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At least 289 records · Page 16

Analysis of UAS DAA Surveillance in Fast-Time Simulations without DAA Mitigation

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements for DAA surveillance system performance. A recent study conducted using NASA's ACES (Airspace Concept Evaluation System) simulation capability begins to address questions surrounding the development of draft MOPS for DAA surveillance systems. ACES simulations were conducted to study the performance of sensor systems proposed by the SC-228 DAA Surveillance sub-group. Analysis included but was not limited to: 1) number of intruders (both IFR and VFR) detected by all sensors as a function of UAS flight time, 2) number of intruders (both IFR and VFR) detected by radar alone as a function of UAS flight time, and 3) number of VFR intruders detected by all sensors as a function of UAS flight time. The results will be used by SC-228 to inform decisions about the surveillance standards of UAS DAA systems and future requirements development and validation efforts.

unmanned aircraft systems↗

The MeerKAT Fornax Survey: II. The rapid removal of H I from dwarf galaxies in the Fornax cluster

We present MeerKAT Fornax Survey atomic hydrogen (H I) observations of the dwarf galaxies located in the central ~2.5 × 4 deg 2 of the Fornax galaxy cluster (R vir ~2°). The H I images presented in this work have a 3σ column density sensitivity between 2.7 and 50 × 10 18 cm –2 over 25 km s –1 for spatial resolution between 4 and 1 kpc. We are able to detect an impressive M HI = 5 × 10 5 M ⊙ 3σ point source with a line width of 50 km s –1 at a distance of 20 Mpc. We detected H I in 17 out of the 304 dwarfs in our field, with 14 out of the 36 late-type dwarfs (LTDs) and three out of the 268 early-type dwarfs (ETDs). The H I-detected LTDs have likely just joined the cluster and are on their first infall as they are located at large clustocentric radii, with comparable MHI and mean stellar surface brightness at fixed luminosity as blue, star-forming LTDs in the field. By contrast, the H I-detected ETDs have likely been in the cluster longer than the LTDs and acquired their H I through a recent merger or accretion from nearby H I. Eight of the H I-detected LTDs host irregular or asymmetric H I emission and disturbed or lopsided stellar emission. There are two clear cases of ram pressure shaping the H I, with the LTDs displaying compressed H I on the side closest to the cluster centre and a one-sided, starless tail pointing away from the cluster centre. The H I-detected dwarfs avoid the most massive potentials (i.e. cluster centre and massive galaxies), consistent with massive galaxies playing an active role in the removal of H I. We created a simple toy model to quantify the timescale of H I stripping in the cluster by reproducing the observed M r' –M HI relation. We find that a M HI = 10 8 M ⊙ dwarf is stripped in ~240 Myr. The model is consistent with our observations, where low-mass LTDs are directly stripped of their H I from a single encounter and more massive LTDs can harbour a disturbed H I morphology due to longer times or multiple encounters being required to fully strip their H I. This is the first time dwarf galaxies with M HI ≲ 1 × 10 6 M ⊙ have been detected and resolved beyond the local group and in a galaxy cluster.

79 ASTRONOMY AND ASTROPHYSICS↗

A Survey of Autonomous Navigation Techniques Applicable to Lunar Surface Exploration

As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.

Paul D Mckee↗

A Survey of Autonomous Navigation Techniques Applicable to Lunar Surface Exploration

As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.

Paul McKee↗

Application of infrared radiometers for airborne detection of clear air turbulence and low level wind shear, airborne infrared low level wind shear detection test

The feasibility of infrared optical techniques for the advance detection and avoidance of low level wind shear (LLWS) or low altitude wind shear hazardous to aircraft operations was investigated. A primary feasibility research effort was conducted with infrared detectors and instrumentation aboard the NASA Ames Research Center Learjet. The main field effort was flown on the NASA-Ames Dryden B57B aircraft. The original approach visualized a forward-looking, infrared transmitting (KRS-5) window through which signals would reach the detector. The present concept of a one inch diameter light pipe with a 45 deg angled mirror enables a much simpler installation virtually anywhere on the aircraft coupled with the possibility of horizontal scanning via rotation of the forward directed mirror. Present infrared detectors and filters would certainly permit ranging and horizontal scanning in a variety of methods. CRT display technology could provide a contoured picture with possible shear intensity levels from the infrared detection system on the weather radar or a small adjunct display. This procedure shoud be further developed and pilot evaluated in a light aircraft such as a Cessna 207 or equivalent.

