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At least 253 records · Page 14

Interplanetary Departure Stage Navigation by Means of Liaison Orbit Determination Architecture

Autonomous orbit determination for departure stages of interplanetary trajectories is conducted by means of realistic radiometric observations between the departing spacecraft and a satellite orbiting the first lunar libration point. Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is used to estimate the orbit solution. This paper uses high-fidelity simulations to explore the utilization of LiAISON in providing improved accuracy for interplanetary departure missions. The use of autonomous navigation to supplement current techniques for interplanetary spacecraft is assessed using comparisons with groundbased navigation. Results from simulations including the Mars Science Laboratory, Mars Exploration Rover, and Cassini are presented. It is shown that observations from a dedicated LiAISON navigation satellite could be used to supplement ground-based measurements and significantly improve tracking performance.

Linked Autonomous Interplanetary Satellite Orbit N↗

Machine Learning Based Crater Detection for Terrain Relative Navigation

As Lunar exploration continues to become more commonplace, reliable methods of precise Terrain Relative Navigation (TRN) are needed. While there are many TRN techniques available, one that has received increased interest in the past few years is that of crater based navigation. Crater based navigation has numerous benefits, including being a human recognizable feature (important for crewed missions), as well as the fact that craters are often possible hazards that need to be detected and avoided. The use of crater based navigation has been limited however. This has been due to the difficulty of running such algorithms on board a spacecraft, as well as the difficulty in procuring large amounts of the required training data. This paper presents a new rendering tool for generating large amounts of high quality training data. It then looks at two recently developed machine learning techniques for crater detection and crater identification in real-time on near-future space hardware.

computer vision↗

A STATISTICAL OPTIMIZING NAVIGATION PROCEDURE FOR SPACE FLIGHT

In a typical self-contained space navigation system, celestial observation data are gathered and processed to produce estimated velocity corrections. The results of this paper provide a basis for determining the best celestial measurements and the proper time s to implement velocity corrections. Fundamental to the navigation system is a procedure for processing celestial measurement data which permits incorporation of each individual measurement as it is made in order to provide an improved estimate of position and velocity. In order to "optimize" the navigation, a statistical evaluation of a number of alternative courses of action is made. The various alternatives, which form the basis of a decision process, concern the following: 1) which star and planet combination provides the "best" available observation; 2) whether the best observation gives a sufficient reduction in the predicted target error to warrant making the measurement; and 3) whether the uncertainty in the indicated velocity correction is a small enough percentage of the correction itself to justify an engine re-start and propellant expenditure. Numerical results are presented which illustrate the effectiveness of this approach to the space navigation problem.

NAVIGATION↗

The JPL roadmap for Deep Space navigation

This paper reviews the tentative set of deep space missions that will be supported by NASA's Deep Space Mission System in the next twenty-five years, and extracts the driving set of navigation capabilities that these missions will require. There will be many challenges including the support of new mission navigation approaches such as formation flying and rendezvous in deep space, low-energy and low-thrust orbit transfers, precise landing and ascent vehicles, and autonomous navigation. Innovative strategies and approaches will be needed to develop and field advanced navigation capabilities.

