SEARCH · Search NASA

Results for “reference trajectory”

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 91 records · Page 5

All sources NASA NTRS DOE OSTI

NASA NTRS2016

Trajectory Specification for Automation of Terminal Air Traffic Control

"Trajectory specification" is the explicit bounding and control of aircraft tra- jectories such that the position at each point in time is constrained to a precisely defined volume of space. The bounding space is defined by cross-track, along-track, and vertical tolerances relative to a reference trajectory that specifies position as a function of time. The tolerances are dynamic and will be based on the aircraft nav- igation capabilities and the current traffic situation. A standard language will be developed to represent these specifications and to communicate them by datalink. Assuming conformance, trajectory specification can guarantee safe separation for an arbitrary period of time even in the event of an air traffic control (ATC) sys- tem or datalink failure, hence it can help to achieve the high level of safety and reliability needed for ATC automation. As a more proactive form of ATC, it can also maximize airspace capacity and reduce the reliance on tactical backup systems during normal operation. It applies to both enroute airspace and the terminal area around airports, but this paper focuses on arrival spacing in the terminal area and presents ATC algorithms and software for achieving a specified delay of runway arrival time.

air traffic control↗

NASA NTRS2008

Aerodynamics for the Mars Phoenix Entry Capsule

Pre-flight aerodynamics data for the Mars Phoenix entry capsule are presented. The aerodynamic coefficients were generated as a function of total angle-of-attack and either Knudsen number, velocity, or Mach number, depending on the flight regime. The database was constructed using continuum flowfield computations and data from the Mars Exploration Rover and Viking programs. Hypersonic and supersonic static coefficients were derived from Navier-Stokes solutions on a pre-flight design trajectory. High-altitude data (free-molecular and transitional regimes) and dynamic pitch damping characteristics were taken from Mars Exploration Rover analysis and testing. Transonic static coefficients from Viking wind tunnel tests were used for capsule aerodynamics under the parachute. Static instabilities were predicted at two points along the reference trajectory and were verified by reconstructed flight data. During the hypersonic instability, the capsule was predicted to trim at angles as high as 2.5 deg with an on-axis center-of-gravity. Trim angles were predicted for off-nominal pitching moment (4.2 deg peak) and a 5 mm off-axis center-ofgravity (4.8 deg peak). Finally, hypersonic static coefficient sensitivities to atmospheric density were predicted to be within uncertainty bounds.

Edquist, Karl T.↗

NASA NTRS2014

Trajectory Design for the Europa Clipper Mission Concept

Europa is one of the most scientifically intriguing targets in planetary science due to its potential suitability for extant life. As such, NASA has funded the California Institute of Technology Jet Propulsion Laboratory and the Johns Hopkins University Applied Physics Laboratory to jointly determine and develop the best mission concept to explore Europa in the near future. The result of nearly 4 years of work--the Europa Clipper mission concept--is a multiple Europa flyby mission that could efficiently execute a number of high caliber science investigations to meet Europa science priorities specified in the 2011 NRC Decadal Survey, and is capable of providing reconnaissance data to maximize the probability of both a safe landing and access to surface material of high scientific value for a future Europa lander. This paper will focus on the major enabling component for this mission concept--the trajectory. A representative trajectory, referred to as 13F7-A21, would obtain global-regional coverage of Europa via a complex network of 45 flybys over the course of 3.5 years while also mitigating the effects of the harsh Jovian radiation environment. In addition, 5 Ganymede and 9 Callisto flybys would be used to manipulate the trajectory relative to Europa. The tour would reach a maximum Jovicentric inclination of 20.1 deg. have a deterministic (Delta)V of 164 m/s (post periapsis raise maneuver), and a total ionizing dose of 2.8 Mrad (Si).

orbital mechanics↗

NASA NTRS1999

Autolanding Trajectory Design for the X-34

An Autolanding I-load Program (ALIP) is developed to design unpowered autolanding trajectories for the X-34 Mach 8 vehicle. The trajectory is comprised of geometric flight segments that are based on the shuttle approach and landing design (steep glideslope, circular flare, exponential flare to shallow glideslope). Enforcing physical constraints such as loads, vertical descent rate, continuity and smoothness reduces the design problem to a two point boundary value problem with conditions on the initial and final dynamic pressure. Finding a solution required the development of trajectory simulation techniques that constrained the flight profile to a prescribed geometry. The design methodology can be extended beyond the autolanding flight regime by repeating the series of geometric segments and solving multiple two-point boundary values problems (one for each series). The techniques described in this paper facilitate rapid design of reference trajectories.

