SEARCH · Search NASA

Results for “Collision Avoidance”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

NASA NTRS1996

Virtual Acoustics, Aeronautics and Communications

An optimal approach to auditory display design for commercial aircraft would utilize both spatialized ("3-D") audio techniques and active noise cancellation for safer operations. Results from several aircraft simulator studies conducted at NASA Ames Research Center are reviewed, including Traffic alert and Collision Avoidance System (TCAS) warnings, spoken orientation "beacons" for gate identification and collision avoidance on the ground, and hardware for improved speech intelligibility. The implications of hearing loss amongst pilots is also considered.

Begault, Durand R.↗

NASA NTRS1998

Virtual acoustics, aeronautics, and communications

An optimal approach to auditory display design for commercial aircraft would utilize both spatialized (3-D) audio techniques and active noise cancellation for safer operations. Results from several aircraft simulator studies conducted at NASA Ames Research Center are reviewed, including Traffic alert and Collision Avoidance System (TCAS) warnings, spoken orientation "beacons" for gate identification and collision avoidance on the ground, and hardware for improved speech intelligibility. The implications of hearing loss among pilots is also considered.

NASA Center ARC↗

NASA NTRS2008

2007 Research and Engineering Annual Report

Selected research and technology activities at NASA Dryden Flight Research Center are summarized. These following activities exemplify the Center's varied and productive research efforts: Developing a Requirements Development Guide for an Automatic Ground Collision Avoidance System; Digital Terrain Data Compression and Rendering for Automatic Ground Collision Avoidance Systems; Nonlinear Flutter/Limit Cycle Oscillations Prediction Tool; Nonlinear System Identification Using Orthonormal Bases: Application to Aeroelastic/Aeroservoelastic Systems; Critical Aerodynamic Flow Feature Indicators: Towards Application with the Aerostructures Test Wing; Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm; Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool; Extension of Ko Straight-Beam Displacement Theory to the Deformed Shape Predictions of Curved Structures; F-15B with Phoenix Missile and Pylon Assembly--Drag Force Estimation; Mass Property Testing of Phoenix Missile Hypersonic Testbed Hardware; ARMD Hypersonics Project Materials and Structures: Testing of Scramjet Thermal Protection System Concepts; High-Temperature Modal Survey of the Ruddervator Subcomponent Test Article; ARMD Hypersonics Project Materials and Structures: C/SiC Ruddervator Subcomponent Test and Analysis Task; Ground Vibration Testing and Model Correlation of the Phoenix Missile Hypersonic Testbed; Phoenix Missile Hypersonic Testbed: Performance Design and Analysis; Crew Exploration Vehicle Launch Abort System-Pad Abort-1 (PA-1) Flight Test; Testing the Orion (Crew Exploration Vehicle) Launch Abort System-Ascent Abort-1 (AA-1) Flight Test; SOFIA Flight-Test Flutter Prediction Methodology; SOFIA Closed-Door Aerodynamic Analyses; SOFIA Handling Qualities Evaluation for Closed-Door Operations; C-17 Support of IRAC Engine Model Development; Current Capabilities and Future Upgrade Plans of the C-17 Data Rack; Intelligent Data Mining Capabilities as Applied to Integrated Vehicle Health Management; STARS Flight Demonstration No. 2 IP Data Formatter; Space-Based Telemetry and Range Safety (STARS) Flight Demonstration No. 2 Range User Flight Test Results; Aerodynamic Effects of the Quiet Spike(tm) on an F-15B Aircraft; F-15 Intelligent Flight Controls-Increased Destabilization Failure; F-15 Integrated Resilient Aircraft Control (IRAC) Improved Adaptive Controller; Aeroelastic Analysis of the Ikhana/Fire Pod System; Ikhana: Western States Fire Missions Utilizing the Ames Research Center Fire Sensor; Ikhana: Fiber-Optic Wing Shape Sensors; Ikhana: ARTS III; SOFIA Closed-Door Flutter Envelope Flight Testing; F-15B Quiet Spike(TM) Aeroservoelastic Flight Test Data Analysis; and UAVSAR Platform Precision Autopilot Flight Results.