navigation↗

Mars Exploration Rovers navigation results

The twin Mars Exploration Rovers, Spirit and Opportunity, were launched on June 10, 2003(dagger), and July 8, 2003, from Cape Canaveral, Florida. Spirit and Opportunity were targeted for landings at Gusev Crater (arrival on January 4, 2004) and Meridiani Planum (arrival on January 25, 2004). The primary navigation challenge was to deliver each spacecraft to the desired atmospheric entry interface point with sufficient accuracy such that each lander would touch down within a specified landing ellipse (about 70 km x 5 km) determined to be safe for landing and also judged to be scientifically interesting. In order to achieve landing within the target ellipse, precise control of the inertial entry flight path angle (FPA) at atmospheric entry was required. The maximum allowable errors in FPA following TCM-5 (trajectory correction maneuver #5) at Entry (E) - 2 days were +/-0.12(deg) (3(sigma)) for Spirit and +/-0.14(deg) (3(sigma)) for Opportunity. Achieving these entry delivery accuracies necessitated significant improvements to the interplanetary avigation system used for MER. These improvements included new processes and software for orbit determination, propulsive maneuver design, and entry, descent, and landing (EDL) trajectory simulation. The actual achieved atmospheric entry accuracies for Spirit and Opportunity significantly exceeded the requirements. At the navigation data cutoff for the TCM-5 final design, the orbit determination FPA knowledge error was +/-0.028(deg) (3(sigma) ) for Spirit and +/-0.035(deg) (3(sigma)) for Opportunity. Because of exceptionally accurate navigation performance, TCM-5 (E - 2 days) and TCM-6 (E - 4 hours) were canceled for both Spirit and Opportunity. The actual landing locations (determined from in-situ Doppler tracking between the MER rovers and the Mars Odyssey orbiter) differed from the target landing points by 10.1 km (downtrack) for Spirit and 24.6 km (downtrack) for Opportunity. The majority of the landing position offsets for both landers was primarily caused by variations in atmosphere and spacecraft aerodynamic modeling from what was predicted. The amount of the landing position offset caused by navigation-only errors was only 3.3 km (uptrack) for Spirit and 9.7 km (downtrack) for Opportunity.

Mars Exploration Rover (MER)↗

Mars Reconnaissance Orbiter Navigation

Mars Reconnaissance Orbiter will launch in August 2005 at Cape Canaveral Air Force Station. The heavyweight spacecraft will use a Lockheed-Martin Atlas V-401 launch vehicle. It will be the first mission in a low Mars Orbit to characterize the surface, subsurface, and atmospheric properties. The intensive science operation imposes a great challenge for Navigation to satisfy the stringent requirements. This paper describes navigation key requirements, major challenges, and the sophisticated dynamic modeling. It also details navigation strategy and processes for various mission phases. Mars Reconnaissance Orbiter will return significant amount of scientific data in support of the objectives set by the Mars Exploration Program. A robust and precise navigation is the key to the success of this mission.

navigation↗

Overview of Terrain Relative Navigation Approaches for Precise Lunar Landing

The driving precision landing requirement for the Autonomous Landing and Hazard Avoidance Technology project is to autonomously land within 100m of a predetermined location on the lunar surface. Traditional lunar landing approaches based on inertial sensing do not have the navigational precision to meet this requirement. The purpose of Terrain Relative Navigation (TRN) is to augment inertial navigation by providing position or bearing measurements relative to known surface landmarks. From these measurements, the navigational precision can be reduced to a level that meets the 100m requirement. There are three different TRN functions: global position estimation, local position estimation and velocity estimation. These functions can be achieved with active range sensing or passive imaging. This paper gives a survey of many TRN approaches and then presents some high fidelity simulation results for contour matching and area correlation approaches to TRN using active sensors. Since TRN requires an a-priori reference map, the paper concludes by describing past and future lunar imaging and digital elevation map data sets available for this purpose.

Terrain Relative Navigation (TRN)↗

Autonomous Navigation for Deep Space Missions

Navigation (determining where the spacecraft is at any given time, controlling its path to achieve desired targets), performed using ground-in- the-loop techniques: (1) Data includes 2-way radiometric (Doppler, range), interferometric (Delta- Differential One-way Range), and optical (images of natural bodies taken by onboard camera) (2) Data received on the ground, processed to determine orbit, commands sent to execute maneuvers to control orbit. A self-contained, onboard, autonomous navigation system can: (1) Eliminate delays due to round-trip light time (2) Eliminate the human factors in ground-based processing (3) Reduce turnaround time from navigation update to minutes, down to seconds (4) React to late-breaking data. At JPL, we have developed the framework and computational elements of an autonomous navigation system, called AutoNav. It was originally developed as one of the technologies for the Deep Space 1 mission, launched in 1998; subsequently used on three other spacecraft, for four different missions. The primary use has been on comet missions to track comets during flybys, and impact one comet.

