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NASA NTRS2004

Miniature Robotic Spacecraft for Inspecting Other Spacecraft

A report discusses the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam)-- a compact robotic spacecraft intended to be released from a larger spacecraft for exterior visual inspection of the larger spacecraft. The Mini AERCam is a successor to the AERCam Sprint -- a prior miniature robotic inspection spacecraft that was demonstrated in a space-shuttle flight experiment in 1997. The prototype of the Mini AERCam is a demonstration unit having approximately the form and function of a flight system. The Mini AERCam is approximately spherical with a diameter of about 7.5 in. (.19 cm) and a weight of about 10 lb (.4.5 kg), yet it has significant additional capabilities, relative to the 14-in. (36-cm), 35-lb (16-kg) AERCam Sprint. The Mini AERCam includes miniaturized avionics, instrumentation, communications, navigation, imaging, power, and propulsion subsystems, including two digital video cameras and a high-resolution still camera. The Mini AERCam is designed for either remote piloting or supervised autonomous operations, including station keeping and point-to-point maneuvering. The prototype has been tested on an air-bearing table and in a hardware-in-the-loop orbital simulation of the dynamics of maneuvering in proximity to the International Space Station.

Fredrickson, Steven↗

NASA NTRS2022

Trajectory Specification Applied to Terminal Airspace

Despite major efforts to automate air traffic control (ATC), it is still performed by humans today. The complexity and safety-criticality of ATC makes it very difficult to safely automate, but it must be automated to increase airspace capacity (the density of traffic that can be safely managed) and airport throughput (the number of arrivals and departures that an airport can safely handle in a given period of time) beyond what is possible with human controllers. This paper presents the Trajectory Specification (TS) concept, which can help to safely automate ATC. TS is a method of specifying aircraft trajectories such that the position at any given time in flight is restricted to a precisely defined bounding space, removing all ambiguity as to where the flight is allowed to be. The bounding space or volume is determined by tolerances relative to a reference trajectory (position as a function of time). The tolerances are dynamic and are based on the aircraft navigation capabilities and the traffic situation. The tolerances can be a piecewise linear function of time or distance along the route, allowing the tolerances to vary as needed, typically increasing with time for departures and decreasing for arrivals. A Trajectory Specification Language (TSL) is proposed for communicating trajectories from aircraft to ATC as requests and from ATC to aircraft as assignments. The TS concept requires a new generation of airborne Flight Management Systems (FMS) that understand the TSL and can fly the assigned trajectories, but this paper focuses on the ATC functions and the prototype ATC algorithms and software that were developed to test the TS concept. Assuming conformance, TS can guarantee safe separation for an arbitrary length of time even in the event of an ATC system or communication outage. It can help to achieve the high level of safety and reliability needed for ATC automation, and it can also reduce the reliance on ATC backup systems for tactical conflict detection and resolution during normal operation. TS can be applied to any controlled airspace, including enroute, terminal, and urban airspace, but this paper presents algorithms and software for arrival spacing and conflict detection and resolution in the terminal airspace serving a major airport. In a fast-time simulation of a full day of traffic in a major terminal airspace, all conflicts were resolved in near real time, demonstrating the computational feasibility and the preliminary operational feasibility of the TS concept. This paper is a compilation of previous papers, and it adds significant information that was omitted from those papers due to length limitations. It also updates some of the results of those earlier papers due to algorithm refinements and corrections of minor software errors.