Stoliker, Patrick↗

NASA NTRS2018

Comparative Analysis of ACAS-Xu and DAIDALUS Detect-and-Avoid Systems

The Detect and Avoid (DAA) capability of a recent version (Run 3) of the Airborne Collision Avoidance System-Xu (ACAS-Xu) is measured against that of the Detect and AvoID Alerting Logic for Unmanned Systems (DAIDALUS), a reference algorithm for the Phase 1 Minimum Operational Performance Standards (MOPS) for DAA. This comparative analysis of the two systems' alerting and horizontal guidance outcomes is conducted through the lens of the Detect and Avoid mission using flight data of scripted encounters from a recent flight test. Results indicate comparable timelines and outcomes between ACAS-Xu's Remain Well Clear alert and guidance and DAIDALUS's corrective alert and guidance, although ACAS-Xu's guidance appears to be more conservative. ACAS-Xu's Collision Avoidance alert and guidance occurs later than DAIDALUS's warning alert and guidance, and overlaps with DAIDALUS's timeline of maneuver to remain Well Clear. Interesting discrepancies between ACAS-Xu's directive guidance and DAIDALUS's "Regain Well Clear" guidance occur in some scenarios.

Davies, Jason T.↗

NASA NTRS2016

UAS-NAS Project Demo - Mini HITL Week 2 Stats

The UAS-NAS Project demo will showcase recent research efforts to ensure the interoperability between proposed UAS detect and avoid (DAA) human machine interface requirements (developed within RTCA SC-228) and existing collision avoidance displays. Attendees will be able to view the current state of the art of the DAA pilot traffic, alerting and guidance displays integrated with Traffic advisory and Collision Avoidance (TCAS) II in the UAS-NAS Project's research UAS ground control station (developed in partnership with the Air Force Research Laboratory). In addition, attendees will have the opportunity to interact with the research UAS ground control station and "fly" encounters, using the DAA and TCAS II displays to avoid simulated aircraft. The display of the advisories will be hosted on a laptop with an external 30" monitor, running the Vigilant Spirit system. DAA advisories will be generated by the JADEM software tool, connected to the system via the LVC Gateway. A repeater of the primary flight display will be shown on a 55" monitor mounted on a stand at the back of the booth to show the pilot interaction to the passersby.

UAS↗

NASA NTRS2016

AIAA Aviation UAS DAA Demonstration-Mini HITL Week 2 Stats

The UAS-NAS Project demo will showcase recent research efforts to ensure the interoperability between proposed UAS detect and avoid (DAA) human machine interface requirements (developed within RTCA SC-228) and existing collision avoidance displays. Attendees will be able to view the current state of the art of the DAA pilot traffic, alerting and guidance displays integrated with Traffic advisory and Collision Avoidance (TCAS) II in the UAS-NAS Project's research UAS ground control station (developed in partnership with the Air Force Research Laboratory). In addition, attendees will have the opportunity to interact with the research UAS ground control station and "fly" encounters, using the DAA and TCAS II displays to avoid simulated aircraft. The display of the advisories will be hosted on a laptop with an external 30" monitor, running the Vigilant Spririt system. DAA advisories will be generated by the JADEM software tool, connected to the system via the LVC Gateway. A repeater of the primary flight display will be shown on a 55" tv/monitor mounted on a stand at the back of the booth to show the pilot interaction to the passersby.

UAS↗

NASA NTRS1997

Pilot Non-Conformance to Alerting System Commands During Closely Spaced Parallel Approaches

Pilot non-conformance to alerting system commands has been noted in general and to a TCAS-like collision avoidance system in a previous experiment. This paper details two experiments studying collision avoidance during closely-spaced parallel approaches in instrument meteorological conditions (IMC), and specifically examining possible causal factors of, and design solutions to, pilot non-conformance.

Pritchett, Amy R.↗

NASA NTRS2014

Middle Man Concept for In-Orbit Collision Risks Mitigation, CAESAR and CARA Examples

This paper describes the conjunction analysis which has to be performed using data provided by JSpOC. This description not only demonstrates that Collision Avoidance is a 2- step process (close approach detection followed by risk evaluation for collision avoidance decision) but also leads to the conclusion that there is a need for a Middle Man role. After describing the Middle Man concept, this paper introduces two examples with their similarities and particularities: the American civil space effort delivered by the NASA CARA team (Conjunction Assessment Risk Analysis) and the French response CAESAR (Conjunction Assessment and Evaluation Service: Alerts and Recommendations). For both, statistics are presented and feedbacks discussed. All together, around 80 satellites are served by CARA and/or CAESAR. Both processes regularly evolve in order either to follow JSpOC upgrades or to improve analysis according to experience acquired during the past years.