navigation↗

Addressing the Influence of Space Weather on Airline Navigation

The advent of satellite-based augmentation systems has made it possible to navigate aircraft safely using radio signals emitted by global navigation satellite systems (GNSS) such as the Global Positioning System. As a signal propagates through the earth's ionosphere, it suffers delay that is proportional to the total electron content encountered along the raypath. Since the magnitude of this total electron content is strongly influenced by space weather, the safety and reliability of GNSS for airline navigation requires continual monitoring of the state of the ionosphere and calibration of ionospheric delay. This paper examines the impact of space weather on GNSS-based navigation and provides an overview of how the Wide Area Augmentation System protects its users from positioning error due to ionospheric disturbances

airline navigation↗

SEXTANT - Station Explorer for X-Ray Timing and Navigation Technology

The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a NASA funded technology- demonstration. SEXTANT will, for the first time, demonstrate real-time, on-board X-ray Pulsar-based Navigation (XNAV), a significant milestone in the quest to establish a GPS-like navigation capability available throughout our Solar System and beyond. This paper describes the basic design of the SEXTANT system with a focus on core models and algorithms, and the design and continued development of the GSFC X-ray Navigation Laboratory Testbed (GXLT) with its dynamic pulsar emulation capability. We also present early results from GXLT modeling of the combined NICER X-ray timing instrument hardware and SEXTANT flight software algorithms.

X-rays↗

SEXTANT - Station Explorer for X-ray Timing and Navigation Technology

The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a technology demonstration enhancement to the Neutron-star Interior Composition Explorer (NICER) mission, which is scheduled to launch in late 2016 and will be hosted as an externally attached payload on the International Space Station (ISS) via the ExPRESS Logistics Carrier (ELC). During NICER's 18-month baseline science mission to understand ultra-dense matter though observations of neutron stars in the soft X-ray band, SEXTANT will, for the first-time, demonstrate real-time, on-board X-ray pulsar navigation, which is a significant milestone in the quest to establish a GPS-like navigation capability that will be available throughout our Solar System and beyond. Along with NICER, SEXTANT has proceeded through Phase B, Mission Definition, and received numerous refinements in concept of operation, algorithms, flight software, ground system, and ground test capability. NICER/SEXTANT's Phase B work culminated in NASA's confirmation of NICER to Phase C, Design and Development, in March 2014. Recently, NICER/SEXTANT successfully passed its Critical Design Review and SEXTANT received continuation approval in September 2014. In this paper, we describe the X-ray pulsar navigation concept and provide a brief history of previous work, and then summarize the SEXTANT technology demonstration objective, hardware and software components, and development to date.

X-rays↗

The Deep Space Atomic Clock: Ushering in a New Paradigm for Radio Navigation and Science

The Deep Space Atomic Clock (DSAC) mission will demonstrate the on-orbit performance of a high-accuracy, high-stability miniaturized mercury ion atomic clock during a year-long experiment in Low Earth Orbit. DSAC's timing error requirement provides the frequency stability necessary to perform deep space navigation based solely on one-way radiometric tracking data. Compared to a two-way tracking paradigm, DSAC-enabled one-way tracking will benefit navigation and radio science by increasing the quantity and quality of tracking data. Additionally, DSAC also enables fully-autonomous onboard navigation useful for time-sensitive situations. The technology behind the mercury ion atomic clock and a DSAC mission overview are presented. Example deep space applications of DSAC, including navigation of a Mars orbiter and Europa flyby gravity science, highlight the benefits of DSAC-enabled one-way Doppler tracking.

atomic clock↗

SEXTANT X-Ray Pulsar Navigation Demonstration: Flight System and Test Results

The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a technology demonstration enhancement to the Neutron-star Interior Composition Explorer (NICER) mission. NICER is a NASA Explorer Mission of Opportunity that will be hosted on the International Space Station (ISS). SEXTANT will, for the first time, demonstrate real-time, on-board X-ray Pulsar Navigation (XNAV), a significant milestone in the quest to establish a GPS-like navigation capability available throughout our Solar System and beyond. This paper gives an overview of the SEXTANT system architecture and describes progress prior to environmental testing of the NICER flight instrument. It provides descriptions and development status of the SEXTANT flight software and ground system, as well as detailed description and results from the flight software functional and performance testing within the highfidelity Goddard Space Flight Center (GSFC) X-ray Navigation Laboratory Testbed (GXLT) software and hardware simulation environment. Hardware-in-the-loop simulation results are presented, using the engineering model of the NICER timing electronics and the GXLT pulsar simulator-the GXLT precisely controls NASA GSFC's unique Modulated X-ray Source to produce X-rays that make the NICER detector electronics appear as if they were aboard the ISS viewing a sequence of millisecond pulsars.

