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NASA NTRS2011

Launch Vehicle Failure Dynamics and Abort Triggering Analysis

Launch vehicle ascent is a time of high risk for an on-board crew. There are many types of failures that can kill the crew if the crew is still on-board when the failure becomes catastrophic. For some failure scenarios, there is plenty of time for the crew to be warned and to depart, whereas in some there is insufficient time for the crew to escape. There is a large fraction of possible failures for which time is of the essence and a successful abort is possible if the detection and action happens quickly enough. This paper focuses on abort determination based primarily on data already available from the GN&C system. This work is the result of failure analysis efforts performed during the Ares I launch vehicle development program. Derivation of attitude and attitude rate abort triggers to ensure that abort occurs as quickly as possible when needed, but that false positives are avoided, forms a major portion of the paper. Some of the potential failure modes requiring use of these triggers are described, along with analysis used to determine the success rate of getting the crew off prior to vehicle demise.

Hanson, John M.↗

NASA NTRS2009

Processing Images of Craters for Spacecraft Navigation

A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.

Cheng, Yang↗

NASA NTRS2015

Abort Trigger False Positive and False Negative Analysis Methodology for Threshold-Based Abort Detection

This paper describes a quantitative methodology for bounding the false positive (FP) and false negative (FN) probabilities associated with a human-rated launch vehicle abort trigger (AT) that includes sensor data qualification (SDQ). In this context, an AT is a hardware and software mechanism designed to detect the existence of a specific abort condition. Also, SDQ is an algorithmic approach used to identify sensor data suspected of being corrupt so that suspect data does not adversely affect an AT's detection capability. The FP and FN methodologies presented here were developed to support estimation of the probabilities of loss of crew and loss of mission for the Space Launch System (SLS) which is being developed by the National Aeronautics and Space Administration (NASA). The paper provides a brief overview of system health management as being an extension of control theory; and describes how ATs and the calculation of FP and FN probabilities relate to this theory. The discussion leads to a detailed presentation of the FP and FN methodology and an example showing how the FP and FN calculations are performed. This detailed presentation includes a methodology for calculating the change in FP and FN probabilities that result from including SDQ in the AT architecture. To avoid proprietary and sensitive data issues, the example incorporates a mixture of open literature and fictitious reliability data. Results presented in the paper demonstrate the effectiveness of the approach in providing quantitative estimates that bound the probability of a FP or FN abort determination.

risk assessment↗

NASA NTRS2016

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗

NASA NTRS2020

Cloud Detection over Snow and Ice with Oxygen A- and B-band Observations from the Earth Polychromatic Imaging Camera (EPIC)

Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.

EPIC↗

NASA NTRS1975

Decision-related cortical potentials during an auditory signal detection task with cued observation intervals

Cortical-evoked potentials were recorded from human subjects performing an auditory detection task with confidence rating responses. Unlike earlier studies that used similar procedures, the observation interval during which the auditory signal could occur was clearly marked by a visual cue light. By precisely defining the observation interval and, hence, synchronizing all perceptual decisions to the evoked potential averaging epoch, it was possible to demonstrate that high-confidence false alarms are accompanied by late-positive P3 components equivalent to those for equally confident hits. Moreover the hit and false alarm evoked potentials were found to covary similarly with variations in confidence rating and to have similar amplitude distributions over the scalp. In a second experiment, it was demonstrated that correct rejections can be associated with a P3 component larger than that for hits. Thus it was possible to show, within the signal detection paradigm, how the two major factors of decision confidence and expectancy are reflected in the P3 component of the cortical-evoked potential.

Squires, K. C.↗

NASA NTRS2021

Automated Technique for the Detection of Step-Like Solar Wind Dynamic Pressure Changes: Application to the Response of the Transpolar Potential to Solar Wind Dynamic Pressure Fronts

The input from the solar wind (SW) and the accompanying Interplanetary Magnetic Field (IMF) is the defining feature of the solar wind-magnetosphere interactions. One of the most important SW drivers is the solar wind dynamic pressure, and most significantly its sharp changes known as pressure fronts. Sudden enhancements in solar wind dynamic pressure, SWP, have been shown to lead to intensification of the auroral electrojets (and Region 1 field-aligned currents), increase in auroral emissions, and significant enhancement in ionospheric convection and the transpolar potential. Case studies of the interaction between pressure fronts and the terrestrial space environment shed great light on their importance to the structure and dynamics of the system. However, thorough understanding of the interaction requires fully statistical investigations. These statistical studies require a large number of suitable pressure front events. In the past these have been obtained through laborious manual inspection of solar wind data. We present an automated procedure that identifies sudden step enhancements in SWP that satisfy a desired set of limiting step-like characteristics, such as magnitude of the change, sign of the change (positive/negative), and rate of change. The procedure yields a list of suitable events, along with their step features within minutes. The technique is tested for missed events and false positives by direct comparison to manual inspection of the data. Its utility is illustrated by application to the statistical effect of pressure fronts to the transpolar potential as measured by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) technique.