air traffic control, trajectory↗

NASA NTRS2008

A Self Contained Method for Safe and Precise Lunar Landing

The return of humans to the Moon will require increased capability beyond that of the previous Apollo missions. Longer stay times and a greater flexibility with regards to landing locations are among the many improvements planned. A descent and landing system that can land the vehicle more accurately than Apollo with a greater ability to detect and avoid hazards is essential to the development of a Lunar Outpost, and also for increasing the number of potentially reachable Lunar Sortie locations. This descent and landing system should allow landings in more challenging terrain and provide more flexibility with regards to mission timing and lighting considerations, while maintaining safety as the top priority. The lunar landing system under development by the ALHAT (Autonomous precision Landing and Hazard detection Avoidance Technology) project is addressing this by providing terrain-relative navigation measurements to enhance global-scale precision, an onboard hazard-detection system to select safe landing locations, and an Autonomous GNC (Guidance, Navigation, and Control) capability to process these measurements and safely direct the vehicle to this landing location. This ALHAT landing system will enable safe and precise lunar landings without requiring lunar infrastructure in the form of navigation aids or a priori identified hazard-free landing locations. The safe landing capability provided by ALHAT uses onboard active sensing to detect hazards that are large enough to be a danger to the vehicle but too small to be detected from orbit, given currently planned orbital terrain resolution limits. Algorithms to interpret raw active sensor terrain data and generate hazard maps as well as identify safe sites and recalculate new trajectories to those sites are included as part of the ALHAT System. These improvements to descent and landing will help contribute to repeated safe and precise landings for a wide variety of terrain on the Moon.

Paschall, Stephen C., II↗

NASA NTRS2016

Precision Landing and Hazard Avoidance Doman

The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking. Autonomous PL&HA builds upon the core GN&C capabilities developed to enable soft, controlled landings on the Moon, Mars, and other solar system bodies. Through the addition of a Terrain Relative Navigation (TRN) function, precision landing within tens of meters of a map-based target is possible. The addition of a 3-D terrain mapping lidar sensor improves the probability of a safe landing via autonomous, real-time Hazard Detection and Avoidance (HDA). PL&HA significantly improves the probability of mission success and enhances access to sites of scientific interest located in challenging terrain. PL&HA can also utilize external navigation aids, such as navigation satellites and surface beacons. Advanced Lidar Sensors High precision ranging, velocimetry, and 3-D terrain mapping Terrain Relative Navigation (TRN) TRN compares onboard reconnaissance data with real-time terrain imaging data to update the S/C position estimate Hazard Detection and Avoidance (HDA) Generates a high-resolution, 3-D terrain map in real-time during the approach trajectory to identify safe landing targets Inertial Navigation During Terminal Descent High precision surface relative sensors enable accurate inertial navigation during terminal descent and a tightly controlled touchdown within meters of the selected safe landing target.

Robertson, Edward A.↗

NASA NTRSDate not supplied

AmesDT: Digital Twin and Autonomy Validation Environment

A simulation of NASA Ames Research Center was developed to provide a common testbed for multiple areas of research within the Intelligent Systems Division, primarily related to verification and validation of autonomous technologies, machine learning, and digital twin systems. AmesSim corresponds a physical rover that is capable of navigation in the real-world environment; in this way, the same experiments can be run in both settings, with the same software and hardware stacks in the loop. The simulation is built in Unreal Engine 4 and uses the AirSim plugin for API convenience. Several custom modifications allow deterministic, faster-than-realtime execution, which enables consistent testing of on-line algorithms and large-scale data collection. This paper describes the architecture and capabilities of the simulation and discusses development challenge.

simulation↗

NASA NTRS2013

Cloud Absorption Radiometer Autonomous Navigation System - CANS

CAR (cloud absorption radiometer) acquires spatial reference data from host aircraft navigation systems. This poses various problems during CAR data reduction, including navigation data format, accuracy of position data, accuracy of airframe inertial data, and navigation data rate. Incorporating its own navigation system, which included GPS (Global Positioning System), roll axis inertia and rates, and three axis acceleration, CANS expedites data reduction and increases the accuracy of the CAR end data product. CANS provides a self-contained navigation system for the CAR, using inertial reference and GPS positional information. The intent of the software application was to correct the sensor with respect to aircraft roll in real time based upon inputs from a precision navigation sensor. In addition, the navigation information (including GPS position), attitude data, and sensor position details are all streamed to a remote system for recording and later analysis. CANS comprises a commercially available inertial navigation system with integral GPS capability (Attitude Heading Reference System AHRS) integrated into the CAR support structure and data system. The unit is attached to the bottom of the tripod support structure. The related GPS antenna is located on the P-3 radome immediately above the CAR. The AHRS unit provides a RS-232 data stream containing global position and inertial attitude and velocity data to the CAR, which is recorded concurrently with the CAR data. This independence from aircraft navigation input provides for position and inertial state data that accounts for very small changes in aircraft attitude and position, sensed at the CAR location as opposed to aircraft state sensors typically installed close to the aircraft center of gravity. More accurate positional data enables quicker CAR data reduction with better resolution. The CANS software operates in two modes: initialization/calibration and operational. In the initialization/calibration mode, the software aligns the precision navigation sensors and initializes the communications interfaces with the sensor and the remote computing system. It also monitors the navigation data state for quality and ensures that the system maintains the required fidelity for attitude and positional information. In the operational mode, the software runs at 12.5 Hz and gathers the required navigation/attitude data, computes the required sensor correction values, and then commands the sensor to the required roll correction. In this manner, the sensor will stay very near to vertical at all times, greatly improving the resulting collected data and imagery. CANS greatly improves quality of resulting imagery and data collected. In addition, the software component of the system outputs a concisely formatted, high-speed data stream that can be used for further science data processing. This precision, time-stamped data also can benefit other instruments on the same aircraft platform by providing extra information from the mission flight.

