Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Navigation”

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.

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

At least 703 records · Page 39

Optical navigation planning process for the Cassini Solstice Mission

During the Cassini Equinox Mission, the Optical Navigation strategy has gradually evolved toward maintenance of an acceptable level of uncertainty on the positions of the bodies to be observed. By counteracting the runoff of the uncertainty over time, this strategy helps satisfy the spacecraft pointing requirements throughout the Solstice Mission, while considerably reducing the required imaging frequency. Requirements for planning observations were established, and the planning process itself was largely automated to facilitate re-planning if it becomes necessary. This paper summarizes the process leading to the optical navigation schedule for the seven years of the Solstice Mission.

Cassini↗

Engineering a Multimission Approach to Navigation Ground Data System Operations

The Mission Design and Navigation (MDNAV) Section at the Jet Propulsion Laboratory (JPL) supports many deep space and earth orbiting missions from formulation to end of mission operations. The requirements of these missions are met with a multimission approach to MDNAV ground data system (GDS) infrastructure capable of being shared and allocated in a seamless and consistent manner across missions. The MDNAV computing infrastructure consists of compute clusters, network attached storage, mission support area facilities, and desktop hardware. The multimission architecture allows these assets, and even personnel, to be leveraged effectively across the project lifecycle and across multiple missions simultaneously. It provides a more robust and capable infrastructure to each mission than might be possible if each constructed its own. It also enables a consistent interface and environment within which teams can conduct all mission analysis and navigation functions including: trajectory design; ephemeris generation; orbit determination; maneuver design; and entry, descent, and landing analysis. The savings of these efficiencies more than offset the costs of increased complexity and other challenges that had to be addressed: configuration management, scheduling conflicts, and competition for resources. This paper examines the benefits of the multimission MDNAV ground data system infrastructure, focusing on the hardware and software architecture. The result is an efficient, robust, scalable MDNAV ground data system capable of supporting more than a dozen active missions at once.

Mission Design and Navigation (MDNAV)↗

LiAISON-Supplemented Navigation for Geosynchronous and Lunar L1 Orbiter

A high-fidelity simulation is developed to test the theory that relative range and range-rate measurements between a satellite in a geosynchronous orbit and a satellite in orbit about the Earth-Moon L1 point may be used to improve the navigation accuracy of both satellites, compared with ground-only tracking. Recent research has determined that satellite-to-satellite range measurements between these two orbits are su cient to perform absolute state estimation as well as relative state estimation of both satellites - a technology known as LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation). This study quanties the improvement in accuracy when LiAISON is used to supplement ground tracking of one or both satellites in a very realistic simulation. Orbit determination techniques show that the inclusion of LiAISON measurements with ground tracking observations can greatly improve absolute position and velocity estimates for both satellites in geosynchronous orbit and about the Earth-Moon L1 point.

satellite-to-satellite tracking (SST)↗

Raven: An On-Orbit Relative Navigation Demonstration Using International Space Station Visiting Vehicles

Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.

Rendezvous↗

Navigation Challenges in the MAVEN Science Phase

The MAVEN spacecraft will explore Mars' upper atmosphere. The primary science phase will last one (Earth) year, during which the spacecraft will be in an elliptical 4.5 hour orbit at an inclination of 75 degrees. The 75 degree inclination results in the orbit periapsis oscillating between +/-75 degrees latitude, thus naturally covering most Mars latitudes during the primary mission. The orbit will be controlled via maneuvers so that the maximum orbit density remains in a density corridor. This results in the MAVEN science phase being in a light aerobraking type orbit of around 160 km for an extended period. In addition, the mission has significantly less tracking data than aerobraking phases of other missions, and even less than other NASA Mars orbiter primary phases. This results in significant challenges for the Navigation Team. They can be summarized as a difficulty in determining the current density profile, which maps into degraded trajectory predictions and less accurate control over the spacecraft location in the targeted density corridor via maneuvers. This paper describes these challenges and the Navigation Team's plans to meet them.