A. Boudouridis↗

NASA NTRS2008

Commodity-Free Calibration

Commodity-free calibration is a reaction rate calibration technique that does not require the addition of any commodities. This technique is a specific form of the reaction rate technique, where all of the necessary reactants, other than the sample being analyzed, are either inherent in the analyzing system or specifically added or provided to the system for a reason other than calibration. After introduction, the component of interest is exposed to other reactants or flow paths already present in the system. The instrument detector records one of the following to determine the rate of reaction: the increase in the response of the reaction product, a decrease in the signal of the analyte response, or a decrease in the signal from the inherent reactant. With this data, the initial concentration of the analyte is calculated. This type of system can analyze and calibrate simultaneously, reduce the risk of false positives and exposure to toxic vapors, and improve accuracy. Moreover, having an excess of the reactant already present in the system eliminates the need to add commodities, which further reduces cost, logistic problems, and potential contamination. Also, the calculations involved can be simplified by comparison to those of the reaction rate technique. We conducted tests with hypergols as an initial investigation into the feasiblility of the technique.

Source record↗

NASA NTRS2017

Kepler Planet Detection Metrics: Robovetter Completeness and Effectiveness for Data Release 25

In general, the Kepler pipeline identifies a list of Threshold Crossing Events (TCEs), which are periodic flux decrements meeting certain criteria (Jenkins, 2017). These TCEs are reviewed and those that appear consistent with astrophysically transiting or eclipsing systems are classified as Kepler Objects of Interest (KOIs). Further review is given to KOIs, which are then dispositioned as Planet Candidates (PCs) or False Positive (FPs). FPs are further denoted by four major flags that indicate if the signal is Not Transit-Like (NTL), due to a Stellar Eclipse (SS; previously referred to as Significant Secondary), and/or due to contamination from a source other than the target as evidenced by a Centroid Offset (CO) oran Ephemeris Match (EM) with another object. This entire TCE review process is known as dispositioning or vetting.In the first five Kepler mission planet candidate catalogs (Borucki et al., 2011a,b; Batalha et al., 2013; Burke et al., 2014; Rowe et al., 2015), TCEs were manually examined on an individual basis and dispositioned using various plots and quantitative diagnostic tests (see e.g., Coughlin, 2017). In the sixth catalog, Mullally et al. (2015a) employed partial automation via simple parameter cuts to automatically disposition a large fraction of TCEs as not transit-like. Mullally et al. (2015a) also used an automated technique known as the centroid Robovetter (Mullally, 2017) to automatically identify some FP KOIs due to centroid offsets - a telltale signature of light contamination from another target. The remaining targets were manually dispositioned. In the seventh catalog, Coughlin et al. (2016) automated theentire dispositioning process using what is collectively known simply as the Robovetter.In the eighth and final mission catalog, Thompson et al. (2017) use a revised Robovetter to automate the dispositioning of all TCEs with an emphasis on creating a catalog suitable for accurately determining planet occurrence rates. In order to calculate accurate occurrence rates, the completeness and effectiveness of the Robovetter must be characterized. We define these terms as applied to the Robovetter, following Thompson et al. (2017), as:1. Completeness: The fraction of transiting planets detected by the pipeline that are classified as planet candidates by the Robovetter.2. Effectiveness: The fraction of false positives detected by the pipeline that are classified as false positives by the Robovetter.The remainder of this document describes products that can be used to quantitatively assess Robovetter completeness and effectiveness for an arbitrary set of Kepler stars.

Robovetter↗

NASA NTRS2007

Corrigendum: New Form of Kane's Equations of Motion for Constrained Systems

A correction to the previously published article "New Form of Kane's Equations of Motion for Constrained Systems" is presented. Misuse of the transformation matrix between time rates of change of the generalized coordinates and generalized speeds (sometimes called motion variables) resulted in a false conclusion concerning the symmetry of the generalized inertia matrix. The generalized inertia matrix (sometimes referred to as the mass matrix) is in fact symmetric and usually positive definite when one forms nonminimal Kane's equations for holonomic or simple nonholonomic systems, systems subject to nonlinear nonholonomic constraints, and holonomic or simple nonholonomic systems subject to impulsive constraints according to Refs. 1, 2, and 3, respectively. The mass matrix is of course symmetric when one forms minimal equations for holonomic or simple nonholonomic systems using Kane s method as set forth in Ref. 4.

Roithmayr, Carlos M.↗

NASA NTRS2018

Uncertainty in Heart Rate Complexity Metrics Caused by R-Peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Napoli, Nicholas J.↗

NASA NTRS1982

Mare basin filling on the moon - Laboratory simulations

Laboratory simulations of lavas filling a stylized lunar multi-ringed basin demonstrate several relationships between the morphology of the emplaced lavas and various eruption conditions. The rate of effusion is the primary control on the gross shape of the accumulated lavas, with relatively low rates (e.g., Hawaiian style) leading to shield volcanoes and high rates (e.g., flood eruptions) producing flat, ponded lavas. Pre-flow topography can have a significant effect on the general form of individual flows and the position of flow features such as lava channels. Rootless vents develop in many parts of the flow, including areas apparently related to the position of basin rings, giving the false appearance of aligned true vent systems.

