗
NASA NTRS2015

Reduction of Subjective and Objective System Complexity

Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached in finding the optimal or 'best balance' of the system functions and interrelationships. This is achievable following von Bertalanffy's approach of describing systems as a set of equations representing both the system functions and the system interrelationships. Reduction is found based on an objective function defining the system output given variations in the system inputs and the system operating environment. By minimizing the objective function with respect to these inputs and environments, a reduced system can be found. Thus, a reduction of the system complexity is feasible.

Watson, Michael D.↗
NASA NTRS2017

Multi-Objective Flight Control for Drag Minimization and Load Alleviation of High-Aspect Ratio Flexible Wing Aircraft

As aircraft wings become much more flexible due to the use of light-weight composites material, adverse aerodynamics at off-design performance can result from changes in wing shapes due to aeroelastic deflections. Increased drag, hence increased fuel burn, is a potential consequence. Without means for aeroelastic compensation, the benefit of weight reduction from the use of light-weight material could be offset by less optimal aerodynamic performance at off-design flight conditions. Performance Adaptive Aeroelastic Wing (PAAW) technology can potentially address these technical challenges for future flexible wing transports. PAAW technology leverages multi-disciplinary solutions to maximize the aerodynamic performance payoff of future adaptive wing design, while addressing simultaneously operational constraints that can prevent the optimal aerodynamic performance from being realized. These operational constraints include reduced flutter margins, increased airframe responses to gust and maneuver loads, pilot handling qualities, and ride qualities. All of these constraints while seeking the optimal aerodynamic performance present themselves as a multi-objective flight control problem. The paper presents a multi-objective flight control approach based on a drag-cognizant optimal control method. A concept of virtual control, which was previously introduced, is implemented to address the pair-wise flap motion constraints imposed by the elastomer material. This method is shown to be able to satisfy the constraints. Real-time drag minimization control is considered to be an important consideration for PAAW technology. Drag minimization control has many technical challenges such as sensing and control. An initial outline of a real-time drag minimization control has already been developed and will be further investigated in the future. A simulation study of a multi-objective flight control for a flight path angle command with aeroelastic mode suppression and drag minimization demonstrates the effectiveness of the proposed solution. In-flight structural loads are also an important consideration. As wing flexibility increases, maneuver load and gust load responses can be significant and therefore can pose safety and flight control concerns. In this paper, we will extend the multi-objective flight control framework to include load alleviation control. The study will focus initially on maneuver load minimization control, and then subsequently will address gust load alleviation control in future work.

Aerolasticity↗
NASA NTRS2018

The Gaia Catalogue Second Data Release and Its Implications to Optical Observations of Man-Made Earth Orbiting Objects

The Gaia catalogue second data release and its implications to optical observations of man-made Earth orbiting objects. Abstract and not the Final Paper is attached. The Gaia spacecraft was launched in December 2013 by the European Space Agency to produce a three-dimensional, dynamic map of objects within the Milky Way. Gaia's first year of data was released in September 2016. Common sources from the first data release have been combined with the Tycho-2 catalogue to provide a 5 parameter astrometric solution for approximately 2 million stars. The second Gaia data release is scheduled to come out in April 2018 and is expected to provide astrometry and photometry for more than 1 billion stars, a subset of which with a the full 6 parameter astrometric solution (adding radial velocity) and positional accuracy better than 0.002 arcsec (2 mas). In addition to precise astrometry, a unique opportunity exists with the Gaia catalogue in its production of accurate, broadband photometry using the Gaia G filter. In the past, clear filters have been used by various groups to maximize likelihood of detection of dim man-made objects but these data were very difficult to calibrate. With the second release of the Gaia catalogue, a ground based system utilizing the G band filter will have access to 1.5 billion all-sky calibration sources down to an accuracy of 0.02 magnitudes or better. In this talk, we will discuss the advantages and practicalities of implementing the Gaia filters and catalogue into data pipelines designed for optical observations of man-made objects.

Frith, James M.↗
NASA NTRS2018

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗
NASA NTRS2019

Template Matching Used for Small Body Optical Navigation with Poorly Detailed Objects

Object and template matching becomes difficult when an image lacks detail. This is particularly worrisome when typical matching techniques, cross-correlation, log-polar mapping, and key point matching fail. Work herein describes a formulation that identifies objects of interest, estimates the affine transformation between a template object and scene using Principal Component Analysis (PCA), and provides a fit value for the objects and template incorporating Hu's Moments. The algorithm presented is tested on synthetic images and images obtained from the OSIRIS-REx mission while the spacecraft was approaching its target, Bennu. Results for the current formulation show that, with the presence of large-scale variations and rotation, the fitting scheme performs well when compared with other techniques.

Lyzhoft, Joshua R.↗
NASA NTRS2018

Occluded Object Reconstruction for First Responders with Augmented Reality Glasses Using Conditional Generative Adversarial Networks

Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts. Our system then reconstructed an image of a new flammable object. Finally, the reconstructed image was superimposed on the input image to provide "transparency". The system imitates human learning about the laws of physics through experience by learning the shape of flammable objects and the flame characteristics.

