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Control in Unmanned NASA Missions

This viewgraph presentation reviews several general aspects of control for NASA space missions. Included in the review are the Entry, Descent and Landing (EDL) for both Mars Exploration Rover (MER), and Mars Science Laboratory (MSL); and the control of the MER Rover. Also included is discussion about control issues in relation to formation flying, adaptive optics and precision wavefront control, sensors for environmental control- ENose. Essential developments in the areas of control are important for increase in Autonomy/Automation is essential for deep space manned missions. Other areas of concern are robustness and the need to address life support system control issues.

wavefront control↗

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level precision at a range of two meters with a 1U target.

Carter, C.↗

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However, it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level accuracy at a range of two meters with a 1U target.

Carter, Christopher↗

Anti-Collision Function Design and Performances of the CNES Formation Flying Experiment on the PRISMA Mission

Within the framework of a partnership agreement, EADS ASTRIUM has worked since June 2006 for the CNES formation flying experiment on the PRISMA mission. EADS ASTRIUM is responsible for the anti-collision function. This responsibility covers the design and the development of the function as a Matlab/Simulink library, as well as its functional validation and performance assessment. PRISMA is a technology in-orbit testbed mission from the Swedish National Space Board, mainly devoted to formation flying demonstration. PRISMA is made of two micro-satellites that will be launched in 2009 on a quasi-circular SSO at about 700 km of altitude. The CNES FFIORD experiment embedded on PRISMA aims at flight validating an FFRF sensor designed for formation control, and assessing its performances, in preparation to future formation flying missions such as Simbol X; FFIORD aims as well at validating various typical autonomous rendezvous and formation guidance and control algorithms. This paper presents the principles of the collision avoidance function developed by EADS ASTRIUM for FFIORD; three kinds of maneuvers were implemented and are presented in this paper with their performances.

Cayeux, P.↗

Sensors for Pointing Moving Instruments Toward Each Other

Optoelectronic sensor systems are being developed for use in maintaining fixed relative orientations of two scientific-instrument platforms that are in relative motion. In the original intended application, the platforms would be two spacecraft flying in formation and separated by a long baseline. In principle, sensor systems of this type could also be used in terrestrial applications for maintaining alignments between moving instrument platforms. The sensor system would utilize beacon laser beams that would be transmitted by the platforms in the normal course of scientific measurements. The frequency of the returned laser beam would differ by about 5 MHz. On each platform, the transmitted laser beam and the laser beam bounced off the other platform would be focused onto a quadrant photodetector, where the interference between the laser beams would give rise to sinusoidal (beat-frequency) signals on all four quadrants. The differences among the phases of the beat-frequency signals in the quadrants would depend on, and would be used to determine the angle between, the wave fronts of the outgoing and incoming laser beams.

Liebe, Carl↗

Relative Navigation for Formation Flying of Spacecraft

This paper presents a robust and efficient approach for relative navigation and attitude estimation of spacecraft flying in formation. This approach uses measurements from a new optical sensor that provides a line of sight vector from the master spacecraft to the secondary satellite. The overall system provides a novel, reliable, and autonomous relative navigation and attitude determination system, employing relatively simple electronic circuits with modest digital signal processing requirements and is fully independent of any external systems. Experimental calibration results are presented, which are used to achieve accurate line of sight measurements. State estimation for formation flying is achieved through an optimal observer design. Also, because the rotational and translational motions are coupled through the observation vectors, three approaches are suggested to separate both signals just for stability analysis. Simulation and experimental results indicate that the combined sensor/estimator approach provides accurate relative position and attitude estimates.

Alonso, Roberto↗

Enabling Spacecraft Formation Flying through Position Determination, Control and Enhanced Automation Technologies