Greeley, R.↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.

Park, Thomas↗

NASA NTRS2017

Structured Light-Based Hazard Detection For Planetary Surface Navigation

This paper describes a structured light-based sensor for hazard avoidance in planetary environments. The system presented here can also be used in terrestrial applications constrained by reduced onboard power and computational complexity and low illumination conditions. The sensor is on a calibrated camera and laser dot projector system. The onboard hazard avoidance system determines the position of the projected dots in the image and through a triangulation process detects potential hazards. The paper presents the design parameters for this sensor and describes the image based solution for hazard avoidance. The system presented here was tested extensively in day and night conditions in Lunar analogue environments. The current system achieves over 97 detection rate with 1.7 false alarms over 2000 images.

Nefian, Ara↗

NASA NTRS2020

Visible - Near Infrared Spectral Indices for Mapping Mineralogy and Chemistry with OSIRIS-REx

The primary objective of the Origins, Spectral Interpretation, Resource Identification, SecurityRegolith Explorer (OSIRIS-REx) mission is to return to Earth a pristine sample of carbonaceous material from the primitive asteroid (101955) Bennu. To support compositional mapping as part of sample site selection and characterization, we tested 95 spectral parameters on visible to near infrared laboratory reflectance data of minerals and carbonaceous meteorites to find which of these parameters reliably identified spectral features of interest. Most spectral parameters had high positive detection rates when used on spectra of pure, single component materials. The meteorite spectra have fewer and weaker absorption features and, as a result, fewer detections with the spectral parameters. Parameters targeting absorptions at 0.7 and 2.7 – 3 µm, which arise due to hydrated minerals, were most successful for the meteorites. Based on these results, we have identified a set of 17 parameters that are most likely to be useful at Bennu and spectral analogs. These parameters detect olivines, pyroxenes, carbonates, water/OH-bearing minerals, serpentines, ferric minerals, and organics. Particle size and albedo are known to affect band depth but had a negligible impact on parameter accuracy. The effect of instrument-like noise added to the laboratory spectra can result in more false positive detections, but these exhibit large errors. Our study has determined the prioritization of spectral parameters used for OSIRISREx spectral analysis and mapping and informs the reliability of all parameter-derived data products.

Hannah H Kaplan↗

NASA NTRS2021

Passive Microwave Signatures and Retrieval of High-Latitude Snowfall Over Open Oceans and Sea Ice: Insights From Coincidences of GPM and CloudSat Satellites

This article studies changes in microwave signals of oceanic snowfall in response to the formation of snow-covered sea ice using active and passive coincident data from the radar and radiometer onboard the CloudSat and the global precipitation measurement satellites. Using reanalysis data of liquid and ice water path as well as satellite retrievals of sea ice snow-cover depth, spectral regions are determined over which the snowfall signatures are likely to be obscured or falsely detected. Relying on an a priori database populated with the active–passive coincidences, a Bayesian snowfall retrieval algorithm is presented that links a k -nearest neighbor matching with the inverse Gaussian estimator used in the Goddard profiling algorithm. Without relying on any ancillary data of air temperature, the results demonstrate that over open oceans (sea ice), we can passively retrieve the CloudSat active snowfalls with a true positive rate of 92 (85%) and the root mean squared error of 0.24 (0.15) mm per h.

Sajad Vahedizade↗

NASA NTRS2012

Adaptive Trajectory Prediction Algorithm for Climbing Flights

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.

Seperation Assurance↗

NASA NTRS2018

Exoplanet Biosignatures: At the Dawn of a New Era of Planetary Observations

The rapid rate of discoveries of exoplanets has expanded the scope of the science possible for the remote detection of life beyond Earth. The Exoplanet Biosignatures Workshop-Without-Walls (EBWWW) held in 2016 engaged the international scientific community across diverse scientific disciplines, to assess the state of the science and technology in the search for life on exoplanets, and to identify paths for progress. The workshop activities resulted in five (5) major review papers which provide: 1) an encyclopedic review of known and proposed biosignatures and models used to ascertain them; 2) an in-depth review of O2 as a biosignature, rigorously examining the nuances of false positives and negatives for evidence of life; 3) a Bayesian framework to comprehensively organize current understanding to quantify confidence in biosignature assessments; 4) an extension of that Bayesian framework in anticipation of increasing planetary data and novel concepts of biosignatures, and 5) a review of the upcoming telescope capabilities to characterize exoplanets and their environment. Because of the immense content of these review papers, this summary provides a guide to their complementary scope and highlights salient features. Strong themes that emerged from the workshop were that biosignatures must be interpreted in the context of their environment, and that frameworks must be developed to link diverse forms of scientific understanding of that context to quantify the likelihood that a biosignature has been observed. Models are needed to explore the parameter space where measurements will be widespread but sparse in detail. Given the technological prospects for large ground-based telescopes and direct imaging from space-based observatories, the detection of atmospheric signatures of a few potentially habitable planets may come before 2030.

spectral imaging↗