Kuhn, P. M.↗

A situated reasoning architecture for space-based repair and replace tasks

Space-based robots need low level control for collision detection and avoidance, short-term load management, fine-grained motion, and other physical tasks. In addition, higher level control is required to focus strategic decision making as missions are assigned and carried out. Reasoning and control must be responsive to ongoing changes in the environment. Research aimed at bridging the gap between high level artificial intelligence (AI) planning techniques and task-level robot programming for telerobotic systems is described. Situated reasoning is incorporated into AI and Robotics systems in order to coordinate a robot's activity within its environment. An integrated system under development in a component maintenance domain is described. It is geared towards replacing worn and/or failed Orbital Replacement Units (ORUs) designed for use aboard NASA's Space Station Freedom based on the collection of components available at a given time. High level control reasons in component space in order to maximize the number operational component-cells over time, while the task-level controls sensors and effectors, detects collisions, and carries out pick and place tasks in physical space. Situated reasoning is used throughout the system to cope with component failures, imperfect information, and unexpected events.

Bloom, Ben↗

Approach-Phase Precision Landing with Hazard Relative Navigation: Terrestrial Test Campaign Results of the Morpheus/ALHAT Project

The Morpheus Project began in late 2009 as an ambitious e ort code-named Project M to integrate three ongoing multi-center NASA technology developments: humanoid robotics, liquid oxygen/liquid methane (LOX/LCH4) propulsion and Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) into a single engineering demonstration mission to be own to the Moon by 2013. The humanoid robot e ort was redirected to a deploy- ment of Robonaut 2 on the International Space Station in February of 2011 while Morpheus continued as a terrestrial eld test project integrating the existing ALHAT Project's tech- nologies into a sub-orbital ight system using the world's rst LOX/LCH4 main propulsion and reaction control system fed from the same blowdown tanks. A series of 33 tethered tests with the Morpheus 1.0 vehicle and Morpheus 1.5 vehicle were conducted from April 2011 - December 2013 before successful, sustained free ights with the primary Vertical Testbed (VTB) navigation con guration began with Free Flight 3 on December 10, 2013. Over the course of the following 12 free ights and 3 tethered ights, components of the ALHAT navigation system were integrated into the Morpheus vehicle, operations, and ight control loop. The ALHAT navigation system was integrated and run concurrently with the VTB navigation system as a reference and fail-safe option in ight (see touchdown position esti- mate comparisons in Fig. 1). Flight testing completed with Free Flight 15 on December 15, 2014 with a completely autonomous Hazard Detection and Avoidance (HDA), integration of surface relative and Hazard Relative Navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman lter software, and landing within 2 meters of the VTB GPS-based navigation solution at the safe landing site target. This paper describes the Mor- pheus joint VTB/ALHAT navigation architecture, the sensors utilized during the terrestrial ight campaign, issues resolved during testing, and the navigation results from the ight tests.

Crain, Timothy P.↗

Helicopter Flight Test of a Compact, Real-Time 3-D Flash Lidar for Imaging Hazardous Terrain During Planetary Landing