Formation Flying is revolutionizing the way the space community conducts science missions around the Earth and in deep space. This technological revolution will provide new, innovative ways for the community to gather scientific information, share that information between space vehicles and the ground, and expedite the human exploration of space. Once fully matured, formation flying will result in numerous sciencecraft acting as virtual platforms and sensor webs, gathering significantly more and better science data than call be collected today. To achieve this goal, key technologies must be developed including those that address the following basic questions posed by the spacecraft: Where am I? Where is the rest of the fleet? Where do I need to be? What do I have to do (and what am I able to do) to get there? The answers to these questions and the means to implement those answers will depend oil the specific mission needs and formation configuration. However, certain critical technologies are common to most formations. These technologies include high-precision position and relative-position knowledge including Global Positioning System (GPS) mid celestial navigation; high degrees of spacecraft autonomy inter-spacecraft communication capabilities; targeting and control including distributed control algorithms, and high precision control thrusters and actuators. This paper provides an overview of a selection of the current activities NASA/DoD/Industry/Academia are working to develop Formation Flying technologies as quickly as possible, the hurdles that need to be overcome to achieve our formation flying vision, and the team's approach to transfer this technology to space. It will also describe several of the formation flying testbeds, such as Orion and University Nanosatellites, that are being developed to demonstrate and validate many of these innovative sensing and formation control technologies.

Bristow, John↗

An Environment for Hardware-in-the-Loop Formation Navigation and Control Simulation

Recent interest in formation flying satellite systems has spurred a considerable amount of research in the relative navigation and control of satellites. Development in this area has included new estimation and control algorithms as well as sensor and actuator development specifically geared toward the relative control problem. This paper describes a simulation facility, the Formation Flying Testbed (FFTB) at NASA's Goddard Space Flight Center, which allows engineers to test new algorithms for the formation flying problem with relevant GN&C hardware in a closed loop simulation. The FFTB currently supports the injection of GPS receiver hardware into the simulation loop, and support for satellite crosslink ranging technology is at a prototype stage. This closed-loop, hardware inclusive simulation capability permits testing of navigation and control software in the presence of the actual hardware with which the algorithms must interact. This capability provides the navigation or control developer with a perspective on how the algorithms perform as part of the closed-loop system. In this paper, the overall design and evolution of the FFTB are presented. Each component of the FFTB is then described in detail. Interfaces between the components of the FFTB are shown and the interfaces to and between navigation and control software are described in detail. Finally, an example of closed-loop formation control with GPS receivers in the loop is presented and results are analyzed.

Burns, Rich↗

An Environmental for Hardware-in-the-Loop Formation Navigation and Control

Recent interest in formation flying satellite systems has spurred a considerable amount of research in the relative navigation and control of satellites. Development in this area has included new estimation and control algorithms as well as sensor and actuator development specifically geared toward the relative control problem. This paper describes a simulation facility, the Formation Flying Test Bed (FFTB) at NASA Goddard Space Flight Center, which allows engineers to test new algorithms for the formation flying problem with relevant GN&C hardware in a closed loop simulation. The FFTB currently supports the inclusion of GPS receiver hardware in the simulation loop. Support for satellite crosslink ranging technology is at a prototype stage. This closed-loop, hardware inclusive simulation capability permits testing of navigation and control software in the presence of the actual hardware with which the algorithms must interact. This capability provides the navigation or control developer with a perspective on how the algorithms perform as part of the closed-loop system. In this paper, the overall design and evolution of the FFTB are presented. Each component of the FFTB is then described. Interfaces between the components of the FFTB are shown and the interfaces to and between navigation and control software are described. Finally, an example of closed-loop formation control with GPS receivers in the loop is presented.

Burns, Rich↗

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

Several multisensor simulator packages are being developed by different research groups across the world. Such simulator packages [e.g., COSP , CRTM, ECSIM, RTTO, ISSARS (under development), and SDSU (this article), among others] share overall aims, although some are targeted more on particular satellite programs or specific applications (for research purposes or for operational use) than others. The SDSU or Satellite Data Simulator Unit is a general-purpose simulator composed of Fortran 90 codes and applicable to spaceborne microwave radiometer, radar, and visible/infrared imagers including, but not limited to, the sensors listed in a table. That shows satellite programs particularly suitable for multisensor data analysis: some are single satellite missions carrying two or more instruments, while others are constellations of satellites flying in formation. The TRMM and A-Train are ongoing satellite missions carrying diverse sensors that observe clouds and precipitation, and will be continued or augmented within the decade to come by future multisensor missions such as the GPM and Earth-CARE. The ultimate goals of these present and proposed satellite programs are not restricted to clouds and precipitation but are to better understand their interactions with atmospheric dynamics/chemistry and feedback to climate. The SDSU's applicability is not technically limited to hydrometeor measurements either, but may be extended to air temperature and humidity observations by tuning the SDSU to sounding channels. As such, the SDSU and other multisensor simulators would potentially contribute to a broad area of climate and atmospheric sciences. The SDSU is not optimized to any particular orbital geometry of satellites. The SDSU is applicable not only to low-Earth orbiting platforms as listed in Table 1, but also to geostationary meteorological satellites. Although no geosynchronous satellite carries microwave instruments at present or in the near future, the SDSU would be useful for future geostationary satellites with a microwave radiometer and/or a radar aboard, which could become more feasible as engineering challenges are met. In this short article, the SDSU algorithm architecture and potential applications are reviewed in brief.