Barton, Gregg H.↗

NASA NTRSDate not supplied

Evaluating Lunar Descent and Landing Performance From a Near Rectilinear Halo Orbit Using Linear Covariance Resetting Techniques

Upcoming lunar programs are striving the achieve precision landing in a safe and robust manner. Various elements impact this mission objective ranging from on-orbit operations with ground station tracking to incorporating relative sensors with hazard detection and avoidance (HDA) to support the final approach and landing phase. Modeling the impacts of ground tracking, trajectory replanning, relative navigation sensors, and particularly a potential HDA system on the integrated closed-loop GN\&C system performance poses a unique challenge due to the complexity and interaction with multiple facets of the vehicle including the trajectory design, sensing hardware, navigation system, guidance and targeting, and the overall mission concept of operations. This paper outlines techniques to systematically analyze and compare the performance impacts of ground tracking and replanning and an HDA system where the onboard navigation errors are reset or uploaded from an external source and the vehicle's reference trajectory is regenerated requiring the system dispersions to also be reset to reflect this in-flight profile adjustment. To illustrate the application of these general techniques for analyzing the performance impacts due to incorporating these resetting events, they are demonstrated with a human lunar descent and landing scenario starting from a near rectilinear halo orbit (NRHO) until the vehicle precisely reaches its predetermined landing site on the lunar surface. Performance metrics such as inertial and relative navigation errors, trajectory dispersions, footprint dispersions, and propellant usage are provided.

GN&C↗

NASA NTRS1987

Design and analysis of advanced flight planning concepts

The objectives of this continuing effort are to develop and evaluate new algorithms and advanced concepts for flight management and flight planning. This includes the minimization of fuel or direct operating costs, the integration of the airborne flight management and ground-based flight planning processes, and the enhancement of future traffic management systems design. Flight management (FMS) concepts are for on-board profile computation and steering of transport aircraft in the vertical plane between a city pair and along a given horizontal path. Flight planning (FPS) concepts are for the pre-flight ground based computation of the three-dimensional reference trajectory that connects the city pair and specifies the horizontal path, fuel load, and weather profiles for initializing the FMS. As part of these objectives, a new computer program called EFPLAN has been developed and utilized to study advanced flight planning concepts. EFPLAN represents an experimental version of an FPS. It has been developed to generate reference flight plans compatible as input to an FMS and to provide various options for flight planning research. This report describes EFPLAN and the associated research conducted in its development.

Sorensen, John A.↗

NASA NTRS2012

EUROPA Multiple-Flyby Trajectory Design

As reinforced by the 2011 NRC Decadal Survey, Europa remains one of the most scientifically intriguing targets in planetary science due to its potential suitability for life. However, based on JEO cost estimates and current budgetary constraints, the Decadal Survey recommended-and later directed by NASA Headquarters-a more affordable pathway to Europa exploration be derived. In response, a flyby-only proof-of-concept trajectory has been developed to investigate Europa. The trajectory, enabled by employing a novel combination of new mission design techniques, successfully fulfills a set of Science Definition Team derived scientific objectives carried out by a notional payload including ice penetrating radar, topographic imaging, and short wavelength infrared observations, and ion neutral mass spectrometry in-situ measurements. The current baseline trajectory, referred to as 11-F5, consists of 34 Europa and 9 Ganymede flybys executed over the course of 2.4 years, reached a maximum inclination of 15 degrees, has a deterministic delta v of 157 m/s (post-PJR), and has a total ionizing dose of 2.06 Mrad (Si behind 100 mil Al, spherical shell). The 11-F5 trajectory and more generally speaking, flyby-only trajectories-exhibit a number of potential advantages over an Europa orbiter mission.

Europa↗

NASA NTRSDate not supplied

Optimized Trajectory Correction Burn Placement for NRHO Orbit Maintenance

NASA's future Artemis missions plan to utilize a near rectilinear halo orbit (NRHO) in the lunar vicinity to facilitate access to the lunar surface and place other critical assets to support human exploration. This exploration architecture requires a vehicle to remain in the NRHO for long periods of time ranging from several days, to weeks, to months, and even years. Consequently, periodic orbit maintenance burns become essential to ensure the spacecraft follows the desired reference trajectory in an efficient yet effective manner despite crew activity, navigation uncertainty, maneuver execution errors, disturbance accelerations, orbit insertion dispersions, and other system limitations. This work introduces a targeting algorithm that can be utilized to analyze a variety of targeting constraints and parameters that maximizes overall performance. Techniques associated with robust trajectory optimization are used to identify the optimized number and placement for NRHO trajectory correction (NTC) burns that accounts for the mission schedule, both a primary and backup navigation system, targeting strategies and burn plan configurations, vehicle venting, thruster selection, and integrated GN\&C performance. A notional scenario extracted from the NASA Artemis III mission is used to motivate and demonstrate these concepts and performance results.