A second generation, compact, real-time, air-cooled 3-D imaging Flash Lidar sensor system, developed from a number of cutting-edge components from industry and NASA, is lab characterized and helicopter flight tested under the Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT) project. The ALHAT project is seeking to develop a guidance, navigation, and control (GN&C) and sensing system based on lidar technology capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The Flash Lidar incorporates a 3-D imaging video camera based on Indium-Gallium-Arsenide Avalanche Photo Diode and novel micro-electronic technology for a 128 x 128 pixel array operating at a video rate of 20 Hz, a high pulse-energy 1.06 μm Neodymium-doped: Yttrium Aluminum Garnet (Nd:YAG) laser, a remote laser safety termination system, high performance transmitter and receiver optics with one and five degrees field-of-view (FOV), enhanced onboard thermal control, as well as a compact and self-contained suite of support electronics housed in a single box and built around a PC-104 architecture to enable autonomous operations. The Flash Lidar was developed and then characterized at two NASA-Langley Research Center (LaRC) outdoor laser test range facilities both statically and dynamically, integrated with other ALHAT GN&C subsystems from partner organizations, and installed onto a Bell UH-1H Iroquois "Huey" helicopter at LaRC. The integrated system was flight tested at the NASA-Kennedy Space Center (KSC) on simulated lunar approach to a custom hazard field consisting of rocks, craters, hazardous slopes, and safe-sites near the Shuttle Landing Facility runway starting at slant ranges of 750 m. In order to evaluate different methods of achieving hazard detection, the lidar, in conjunction with the ALHAT hazard detection and GN&C system, operates in both a narrow 1deg FOV raster-scanning mode in which successive, gimbaled images of the hazard field are mosaicked together as well as in a wider, 4.85deg FOV staring mode in which digital magnification, via a novel 3-D superresolution technique, is used to effectively achieve the same spatial precision attained with the more narrow FOV optics. The lidar generates calibrated and corrected 3-D range images of the hazard field in real-time and passes them to the ALHAT Hazard Detection System (HDS) which stitches the images together to generate on-the-fly Digital Elevation Maps (DEM's) and identifies hazards and safe-landing sites which the ALHAT GN&C system can then use to guide the host vehicle to a safe landing on the selected site. Results indicate that, for the KSC hazard field, the lidar operational range extends from 100m to 1.35 km for a 30 degree line-of-sight angle and a range precision as low as 8 cm which permits hazards as small as 25 cm to be identified. Based on the Flash Lidar images, the HDS correctly found and reported safe sites in near-real-time during several of the flights. A follow-on field test, planned for 2013, seeks to complete the closing of the GN&C loop for fully-autonomous operations on-board the Morpheus robotic, rocket-powered, free-flyer test bed in which the ALHAT system would scan the KSC hazard field (which was vetted during the present testing) and command the vehicle to landing on one of the selected safe sites.

Roback, VIncent E.↗

A taxonomy of automatic differentiation pitfalls

Automatic differentiation is a popular technique for computing derivatives of computer programs. While automatic differentiation has been successfully used in countless engineering, science, and machine learning applications, it can sometimes nevertheless produce surprising results. In this paper, we categorize problematic usages of automatic differentiation, and illustrate each category with examples such as chaos, time-averages, discretizations, fixed-point loops, lookup tables, linear solvers, and probabilistic programs, in the hope that readers may more easily avoid or detect such pitfalls. We also review debugging techniques and their effectiveness in these situations.

Autodiff↗

A Miniaturized Linear Wire Ion Trap with Electron Ionization and Single Photon Ionization Sources

A linear wire ion trap (LWIT) with both electron ionization (EI) and single photon ionization (SPI) sources was built. The SPI was provided by a vacuum ultraviolet (VUV) lamp with the ability to softly ionize organic compounds. The VUV lamp was driven by a pulse amplifier, which was controlled by a pulse generator, to avoid the detection of photons during ion detection. Sample gas was introduced through a leak valve, and the pressure in the system is shown to affect the signal-to-noise ratio and resolving power. Under optimized conditions, the limit of detection (LOD) for benzene was 80 ppbv using SPI, better than the LOD using EI (137 ppbv). System performance was demonstrated by distinguishing compounds in different classes from gasoline. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Evaluation of possible reactivation of undetected faults during CO 2 injection

Geologic storage of carbon dioxide can efficiently contribute to reduce greenhouse gas emissions to the atmosphere. Two major hazards of this technology are leakage towards the ground surface and fluid-induced seismicity. While major faults may be detected and avoided during site characterization, undetected subseismic faults could be encountered once injection has started. This paper investigates leakage and reactivation of undetected faults through coupled thermal–hydraulic–mechanical modeling. The simulations are performed using a recently developed sequential simulator, TOUGH-Pylith, that allows to accurately account for the thermodynamics of brine-CO 2 injection mixtures, and to model faults as surfaces of discontinuity using state-of-the-art fault friction laws. The simulator is benchmarked against well-known analytical solutions and subsequently applied to investigate two cases of CO 2 injection injection close to undetected faults under normal and strike-slip faulting regimes. Furthermore, although the scenarios are generic and represent unfavorable conditions, they suggest that leakage could occur and that undetected faults could trigger minor seismic events. Therefore, careful site characterization and continuous monitoring during operations should be always performed.