Kahle, Duncan↗

NASA NTRS2018

Trajectory Specification Language for Air Traffic Control

Trajectory Specification is a method of specifying aircraft trajectories with tolerances such that the position at any instant in time is constrained to a precisely defined bounding space. The bounding space at any instant in time is defined by tolerances relative to a reference trajectory that specifies position as a function of time. The tolerances are dynamic and are based on the aircraft navigation capabilities and the traffic situation. This paper proposes a standard Trajectory Specification Language (TSL) based on the Extensible Markup Language (XML) to represent these specifications and to communicate them by datalink. The language can be used to downlink trajectory requests from air to ground and to uplink trajectory assignments from ground to air. The XML format can be converted to binary for operational use, if necessary, using Efficient XML Interchange (EXI) or Abstract Syntax Notation (ASN.1).

XM↗

NASA NTRSDate not supplied

Autonomous Nanosatellite Swarming (ANS) Using Radio Frequency and Optical Navigation

The Autonomous Nanosatellite Swarming (ANS) subsystem is a dynamics, guidance, navigation, and control software unit based on commercial-off-the-shelf avionics, which is distributed and deployed on a cluster of cooperative nanosatellites to enable future exploration missions to near-Earth objects (NEOs). ANS allows multiple nanosatellites to act together as a single large spacecraft through radio-frequency (RF) cross-links, optical navigation, and low-thrust control. In particular, ANS-equipped nanosatellites can utilize images of a NEO taken from multiple viewpoints to achieve stereo-vision capabilities and characterize the target body’s shape, gravity field, and dynamical properties. All this is enabled by the fusion of major advances to the state of the art in the astrodynamics of relative motion, RF and vision-based navigation, as well as low-thrust control.

Simone D'Amico↗

NASA NTRS1981

Development and evaluation of a prototype in-flight instrument flight rules (IFR) procedures trainer

An in-flight instrument flight rules (IFR) procedures trainer capable of providing simulated indications of instrument flight in a typical general aviation aircraft independent of ground based navigation aids was developed. The IFR navaid related instruments and circuits from an ATC 610J table top simulator were installed in a Cessna 172 aircraft and connected to its electrical power and pitot static systems. The benefits expected from this hybridization concept include increased safety by reducing the number of general aviation aircraft conducting IFR training flights in congested terminal areas, and reduced fuel use and instruction costs by lessening the need to fly to and from navaid equipped airports and by increased efficiency of the required in-flight training. Technical feasibility was demonstrated and the operational feasibility of the concept was evaluated. Results indicated that the in-flight simulator is an effective training device for teaching IFR procedural skills.