conjunction↗

NASA NTRS1989

Interaction dynamics of multiple autonomous mobile robots in bounded spatial domains

A general navigation strategy for multiple autonomous robots in a bounded domain is developed analytically. Each robot is modeled as a spherical particle (i.e., an effective spatial domain about the center of mass); its interactions with other robots or with obstacles and domain boundaries are described in terms of the classical many-body problem; and a collision-avoidance strategy is derived and combined with homing, robot-robot, and robot-obstacle collision-avoidance strategies. Results from homing simulations involving (1) a single robot in a circular domain, (2) two robots in a circular domain, and (3) one robot in a domain with an obstacle are presented in graphs and briefly characterized.

Wang, P. K. C.↗

NASA NTRSDate not supplied

Monocular Ranging for Small Unmanned Aerial Systems in the Far-Field

Recent proliferation of small Unmanned Aerial Systems (sUAS) applications requires onboard collision avoidance systems to mitigate the risk of collision with non-cooperative aircraft and manned aircraft, which may not see sUAS in time to perform an avoidance maneuver. An attractive avenue for onboard collision avoidance is the utilization of machine vision cameras due to their low size, weight and power (SWaP) requirements. In this paper, we characterize the range performance of a machine vision system developed in-house and mounted onto an sUAS. The technique was designed to estimate the performance of a sense-and-avoid system to ensure that the sensing components meet the well-clear requirements for the chosen platform and avoidance strategy. Experimental flight-test data was acquired from test-flights flown along multiple collision geometries for two intruders: a general Aviation (GA) aircraft and a fixed-wing sUAS. The ownship and both intruders were instrumented with inertial navigation systems (INS) recording position and attitude information. The range at first detection, 𝑹𝟎, was extracted from in-flight imagery of head-on collision course geometry synchronized with INS data from both aircraft and ground-truth values extracted from the raw imagery. This initial detection distance, 𝑹𝟎, scales with atmospheric attenuation. Therefore, under clear sky conditions, the derived 𝑹𝟎 value represents the upper bound on the detection range achievable by the test configuration of the detector. Results indicate that the maximum initial detection distance for a 4k resolution action camera fitted with a 41º Field of View (FOV) lens is 2.763 ± 0.037 km for a GA aircraft and 0.881 ± 0.061 km for a fixed-wing sUAS, respectively. The in results this study suggest that a vision-based detect and track system may be analyzed using the sensor characterization and contextualized within aircraft well-clear volumes.

Chester V. Dolph↗

NASA NTRS2018

Realistic Covariance Generation for the GPM Spacecraft

A covariance realism process for NASA's Global Precipitation Measurement (GPM) spacecraft is detailed. The GPM spacecraft is in a low earth orbit, and performs collision avoidance maneuvers few times a year. Currently GPM is below the International Space Station (ISS). So, in addition to cataloged debris objects, GPM must contend with smallsat/cubesat objects that are deployed from the ISS. Both operational scenarios require complete knowledge of the expected GPM prediction errors as a function of time. In this study, we present a method for generating realistic predicted covariance that uses linear propagation of the covariance with the addition of process noise. Further analyses are presented for the process noise ''tuning'' that generates an inflation factor based on the observed error statistics of the predictive satellite trajectories when compared to the definitive ones. Different tuning strategies are considered and compared via a Goodness-of-Fit testing for the Gaussian properties of the scaled covariance. SpaceNav's realistic covariance generation approach takes into account the contribution of predicted maneuver errors in the increased propagation uncertainty. Corresponding maneuver uncertainty is injected into the state uncertainty, and is used within the collision avoidance process to determine the collision risk for close approach events that follow a maneuver. This is a critical step in the maneuver planning process that provides the satellite operator with an accurate quantification of the collision probability for planned maneuvers. Using this information, an informed decision can be made to proceed with a maneuver if the collision risk is acceptable. This approach is validated by Monte-Carlo simulations and results are presented.

spacecraft uncertainty propagation↗

NASA NTRS2013

A Geometric Analysis to Protect Manned Assets from Newly Launched Objects - Cola Gap Analysis