SEXTANT↗

SEXTANT X-Ray Pulsar Navigation Demonstration: Flight System and Test Results

The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a technology demonstration enhancement to the Neutron-star Interior Composition Explorer (NICER) mission. NICER is a NASA Explorer Mission of Opportunity that will be hosted on the International Space Station (ISS). SEXTANT will, for the first time, demonstrate real-time, on-board X-ray Pulsar Navigation (XNAV), a significant milestone in the quest to establish a GPS-like navigation capability available throughout our Solar System and beyond. This paper gives an overview of the SEXTANT system architecture and describes progress prior to environmental testing of the NICER flight instrument. It provides descriptions and development status of the SEXTANT flight software and ground system, as well as detailed description and results from the flight software functional and performance testing within the high-fidelity Goddard Space Flight Center (GSFC) X-ray Navigation Laboratory Testbed (GXLT) software and hardware simulation environment. Hardware-in-the-loop simulation results are presented, using the engineering model of the NICER timing electronics and the GXLT pulsar simulator-the GXLT precisely controls NASA GSFC's unique Modulated X-ray Source to produce X-rays that make the NICER detector electronics appear as if they were aboard the ISS viewing a sequence of millisecond pulsars

Pulsar↗

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation↗

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Registration↗

Integrating Communication and Navigation: Next Generation Broadcast Service (NGBS)

NASA Goddard has been investing in technology demonstrations of a beacon service, now called Next Generation Broadcast Services (NGBS). NGBS is a global, space-based, communications and navigation service for users of Global Navigation Satellite Systems (GNSS) and the Tracking and Data Relay Satellite System (TDRSS). NGBS will provide an S-band beacon messaging source and radio navigation available to users at orbital altitudes 1400 km and below, increasing the autonomy and resiliency of onboard communication and navigation. NGBS will deliver both one-way radiometric (Doppler and pseudorange) and fast forward data transport services to users. Portions of the overall forward data volume will be allocated for fixed message types while the remaining data volume will be left for user forward command data. The NGBS signal will reside within the 2106.43 MHz spectrum currently allocated for the Space Networks multiple access forward (MAF) service and a live service demonstration is currently being planned via the 2nd and 3rd generation TDRS satellites.

Navigation↗

Lessons Learned from OSIRIS-Rex Autonomous Navigation Using Natural Feature Tracking

The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (Osiris-REx) spacecraft is scheduled to launch in September, 2016 to embark on an asteroid sample return mission. It is expected to rendezvous with the asteroid, Bennu, navigate to the surface, collect a sample (July 20), and return the sample to Earth (September 23). The original mission design called for using one of two Flash Lidar units to provide autonomous navigation to the surface. Following Preliminary design and initial development of the Lidars, reliability issues with the hardware and test program prompted the project to begin development of an alternative navigation technique to be used as a backup to the Lidar. At the critical design review, Natural Feature Tracking (NFT) was added to the mission. NFT is an onboard optical navigation system that compares observed images to a set of asteroid terrain models which are rendered in real-time from a catalog stored in memory on the flight computer. Onboard knowledge of the spacecraft state is then updated by a Kalman filter using the measured residuals between the rendered reference images and the actual observed images. The asteroid terrain models used by NFT are built from a shape model generated from observations collected during earlier phases of the mission and include both terrain shape and albedo information about the asteroid surface. As a result, the success of NFT is highly dependent on selecting a set of topographic features that can be both identified during descent as well as reliably rendered using the shape model data available. During development, the OSIRIS-REx team faced significant challenges in developing a process conducive to robust operation. This was especially true for terrain models to be used as the spacecraft gets close to the asteroid and higher fidelity models are required for reliable image correlation. This paper will present some of the challenges and lessons learned from the development of the NFT system which includes not just the flight hardware and software but the development of the terrain models used to generate the onboard rendered images.

Navigation↗