Aaron, J. B., Jr.↗

NASA NTRS2017

Trajectory Specification for Terminal Air Traffic: Pairwise Conflict Detection and Resolution

Trajectory specification is the explicit bounding and control of aircraft trajectories 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 navigation 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) system 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 the terminal area and presents algorithms and software for spacing arrivals and deconflicting both arrivals and departures.

air traffic control↗

NASA NTRS2017

Trajectory Specification for Terminal Air Traffic: Pairwise Conflict Detection and Resolution

Trajectory Specification is the explicit bounding and control of aircraft trajectories such that the position at any 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 navigation capabilities and the current traffic situation. Assuming conformance, Trajectory Specification can guarantee safe separation for an arbitrary period of time even in the event of an air traffic control (ATC) system or datalink failure; hence it can help to achieve the high level of safety and reliability needed for ATC automation. It can also reduce the reliance on tactical backup systems during normal operation. This paper applies it to the terminal area around a major airport and presents algorithms and software for detecting and resolving conflicts. A representative set of pairwise conflicts was generated, and a fast-time simulation was run on them. All conflicts were successfully resolved in real time, demonstrating the computational feasibility of the concept.

terminal area↗

NASA NTRSDate not supplied

NASA Lunar Surface Innovation Initiative: Ensuring a Cohesive, Executable Strategy for Technology Development

Establishing a sustainable human presence on the Moon allows NASA to develop and test new approaches, technologies, and systems that will enable us to function in other, more challenging environments. The Lunar Surface Innovation Initiative (LSII) was established in 2019 and has evolved into a key agency asset to spur technology development and provide risk reduction for lunar surface system development and flight demonstrations. LSII coordinates activities implemented through a combination of in-house activities, competitive programs, and public-private partnerships to create transformative technologies needed for lunar surface exploration. This paper will outline the LSII model used to develop a technology pipeline that will retire the primary technology hurdles in six capability areas. In-situ resource utilization technologies for collecting, processing, storing, and using material found or manufactured on the Moon. Surface power technologies that provide the capability for sustainable, continuous power throughout the day and night for lunar missions. Dust mitigation strategies that diminish lunar dust hazards on lunar surface systems such as cameras, solar panels, space suits, habitats, and instrumentation. Extreme environments technologies that enable systems to operate throughout the full range of lunar surface conditions, including lunar noon (up to 150 at the equator), night (down to - 180 at the equator), multiple day/night cycles, and in permanently shadowed regions (down to -250). Extreme access technologies that enable humans or robotic systems to access, navigate, and explore previously inaccessible lunar surface or subsurface areas. Excavation and construction technologies that will allow affordable, autonomous manufacturing or construction. We outline key results, including milestones and achievements related to the capability areas and outcomes from partnerships with the commercial sector. A key tenet of the LSII is the Lunar Surface Innovation Consortium (LSIC), a collaboration across industry, academia, and government to successfully develop the transformative capabilities for lunar surface exploration. LSIC provides a forum for NASA to communicate technological requirements, needs, and opportunities and for the community to share existing capabilities and identify critical gaps with NASA. By working side by side with commercial enterprises and our international partners, NASA is able to combine the knowledge and expertise needed to explore the lunar surface and make technical advances that will feed technological and economic growth. Since its inception, LSII has engaged over 600 organizations across the United States and 46 countries to shape the technologies and systems needed to explore the lunar surface and stimulate a lunar surface economy.

lunar, lunar surface, technology development, ISRU↗

NASA NTRSDate not supplied

NASA Lunar Surface Innovation Initiative: Ensuring a Cohesive, Executable Strategy for Technology

Lunar↗

NASA NTRS2015

Lidar Sensor Performance in Closed-Loop Flight Testing of the Morpheus Rocket-Propelled Lander to a Lunar-Like Hazard Field