A safety risk was identified for the International Space Station (ISS) by The Aerospace Corporation, where the ISS would be unable to react to a conjunction with a newly launched object following the end of the launch Collision Avoidance (COLA) process. Once an object is launched, there is a finite period of time required to track, catalog, and evaluate that new object as part of standard onorbit COLA screening processes. Additionally, should a conjunction be identified, there is an additional period of time required to plan and execute a collision avoidance maneuver. While the computed prelaunch probability of collision with any object is extremely low, NASA/JSC has requested that all US launches take additional steps to protect the ISS during this "COLA gap" period. This paper details a geometric-based COLA gap analysis method developed by the NASA Launch Services Program to determine if launch window cutouts are required to mitigate this risk. Additionally, this paper presents the results of several missions where this process has been used operationally.

Hametz, Mark E.↗

NASA NTRS1989

Improved computer simulation of the TCAS 3 circular array mounted on an aircraft

The Traffic advisory and Collision Avoidance System (TCAS) is being developed by the Federal Aviation Administration (FAA) to assist aircraft pilots in mid-air collision avoidance. This report concentrates on the computer simulation of the enchanced TCAS 2 systems mounted on a Boeing 727. First, the moment method is used to obtain an accurate model for the enhanced TCAS 2 antenna array. Then, the OSU Aircraft Code is used to generate theoretical radiation patterns of this model mounted on a simulated Boeing 727 model. Scattering error curves obtained from these patterns can be used to evaluate the performance of this system in determining the angular position of another aircraft with respect to the TCAS-equipped aircraft. Finally, the tracking of another aircraft is simulated when the TCAS-equipped aircraft follows a prescribed escape curve. In short, the computer models developed in this report have generality, completeness and yield reasonable results.

Rojas, R. G.↗

NASA NTRS2017

Interpretable Categorization of Heterogeneous Time Series Data

We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

Drones↗

NASA NTRS2015

An Updated Process for Automated Deepspace Conjunction Assessment

There is currently a high level of interest in the areas of conjunction assessment and collision avoidance from organizations conducting space operations. Current conjunction assessment activity is mainly focused on spacecraft and debris in the Earth orbital environment [1]. However, collisions are possible in other orbital environments as well [2]. This paper will focus on the current operations of and recent updates to the Multimission Automated Deep Space Conjunction Assessment Process (MADCAP) used at the Jet Propulsion Laboratory for NASA to perform conjunction assessment at Mars and the Moon. Various space agencies have satellites in orbit at Mars and the Moon with additional future missions planned. The consequences of collisions are catastrophically high. Intuitive notions predict low probability of collisions in these sparsely populated environments, but may be inaccurate due to several factors. Orbits of scientific interest often tend to have similar characteristics as do the orbits of spacecraft that provide a communications relay for surface missions. The MADCAP process is controlled by an automated scheduler which initializes analysis based on a set timetable or the appearance of new ephemeris files either locally or on the Deep Space Network (DSN) Portal. The process then generates and communicates reports which are used to facilitate collision avoidance decisions. The paper also describes the operational experience and utilization of the automated tool during periods of high activity and interest such as: the close approaches of NASA's Lunar Atmosphere & Dust Environment Explorer (LADEE) and Lunar Reconnaissance Orbiter (LRO) during the LADEE mission. In addition, special consideration was required for the treatment of missions with rapidly varying orbits and less reliable long term downtrack estimates; in particular this was necessitated by perturbations to MAVEN's orbit induced by the Martian atmosphere. The application of special techniques to non-operational spacecraft with large uncertainties is also studied. Areas for future work are also described. Although the applications discussed in this paper are in the Martian and Lunar environments, the techniques are not unique to these bodies and could be applied to other orbital environments.

collision↗

NASA NTRSDate not supplied

Exploring the Impact of Compliance With Maneuvering Guidelines for Space Traffic Management