MAVEN↗

Mars Science Laboratory Navigation Results

The Mars Science Laboratory (MSL), carrying the Curiosity rover to Mars, was launched on November 26, 2011, from Cape Canaveral, Florida. The target for MSL was selected to be Gale Crater, near the equator of Mars, with an arrival date in early August 2012. The two main interplanetary navigation tasks for the mission were to deliver the spacecraft to an entry interface point that would allow the rover to safely reach the landing area, and to tell the spacecraft where it entered the atmosphere of Mars, so it could guide itself accurately to close proximity of the landing target. MSL used entry guidance as it slowed down from the entry speed to a speed low enough to allow for a successful parachute deployment, and this guidance allowed shrinking the landing ellipse to a 99% conservative estimate of 7 by 20 kilometers. Since there is no global positioning system in Mars, achieving this accuracy was predicated on flying a trajectory that closely matched the reference trajectory used to design the guidance algorithm, and on initializing the guidance system with an accurate Mars-relative entry state that could be used as the starting point to integrate the inertial measurement unit data during entry and descent. The pre-launch entry flight path angle (EFPA) delivery requirement was +/- 0.20 deg, but after launch a smaller threshold of +/- 0.05 deg was used as the criteria for late trajectory correction maneuver (TCM) decisions. The pre-launch requirement for entry state knowledge was 2.8 kilometers in position error and 2 meters per second in velocity error, but also smaller thresholds were defined after launch to evaluate entry state update opportunities. The biggest challenge for the navigation team was to accurately predict the trajectory of the spacecraft, so the estimates of the entry conditions could be stable, and late trajectory correction maneuvers or entry parameter updates could be waved off. As a matter of fact, the prediction accuracy was such that the last TCM performed was a small burn executed eight days before landing, and the entry state that was calculated just 36 hours after that TCM, and that was uploaded to the spacecraft the same day, did not need to be updated. The final EFPA was 0.013 deg shallower than the -15.5 deg target, and the on-board entry state was just 200 meters in position and 0.11 meters per second in velocity from the post-landing reconstructed entry state. Overall the entry delivery and knowledge requirements were fulfilled with a margin of more than 90% with respect to the pre-launch thresholds. This excellent accuracy contributed to a very successful and accurate entry, descent, and landing, and surface mission.

navigation↗

Safe Maritime Navigation with COLREGS Using Velocity Obstacles

This paper presents a motion planning algorithm for Unmanned Surface Vehicles (USVs) to navigate safely in dynamic, cluttered environments. The proposed algorithm not only addresses Hazard Avoidance (HA) for stationary and moving hazards but also applies the International Regulations for Preventing Collisions at Sea (known as COLREGs). The COLREG rules specify, for example, which vessel is responsible for giving way to the other and to which side of the "stand-on" vessel to maneuver. The three primary COLREG rules were considered in this paper: crossing, overtaking, and head-on situations. For USVs to be safely deployed in environments with other traffic boats, it is imperative that the USV's navigation algorithm obey COLREGs. Note also that if other boats disregard their responsibility under COLREGs, the USV will still apply its HA algorithms to avoid a collision. The proposed approach is based on Velocity Obstacles, which generates a cone-shaped obstacle in the velocity space. Because Velocity Obstacles also specify which side of the obstacle the vehicle will pass during the avoidance maneuver, COLREGs are encoded in the velocity space in a natural way. The algorithm is demonstrated via both simulation and on-water tests.

velocity obstacles↗

Navigation of the EPOXI Spacecraft to Comet Hartley 2

On November 4, 2010, the EPOXI spacecraft flew by the comet Hartley 2, marking the fourth time that a NASA spacecraft successfully captured high resolution images of a cometary nucleus. EPOXI is the extended mission of the Deep Impact mission, which delivered an impactor on comet Tempel-1 on July 4, 2005. EPOXI officially started in September 2007 and eventually took over 3 years of flight time and had 3 Earth gravity assists to achieve the proper encounter conditions. In the process, the mission was redesigned to accommodate a new comet as the target and changes in the trajectory to achieve better imaging conditions at encounter. Challenges in navigation of the spacecraft included precision targeting of several Earth flybys and the comet encounter, uncertainties in determining the ephemeris of the comet relative to the spacecraft, and the high accuracy trajectory knowledge needed to image the comet during the encounter. This paper presents an overview of the navigation process used for the mission.