For the first time, a suite of three lidar sensors have been used in flight to scan a lunar-like hazard field, identify a safe landing site, and, in concert with an experimental Guidance, Navigation, and Control (GN&C) system, help to guide the Morpheus autonomous, rocket-propelled, free-flying lander to that safe site on the hazard field. The lidar sensors and GN&C system are part of the Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT) project which has been seeking to develop a system capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The 3-D imaging Flash Lidar is a second generation, compact, real-time, aircooled instrument developed from a number of components from industry and NASA and is used as part of the ALHAT Hazard Detection System (HDS) to scan the hazard field and build a 3-D Digital Elevation Map (DEM) in near-real time for identifying safe sites. The Flash Lidar is capable of identifying a 30 cm hazard from a slant range of 1 km with its 8 cm range precision (1-s). The Flash Lidar is also used in Hazard Relative Navigation (HRN) to provide position updates down to a 250m slant range to the ALHAT navigation filter as it guides Morpheus to the safe site. The Navigation Doppler Lidar (NDL) system has been developed within NASA to provide velocity measurements with an accuracy of 0.2 cm/sec and range measurements with an accuracy of 17 cm both from a maximum range of 2,200 m to a minimum range of several meters above the ground. The NDLâ€"TM"s measurements are fed into the ALHAT navigation filter to provide lander guidance to the safe site. The Laser Altimeter (LA), also developed within NASA, provides range measurements with an accuracy of 5 cm from a maximum operational range of 30 km down to 1 m and, being a separate sensor from the Flash Lidar, can provide range along a separate vector. The LA measurements are also fed into the ALHAT navigation filter to provide lander guidance to the safe site. The flight tests served as the culmination of the TRL 6 journey for the ALHAT system and included launch from a pad situated at the NASA-Kennedy Space Center Shuttle Landing Facility (SLF) runway, a lunar-like descent trajectory from an altitude of 250m, and landing on a lunar-like hazard field of rocks, craters, hazardous slopes, and safe sites 400m down-range just off the North end of the runway. The tests both confirmed the expected performance and also revealed several challenges present in the flight-like environment which will feed into future TRL advancement of the sensors. Guidance provided by the ALHAT system was impeded in portions of the trajectory and intermittent near the end of the trajectory due to optical effects arising from air heated by the rocket engine. The Flash Lidar identified hazards as small as 30 cm from the maximum slant range of 450 m which Morpheus could provide; however, it was occasionally susceptible to an increase in range noise due to scintillation arising from air heated by the Morpheus rocket engine which entered its Field-of-View (FOV). The Flash Lidar was also susceptible to pre-triggering, during the HRN phase, on a dust cloud created during launch and transported down-range by the wind. The NDL provided velocity and range measurements to the expected accuracy levels yet it was also susceptible to signal degradation due to air heated by the rocket engine. The LA, operating with a degraded transmitter laser, also showed signal attenuation over a few seconds at a specific phase of the flight due to the heat plume generated by the rocket engine.

Roback, V. Eric↗

NASA NTRS1974

Binary processing and display concepts for low-cost Omega receivers

A description is given of concepts related to plans for developing a low-cost, all-digital Omega receiver capable of offering to the small-aircraft pilot a reliable and accurate navigation aid. The receiver base considered includes a receiver front-end module, a receiver control module, a memory-aided phase-locked loop module, a housekeeping timer module, and a synthesizer module.

Lilley, R. W.↗

NASA NTRS2015

Lidar Sensor Performance in Closed-Loop Flight Testing of the Morpheus Rocket-Propelled Lander to a Lunar-Like Hazard Field

For the first time, a suite of three lidar sensors have been used in flight to scan a lunar-like hazard field, identify a safe landing site, and, in concert with an experimental Guidance, Navigation, and Control (GN&C) system, guide the Morpheus autonomous, rocket-propelled, free-flying test bed to a safe landing on the hazard field. The lidar sensors and GN&C system are part of the Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT) project which has been seeking to develop a system capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The 3-D imaging flash lidar is a second generation, compact, real-time, air-cooled instrument developed from a number of cutting-edge components from industry and NASA and is used as part of the ALHAT Hazard Detection System (HDS) to scan the hazard field and build a 3-D Digital Elevation Map (DEM) in near-real time for identifying safe sites. The flash lidar is capable of identifying a 30 cm hazard from a slant range of 1 km with its 8 cm range precision at 1 sigma. The flash lidar is also used in Hazard Relative Navigation (HRN) to provide position updates down to a 250m slant range to the ALHAT navigation filter as it guides Morpheus to the safe site. The Doppler Lidar system has been developed within NASA to provide velocity measurements with an accuracy of 0.2 cm/sec and range measurements with an accuracy of 17 cm both from a maximum range of 2,200 m to a minimum range of several meters above the ground. The Doppler Lidar's measurements are fed into the ALHAT navigation filter to provide lander guidance to the safe site. The Laser Altimeter, also developed within NASA, provides range measurements with an accuracy of 5 cm from a maximum operational range of 30 km down to 1 m and, being a separate sensor from the flash lidar, can provide range along a separate vector. The Laser Altimeter measurements are also fed into the ALHAT navigation filter to provide lander guidance to the safe site. The flight tests served as the culmination of the TRL 6 journey for the lidar suite and included launch from a pad situated at the NASA-Kennedy Space Center Shuttle Landing Facility (SLF) runway, a lunar-like descent trajectory from an altitude of 250m, and landing on a lunar-like hazard field of rocks, craters, hazardous slopes, and safe sites 400m down-range just off the North end of the runway. The tests both confirmed the expected performance and also revealed several challenges present in the flight-like environment which will feed into future TRL advancement of the sensors. The flash lidar identified hazards as small as 30 cm from the maximum slant range of 450 m which Morpheus could provide, however, it was occasionally susceptible to an increase in range noise due to heated air from the Morpheus rocket plume which entered its Field-of-View (FOV). The flash lidar was also susceptible to pre-triggering on dust during the HRN phase which was created during launch and transported by the wind. The Doppler Lidar provided velocity and range measurements to the expected accuracy levels yet it was also susceptible to signal degradation due to air heated by the rocket engine. The Laser Altimeter, operating with a degraded transmitter laser, also showed signal attenuation over a few seconds at a specific phase of the flight due to the heat plume generated by the rocket engine.