Chow, Edward↗
NASA NTRS2020

WISEA J083011.95+283716.0: A Missing Link Planetary-mass Object

We present the discovery of WISEA J083011.95+283716.0, the first Y-dwarf candidate identified through the “Backyard Worlds: Planet 9” citizen science project. We identified this object as a red, fast-moving source with a faint W2 detection in multiepoch AllWISE and unWISE images. We have characterized this object with Spitzer and Hubble Space Telescope’s (HST) follow-up imaging. With mid-infrared detections in Spitzerʼs ch1 and ch2 bands and flux upper limits in HST F105W and F125W filters, we find that this object is both very faint and has extremely red colors (ch1 − ch2 = 3.25 ± 0.23 mag, F125W− ch2 ≽ 9.36 mag), consistent with a T(sub eff) ∼ 300 K source, as estimated from the known Y-dwarf population. A preliminary parallax provides a distance of - 11.1+1.5 2.0 pc, leading to a slightly warmer temperature of ∼350 K. The extreme faintness and red HST and Spitzer colors of this object suggest that it may be a link between the broader Y-dwarf population and the coldest known brown dwarf WISE J0855−0714, and may highlight our limited knowledge of the true spread of Y-dwarf colors. We also present four additional “Backyard Worlds: Planet 9” late-T brown dwarf discoveries within 30 pc.

Brown dwarf↗
NASA NTRS2020

Hunting Distant BL Lacertae Objects with the Photometric Technique Using Swift and SARA

BL Lacertae objects represent a large fraction (22%) of γ-ray sources in the Third Fermi Large Area Telescope catalog (3FGL). Nearly half of the BL Lac object population remains without a redshift because of their featureless optical spectra. We aim to increase the number of BL Lac objects with a redshift measurement by using the photometric technique. For this work, we have used six Swift-UVOT filters and SDSS g′, r′, i′, and z′ optical filters mounted on the 0.65 m SARA–CTIO located in Chile and the 1.0 m SARA–ORM in the Canary Islands. A sample of 45 sources was selected from the 3FGL catalog for which photometry was performed in 10 optical and UV filters to obtain redshift measurements. We found three sources with z > 1.3, while reliable upper limits have been provided for 17 sources. The results presented here bring the total number of high-z (z > 1.3) BL Lac objects to 29.

M. Rajagopal↗
NASA NTRS2020

Object-Based Comparison of Data-Driven and Physics-Driven Satellite Estimates of Extreme Rainfall

The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conventional ‘‘grid-by-grid analysis,’’ the object-based approach provides a promising way to diagnose spatial properties of storms, trace them through space and time, and connect their accuracy to storm types and input data sources. The evolution of two tropical cyclones are generally captured by IMERG and NU-WRF, while the less organized spatial patterns of two mesoscale convective systems pose challenges for both. NU-WRF rain rates are generally more accurate, while IMERG better captures storm location and shape. Both show higher skill in detecting large, intense storms compared to smaller, weaker storms. IMERG’s accuracy depends on the input microwave and infrared data sources; NU-WRF does not appear to exhibit this dependence. Findings highlight that an object-oriented view can provide deeper insights into satellite precipitation performance and that the satellite precipitation community should further explore the potential for ‘‘hybrid’’ data-driven and physics-driven estimates in order to make optimal usage of satellite observations.

extreme events↗
NASA NTRS2022

A Census of Young Stellar Objects in Two Line-of-Sight Star-Forming Regions Toward IRAS 22147+5948 in the Outer Galaxy

Context. Star formation in the outer Galaxy, namely, outside of the Solar circle, has not been extensively studied in part due to the low CO brightness of the molecular clouds linked with the negative metallicity gradient. Recent infrared surveys provide an overview of dust emission in large sections of the Galaxy, but they suffer from cloud confusion and poor spatial resolution at far-infrared wavelengths. Aims. We aim to develop a methodology to identify and classify young stellar objects (YSOs) in star-forming regions in the outer Galaxy and use it to resolve a long-standing disparity in terms of the distance and evolutionary status of IRAS 22147+5948. Methods. We used a support vector machine learning algorithm to complement standard color–color and color–magnitude diagrams in our search for YSOs in the IRAS 22147 region, based on publicly available data from the Spitzer Mapping of the Outer Galaxy survey. The agglomerative hierarchical clustering algorithm was used to identify clusters. Then the physical properties of individual YSOs were calculated. The distances were determined using CO 1–0 from the Five College Radio Astronomy Observatory survey. Results. We identified 13 Class I and 13 Class II YSO candidates using the color–color diagrams, along with an additional 2 and 21 sources, respectively, using the applied machine learning techniques. The spectral energy distributions of 23 sources were modeled with a star and a passive disk, corresponding to Class II objects. The models of three sources include envelopes that are typical for Class I objects. The objects were grouped into two clusters located at a distance of 2:2 kpc and 5 clusters at 5:6 kpc. The spatial extent of CO, radio continuum, and dust emission confirms the origin of YSOs in two distinct star-forming regions along a similar line of sight. Conclusions. The outer Galaxy may serve as a unique laboratory for exploring star formation across environments, on the condition that complementary methods and ancillary data are used to properly account for cloud confusion and distance uncertainties.

Agata Karska↗
NASA NTRSDate not supplied

Automated Detection and Analysis of Resident Space Objects with the 1.3-Meter Eugene Stansbery-Meter Class Autonomous Telescope

Optical telescopes dedicated to the detection of orbital debris employ large-area detectors that generate a large number of images each night. Such surveys require automated data analysis pipelines that process the images and detect moving objects. We present an overview of the data analysis pipeline employed by the 1.3-meter Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) on Ascension Island, operated by NASA’s Orbital Debris Program Office. The pipeline enfolds the astrometric and photometric calibration of the images, star-trail removal, object detection, correlation over multiple sequential image frames, and orbital parameter estimation. The performance of the pipeline was investigated by means of Monte-Carlo simulations in which simulated object tracks were inserted into ES-MCAT images and then processed by the pipeline. This technique allows one to confidently estimate the completeness for the detection of resident space objects as a function of apparent magnitude and angular velocity. This paper discusses these techniques and provides examples using actual data.

Paul Hickson↗