If the current estimate of proposed large constellations is realized, the near-Earth space environment will see more than 50,000 new satellites added to the catalog of resident space objects (RSOs) in the coming decade. This is an order of magnitude increase from the current population and poses new policy challenges as global operators seek to leverage the benefits these new satellite systems provide while also ensuring a sustainable approach to collision avoidance. Various guidelines have been proposed to date to support this effort, including the development of right of way rules to guide how a collision avoidance maneuver should be performed, and how the maneuver burden should be shared between the two satellites involved. However, it is very difficult to evaluate and compare proposed guidelines due to the complex nature of space traffic and the rapidly changing space environment. This study seeks to address this issue by utilizing the Virtual Environment for Space Traffic Analysis (VESTA), a high-fidelity simulation tool that has been developed at Georgia Tech over the past few years with the explicit purpose of evaluating the future of space traffic environment. Using this tool, a sensitivity study is performed that incorporates a likely set of future large constellations and provides metrics on the impact that a select set of proposed maneuvering guidelines would have on operators given realistic variations in spacecraft capabilities (e.g. maneuverability and propulsion capabilities), and other factors (owner-country, public vs. private, etc.). Specifically, this study compares three potential right of way rules: 1) a rule based on maneuverability proposed by the Space Safety Coalition, 2) a rule based on the geometry of the spacecraft rendezvous, and 3) a rule that equally distributes the maneuver burden between two operators, The results highlight general observations on the effectiveness and limitations of each of the proposed maneuvering guidelines. In addition to the choice of right of way rule, success of space traffic management will be significantly impacted by compliance – which operators, or how many operators, comply with the space traffic rules. The findings of this analysis have important implications for future methods that could be pursued to put in place right of way rules. For example, non-binding right of way rules may have variable levels of compliance that differ across actors. The impact of compliance by just one nation, or non-compliance by just one nation, help to demonstrate the impact of ensuring all major space actors coordinate on this effort. Overall, this analysis provides insight into the relative gains in safety (decrease in collision risk) that would likely result from more politically intense efforts to increase the number of countries implementing space traffic management rules.

conjunction assessment↗

NASA NTRSDate not supplied

NASA CARA Prelaunch Analysis and Process

NASA implemented an official Procedural Requirement (NPR) 8079.1 in June 2023, establishing the minimum collision avoidance requirements and associated operational protocols for NASA space flight programs, projects, and spacecraft to protect the space environment by reducing the risk of collision to an acceptable level. Part of the requirement employs a two-fold approach to analyze the satellite design process with conjunction assessment and risk mitigation in mind, during the pre-launch process, led by the Conjunction Assessment Risk Analysis (CARA) Program for non-Human Space Flight (HSF) Missions. This presentation outlines CARA coordination with missions, informed by the NPR, that spans early mission development to operations. CARA is an Agency-level resource that provides support to all NASA non-HSF missions. CARA protects the orbital environment from collision between NASA non-HSF missions and other tracked on-orbit objects. During the pre-formulation and formulation phases, NASA missions undergo a series of conjunction assessment analyses captured in the Orbital Collision Avoidance Plan (OCAP) prior to transitioning to the implementation phase (typically at the Preliminary Design Review (PDR) or equivalent). The OCAP analyses consist of a thorough review of the spacecraft(s) orbit selection and placement, deployment, cataloguing performance, trackability, ephemeris generation, conjunction mitigation options, autonomous maneuvering, and risk assessment parameters which are performed by a dedicated CARA Analysis Team. The results of these analyses, CARA’s formal recommendations, and the mission’s methods for implementing them, are documented in the OCAP. The intent of engaging in this process so early in the mission design phase, is to ensure that conjunction assessment is considered from the outset, thus mitigating costly design changes and operational risks down the road. NASA missions are also required to coordinate their operational processes and conjunction mitigation procedures with CARA in a Conjunction Assessment Operations Implementation Agreement (CAOIA). The aim of this process is to document the conjunction assessment screening process, conjunction risk assessment parameters, conjunction mitigation steps, flight dynamics operations concepts and maneuvers, and the communication and coordination process between the mission’s project manager and CARA. The intent of the CAOIA document is for it to be completed iteratively, and as missions update these elements, corresponding changes are made in the CAOIA. With this process in place, the engagement and coordination between the missions and CARA from early in the design process into mission operations, helps to ensure that missions not only have a robust conjunction assessment concept of operations to reduce conjunction risk for space sustainability, but are also able to achieve their science goals and have a successful mission.

conjunction assessment↗

NASA NTRSDate not supplied

NASA CARA Prelaunch Analysis and Process

conjunction assessment↗