58 GEOSCIENCES↗

Differential Seismic Phase Detection Probability as a Potential Discriminant of Explosions and Earthquakes

Deep learning models trained to estimate the probability of seismic P and S phases are rapidly expanding the scale of local event detections. Here, we evaluate the potential for deep learning model output phase detection probabilities to contribute to event‐type classification, particularly discrimination of single‐fired borehole explosions and earthquakes at local distances (<300 km). Motivated by the empirical success of P/S amplitude ratios, we consider the difference between P and S pick probability output from previously developed phase detection models, P prob −S prob ⁠, as a discriminant. Test data include M L ∼1–4 earthquakes and explosions observed by common seismographs in ten geologically diverse localities. Depending on the picking model and training data, binary classification using P prob −S prob with at least three stations can achieve approximately equivalent classification accuracy as P/S amplitude ratios without requiring any customization. Joint classification with P/S and P prob −S prob improves accuracy for most quality control scenarios. Pick probabilities are an efficient attribute to consider in explosion discrimination because they can be automated byproducts of event detection. They avoid the binary choice of picking or not picking weakly visible S waves common to explosions.

Duan, Chenglong [Rice Univ., Houston, TX (United S↗

Visualization of Multi-Dimensional Imaging Data for the DIII-D National Fusion Facility

With funding provided from the Office of Fusion Energy Science’s program on Diagnostic Systems for Magnetic Fusion Energy Sciences, the PI and his team have pioneered the development of microwave imaging systems for magnetic fusion plasma diagnostics. Specifically, electron cyclotron emission (ECE) imaging [1], a passive radiometric technique, measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) [2], an active radar imaging technique, measures electron density fluctuations. These microwave imaging diagnostic instruments developed by UC Davis have made important contributions to fusion science in a relatively short period of time from their original installation on DIII-D. The microwave imaging diagnostic technique has matured considerably since the beginning of a fruitful collaboration with DIII-D and PPPL, and has also been adopted at preeminent tokamak facilities worldwide. As discussed in detail in the following, this has continued with the development of revolutionary microwave diagnostic instruments employing monolithic millimeter wave integrated circuit (MMIC) system-on-chip (SoC) technology. Specifically, “chip” receivers mounted in liquid crystal polymer (LCP) modules have been demonstrated to dramatically improve the performance of the electron cyclotron emission imaging (ECEI) system including: 30x improvement in noise temperature thereby permitting absolute 2-D electron temperature images, outstanding shielding against out-of-band interference including microwave bursting which had plagued previous ELM studies using the old quasi-optical mini-lens ECEI system, and independent modules facilitating flexible repair and replacement. Under the “Visualization of multi-dimensional imaging data for the DIII-D National Fusion Facility” program, funding was provided for a research scientist postdoc and a Ph.D. student to support physics studies at DIII-D employing these instruments. This endeavor is synergistic with our current grant under the DOE Fusion Energy Sciences (FES) program on Diagnostic Systems for Magnetic Fusion Energy Sciences. This support considerably increased the scientific output of the diagnostics. The activities were strongly focused in the areas of pedestal and ELM stability, energetic particle confinement, and the early detection and avoidance of tokamak disruptions employing the microwave imaging diagnostic instruments developed under the advanced diagnostics program where imaging of the ELM crash was made possible by the elimination of the interference from the associated microwave “bursts”

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗

Technical evaluation report on AGARD Flight Mechanics Panel Symposium on Flight in Turbulence

The proceedings of a conference on the effects of atmospheric turbulence on flight characteristics are presented. The subjects discussed include the following: (1) turbulent environment, (2) operational problems, (3) design criteria, and (4) artificial aids for flight improvement. One conclusion is that there is a critical need for cross correlation measurements between various low atmosphere turbulence components. Additional discussion were held concerning wake vortex research for wake vortex detection and avoidance.

Aiken, W. S., Jr.↗

Guidance system for a roving vehicle

Computer controlled guidance system for semiautonomous robot guides robot in incompletely defined environment. System operates in real time avoiding obstacles detected by "stereo television and laser range finder eyes."

Miller, J. A.↗

Interpretation of laser/multi-sensor data for short range terrain modeling and hazard detection

A terrain modeling algorithm that would reconstruct the sensed ground images formed by the triangulation scheme, and classify as unsafe any terrain feature that would pose a hazard to a roving vehicle is described. This modeler greatly reduces quantization errors inherent in a laser/sensing system through the use of a thinning algorithm. Dual filters are employed to separate terrain steps from the general landscape, simplifying the analysis of terrain features. A crosspath analysis is utilized to detect and avoid obstacles that would adversely affect the roll of the vehicle. Computer simulations of the rover on various terrains examine the performance of the modeler.

Messing, B. S.↗