Deep Impact (DI)↗

Performance Characterization of a Landmark Measurement System for ARRM Terrain Relative Navigation

This paper describes the landmark measurement system being developed for terrain relative navigation on NASAs Asteroid Redirect Robotic Mission (ARRM),and the results of a performance characterization study given realistic navigational and model errors. The system is called Retina, and is derived from the stereo-photoclinometry methods widely used on other small-body missions. The system is simulated using synthetic imagery of the asteroid surface and discussion is given on various algorithmic design choices. Unlike other missions, ARRMs Retina is the first planned autonomous use of these methods during the close-proximity and descent phase of the mission.

Guidance↗

Performance Characterization of a Landmark Measurement System for ARRM Terrain Relative Navigation

This paper describes the landmark measurement system being developed for terrain relative navigation on NASAs Asteroid Redirect Robotic Mission (ARRM),and the results of a performance characterization study given realistic navigational and model errors. The system is called Retina, and is derived from the stereophotoclinometry methods widely used on other small-body missions. The system is simulated using synthetic imagery of the asteroid surface and discussion is given on various algorithmic design choices. Unlike other missions, ARRMs Retina is the first planned autonomous use of these methods during the close-proximity and descent phase of the mission.

Navigation↗

Navigational Challenges for a Europa Flyby Mission

Jupiter's moon Europa is a prime candidate in the search for present-day habitable environments outside of the Earth. A number of missions have provided increasingly detailed images of the complex surface of Europa, including the Galileo mission, which also carried instruments that allowed for a limited investigation of the environment of Europa. A new mission to Europa is needed to pursue these exciting discoveries using close-up observations with modern instrumentation designed to address the habitability of Europa. In all likelihood the most cost effective way of doing this would be with a spacecraft carrying a comprehensive suite of instruments and performing multiple flybys of Europa. A number of notional trajectory designs have been investigated, utilizing gravity assists from other Galilean moons to decrease the period of the orbit and shape it in order to provide a globally distributed coverage of different regions of Europa. Navigation analyses are being performed on these candidate trajectories to assess the total Delta V that would be needed to complete the mission, to study how accurately the flybys could be executed, and to determine which assumptions most significantly affect the performance of the navigation system.

tour↗

Horizon Based Orientation Estimation for Planetary Surface Navigation

Planetary rovers navigate in extreme environments for which a Global Positioning System (GPS) is unavailable, maps are restricted to relatively low resolution provided by orbital imagery, and compass information is often lacking due to weak or not existent magnetic fields. However, an accurate rover localization is particularly important to achieve the mission success by reaching the science targets, avoiding negative obstacles visible only in orbital maps, and maintaining good communication connections with ground. This paper describes a horizon solution for precise rover orientation estimation. The detected horizon in imagery provided by the on board navigation cameras is matched with the horizon rendered over the existing terrain model. The set of rotation parameters (roll, pitch yaw) that minimize the cost function between the two horizon curves corresponds to the rover estimated pose.

localization↗

Lucy: Navigating a Jupiter Trojan Tour

In January 2017, NASA selected the Lucy mission to explore six Jupiter Trojan asteroids. These six bodies, remnants of the primordial material that formed the outer planets, were captured in the Sun-Jupiter L4 and L5 Lagrangian regions early in the solar system formation. These particular bodies were chosen because of their diverse spectral properties and the chance to observe up close for the first time two orbiting approximately equal mass binaries, Patroclus and Menoetius. KinetX, Inc. is the primary navigation supplier for the Lucy mission. This paper describes preliminary navigation analyses of the approach phase for each Trojan encounter.

trajectory design↗

Testing of the Orion Optical Navigation Image Processing Algorithms

The Optical Navigation System for Orion has been developed to ensure that the crew can return safely to Earth in case of a loss of communications. This presentation contains an overview of the image processing aspect of the Orion optical navigation system. The top level architecture is presented along with results of the testing of these image processing system.