Linear Covariance Analysis↗

NASA NTRSDate not supplied

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth-Moon system. Using Multi-Reward Proximal Policy Optimization, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Christopher J Sullivan↗

NASA NTRS2021

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth- Moon system. Using Multi-Reward Proximal Policy Optimiza- tion, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Mashiku, Alinda K.↗

NASA NTRS2007

Preliminary Performance Analyses of the Constellation Program ARES 1 Crew Launch Vehicle

By the time NASA's Exploration Systems Architecture Study (ESAS) report had been released to the public in December 2005, engineers at NASA's Marshall Space Flight Center had already initiated the first of a series of detailed design analysis cycles (DACs) for the Constellation Program Crew Launch Vehicle (CLV), which has been given the name Ares I. As a major component of the Constellation Architecture, the CLV's initial role will be to deliver crew and cargo aboard the newly conceived Crew Exploration Vehicle (CEV) to a staging orbit for eventual rendezvous with the International Space Station (ISS). However, the long-term goal and design focus of the CLV will be to provide launch services for a crewed CEV in support of lunar exploration missions. Key to the success of the CLV design effort and an integral part of each DAC is a detailed performance analysis tailored to assess nominal and dispersed performance of the vehicle, to determine performance sensitivities, and to generate design-driving dispersed trajectories. Results of these analyses provide valuable design information to the program for the current design as well as provide feedback to engineers on how to adjust the current design in order to maintain program goals. This paper presents a condensed subset of the CLV performance analyses performed during the CLV DAC-1 cycle. Deterministic studies include development of the CLV DAC-1 reference trajectories, identification of vehicle stage impact footprints, an assessment of launch window impacts to payload performance, and the computation of select CLV payload partials. Dispersion studies include definition of input uncertainties, Monte Carlo analysis of trajectory performance parameters based on input dispersions, assessment of CLV flight performance reserve (FPR), assessment of orbital insertion accuracy, and an assessment of bending load indicators due to dispersions in vehicle angle of attack and side slip angle. A short discussion of the various customers for the dispersion results, along with results and ramifications of each study, are also provided.

Phillips, Mark↗

NASA NTRSDate not supplied

MULTI-OBJECTIVE REINFORCEMENT LEARNING FOR LOW-THRUST TRANSFER DESIGN BETWEEN LIBRATION POINT ORBITS

Multi-Reward Proximal Policy Optimization (MRPPO) is a multi-objective reinforcement learning algorithm used to construct low-thrust transfers between periodic orbits in multi-body systems. Previous implementations of MRPPO have relied on a predefined reference transfer to successfully train each policy. In this paper, an algorithmic modification labeled the ‘moving reference’, is introduced to autonomously construct these reference trajectories during training. With this modification, MRPPO is used to recover various low-thrust transfers between two periodic orbits in the Earth-Moon circular restricted three-body problem to solve a multi-objective optimization problem. These results are then compared with the solutions recovered via a gradient descent optimization scheme to validate the performance of MRPPO with the moving reference modification.

Christopher J. Sullivan↗

NASA NTRSDate not supplied

MULTI-OBJECTIVE REINFORCEMENT LEARNING FOR LOW-THRUST TRANSFER DESIGN BETWEEN LIBRATION POINT ORBITS

Christopher John Sullivan↗

NASA NTRS2021

Multi-objective Reinforcement Learning for Low-thrust Transfer Design Between Libration Point Orbits

Multi-Reward Proximal Policy Optimization (MRPPO) is a multi-objective rein- forcement learning algorithm used to construct low-thrust transfers between pe- riodic orbits in multi-body systems. Previous implementations of MRPPO have relied on a predefined reference transfer to successfully train each policy. In this paper, an algorithmic modification labeled the ‘moving reference’, is introduced to autonomously construct these reference trajectories during training. With this modification, MRPPO is used to recover various low-thrust transfers between two periodic orbits in the Earth-Moon circular restricted three-body problem to solve a multi-objective optimization problem. These results are then compared with the solutions recovered via a gradient descent optimization scheme to validate the performance of MRPPO with the moving reference modification.

Anderson, Rodney L.↗

NASA NTRS2021

Multi-objective Reinforcement Learning for Low-thrust Transfer Design Between Libration Point Orbits

Anderson, Rodney L↗

NASA NTRS2008

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

autonomuys vehicles↗

NASA NTRS1961

A Method for Longitudinal and Lateral Range Control for a High-Drag Low-Lift Vehicle Entering the Atmosphere of a Rotating Earth

A study has been made of a method for controlling the trajectory of a high-drag low-lift entry vehicle to a desired longitude and latitude on the surface of a rotating earth. By use of this control technique the vehicle can be guided to the desired point when the present position and heading of the vehicle are known and the desired longitude and latitude are specified. The present study makes use of a single reference trajectory and an estimate of the lift and side-force capabilities of the vehicle. This information is stored in a control-logic system and used with linear control equations to guide the vehicle to the desired destination. Results are presented of a number of trajectory studies which describe the operation of the control system and illustrate its ability to control the vehicle trajectory to the desired landing area.

Young, John W.↗

NASA NTRSDate not supplied

Mission Planning and Trajectory Design of Roundtrip Mars Transfers

NASA’s Exploration Systems Development Mission Directorate has been evaluating architecture concepts that can deliver crew and cargo to Mars vicinity and return the crew safely back to Earth. A series of trade studies and sensitivity analyses are performed to explore the trade space in an effort to inform the decision of the transportation architecture for future human missions to Mars. This paper documents the tools and methods used to perform mission scans for systems that use high-thrust propulsion and provides discussion on some interesting challenges for the roundtrip transportation architecture. Results for the reference trajectories from the current analysis cycle are presented.

Mars↗