Roback, Vincent E.↗

NASA NTRS1994

Development of a Prototype Real-Time Automated Filter for Operational Deep Space Navigation

Operational deep space navigation has in the past, and is currently, performed using systems whose architecture was designed to accommodate tape data transfers and computing environments with a tiny fraction of the current capability. Additionally, this architecture requires constant human supervision and intervention. A prototype for a system which allows relatively automated processing of radio metric data received in near real-time from NASA's Deep Space Network (DSN) without any redesign of the existing operational flow has been developed. This system will allow for more rapid response as well as much reduced staffing to support mission navigation operations.

deep↗

NASA NTRS2004

Proceedings from the 2nd International Symposium on Formation Flying Missions and Technologies

Topics discussed include: The Stellar Imager (SI) "Vision Mission"; First Formation Flying Demonstration Mission Including on Flight Nulling; Formation Flying X-ray Telescope in L2 Orbit; SPECS: The Kilometer-baseline Far-IR Interferometer in NASA's Space Science Roadmap Presentation; A Tight Formation for Along-track SAR Interferometry; Realization of the Solar Power Satellite using the Formation Flying Solar Reflector; SIMBOL-X : Formation Flying for High-Energy Astrophysics; High Precision Optical Metrology for DARWIN; Close Formation Flight of Micro-Satellites for SAR Interferometry; Station-Keeping Requirements for Astronomical Imaging with Constellations of Free-Flying Collectors; Closed-Loop Control of Formation Flying Satellites; Formation Control for the MAXIM Mission; Precision Formation Keeping at L2 Using the Autonomous Formation Flying Sensor; Robust Control of Multiple Spacecraft Formation Flying; Virtual Rigid Body (VRB) Satellite Formation Control: Stable Mode-Switching and Cross-Coupling; Electromagnetic Formation Flight (EMFF) System Design, Mission Capabilities, and Testbed Development; Navigation Algorithms for Formation Flying Missions; Use of Formation Flying Small Satellites Incorporating OISL's in a Tandem Cluster Mission; Semimajor Axis Estimation Strategies; Relative Attitude Determination of Earth Orbiting Formations Using GPS Receivers; Analysis of Formation Flying in Eccentric Orbits Using Linearized Equations of Relative Motion; Conservative Analytical Collision Probabilities for Orbital Formation Flying; Equations of Motion and Stability of Two Spacecraft in Formation at the Earth/Moon Triangular Libration Points; Formations Near the Libration Points: Design Strategies Using Natural and Non-Natural Ares; An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer; GVE-Based Dynamics and Control for Formation Flying Spacecraft; GNC System Design for a New Concept of X-Ray Distributed Telescope; GNC System for the Deployment and Fine Control of the DARWIN Free-Flying Interferometer; Formation Algorithm and Simulation Testbed; and PLATFORM: A Formation Flying, RvD and Robotic Validation Test-bench.

Source record↗