Optical Navigation↗

An Implementation Analysis of Communications, Navigation, and Surveillance (CNS) Technologies for Unmanned Air Systems (UAS)

The aviation industry and government agencies face a rapidly-emerging need for integrating large-scale populations of Unmanned Air Systems (UAS) into the worldwide controlled and uncontrolled airspace. Critical components for integration include the Communications, Navigation, and Surveillance (CNS) technologies necessary for ensuring safe UAS operations. Under NASA program NNA16BD84C, our work on CNS architectural concepts for the safe operation of UAS in controlled and uncontrolled airspace has introduced CNS architectures which must be analyzed in terms of implementation readiness.Controlled airspace operations for UAS are consistent with the needs for manned aviation in the worldwide Air Traffic Management (ATM) service. Uncontrolled airspace operations are consistent with the NASA Unmanned (air) Traffic Management (UTM) concept of operations. Implementation readiness is based on the NASA concept of Technology Readiness Levels (TRLs) ranging from TRL1 (basic principles observed and reported) to TRL9 (actual system flight proven through successful mission operations). In the architecture concepts, we have introduced a number of new CNS architectural elements which need to be correlated with TRL levels. In this paper, we present our implementation analysis for communications networks, communications data links, navigation, and surveillance. Each area has been under active research and development during the course of the current NASA program which has produced studies on UAS CNS Requirements, UAS CNS Architecture for Controlled Airspace and UAS CNS Architecture for Uncontrolled Airspace. We have published our architecture concepts in major UAS-related conferences (including iCNS2017, IEEE Aerospace 2018, and iCNS2018) and will continue to seek additional publication opportunities. We look forward to continuing our work to realize a full integration testing scenario for both controlled and uncontrolled airspace operation.

Unmanned (Air) Traffic Management (UTM) service↗

GOES-16 ABI Navigation Assessment

The US Geostationary Operational Environmental Satellite – R Series (GOES-R) was launched on November 19, 2016and was designated GOES-16 upon reaching geostationary orbit ten days later. After checkout and calibration, GOES-16 was relocated to its operational location of 75.2 degrees west and officially became GOES East on December 18, 2017. The Advanced Baseline Imager (ABI) is the primary instrument on the GOES-R series for imaging Earth's surface and atmosphere to significantly improve the detection and observation of severe environmental phenomena. A team supporting the GOES-R Flight Project at NASA's Goddard Space Flight Center developed algorithms and software for independent verification of ABI Image Navigation and Registration (INR), which became known as the INR Performance Assessment Tool Set (IPATS). In this paper, we will briefly describe IPATS on top concept level, and then introduce the Landsat chips, chip registration algorithms, and how IPATS measurements are filtered. We present GOES-16 navigation (NAV) errors from flight data from January 2017 to May 2018. The results show a) IPATS characterized INR variations throughout the post-launch test phase; and b) ABI INR has improved over time as post-launch tests were performed and corrections applied. Finally, we will describe how estimated NAV errors have been used to assess and understand satellite attitude anomalies and scale errors etc. This paper shows that IPATS is an effective tool for assessing and improving GOES-16 ABI INR and is also useful for INR long-term monitoring.

GOES-R↗

Nanoradian Ground-Based Astrometry, Optical Navigation, and Artificial Reference Stars

Spacecraft carrying optical communication lasers can be treated as artificial stars, whose relative astrometry to Gaia reference stars provides spacecraft positions in the plane-of-sky for optical navigation. To be comparable to current Deep Space Network delta-Differential One-way Ranging measurements, thus sufficient for navigation, nanoradian optical astrometry is required. Here we describe our error budget, techniques for achieving nanoradian level ground-base astrometry, and preliminary results from a 1 m telescope. We discuss also how these spacecraft may serve as artificial reference stars for adaptive optics, high precision astrometry to detect exoplanets, and tying reference frames defined by radio and optical measurements.

optical navigation↗

Automated Management of Small Unmanned Aircraft System Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation System (UAS) Traffic Management↗