Masunaga, Hirohiko↗

Formation Flying for Satellites and Unmanned Aerial Vehicles

The shrinking size of satellites and unmanned aerial vehicles (UAVs) is enabling lower cost missions. As sensors and electronics continue to downsize, the next step is multiple vehicles providing different perspectives or variations for more precise measurements. While flying a single satellite or UAV autonomously is a challenge, flying multiple vehicles in a precise formation is even more challenging. The goal of this project is to develop a scalable mesh network between vehicles (satellites or UAVs) to share real-time position data and maintain formations autonomously. Newly available low-cost, commercial off-the-shelf credit card size computers will be used as the basis for this network. Mesh networking techniques will be used to provide redundant links and a flexible network. The Small Projects Rapid Integration and Test Environment Lab will be used to simulate formation flying of satellites. UAVs built by the Aero-M team will be used to demonstrate the formation flying in the West Test Area. The ability to test in flight on NASA-owned UAVs allows this technology to achieve a high Technology Readiness Level (TRL) (TRL-4 for satellites and TRL-7 for UAVs). The low cost of small UAVs and the availability of a large test range (West Test Area) dramatically reduces the expense of testing. The end goal is for this technology to be ready to use on any multiple satellite or UAV mission.

Merrill, Garrick↗

NASA'S Earth Science Enterprise Embraces Active Laser Remote Sensing from Space

Several objectives of NASA's Earth Science Enterprise are accomplished, and in some cases, uniquely enabled by the advantages of earth-orbiting active lidar (laser radar) sensors. With lidar, the photons that provide the excitation illumination for the desired measurement are both controlled and well known. The controlled characteristics include when and where the illumination occurs, the wavelength, bandwidth, pulse length, and polarization. These advantages translate into high signal levels, excellent spatial resolution, and independence from time of day and the sun's position. As the lidar technology has rapidly matured, ESE scientific endeavors have begun to use lidar sensors over the last 10 years. Several more lidar sensors are approved for future flight. The applications include both altimetry (rangefinding) and profiling. Hybrid missions, such as the approved Geoscience Laser Altimeter System (GLAS) sensor to fly on the ICESat mission, will do both at the same time. Profiling applications encompass aerosol, cloud, wind, and molecular concentration measurements. Recent selection of the PICASSO Earth System Science Pathfinder mission and the complementary CLOUDSAT radar-based mission, both flying in formation with the EOS PM mission, will fully exploit the capabilities of multiple sensor systems to accomplish critical science needs requiring such profiling. To round out the briefing a review of past and planned ESE missions will be presented.

Luther, Michael R.↗

SIMBOL-X: A Formation Flying Mission on HEO for Exploring the Universe

SIMBOL-X is a high energy new generation telescope covering by a single instrument a continuous energy range starting at classical X-rays and extending to hard X-rays, i.e. from 0.5 to 80 keV. It is using in this field a focalizing payload which until now was used for energy below 10 keV only, via the construction of a telescope distributed on two satellites flying in formation. SIMBOL-X permits a gain of two orders of magnitude in sensibility and spatial resolution in comparison to state of the art hard X-rays instruments. The mirror satellite will be in free flight on a high elliptical orbit and will target the object to observe very precisely, thus focusing the hard X-ray emission thanks to this mirror module. At the focal point area which is situated 20 meters behind the mirror satellite, the detector satellite maintains its position on a forced orbit thanks to a radio link with the mirror satellite and a lateral displacement sensor using a beam emitted onboard the mirror satellite. This configuration is said "formation flying". The location of the detector satellite shall be very finely tuned as it carries the focal plane of this distributed telescope. To provide science measurements, the Simbol-X orbit has been chosen High elliptic (HEO), which means elliptical orbit with a high perigee altitude. Preliminary studies where made with an orbit with an altitude of the perigee of 44000km and altitude of the apogee of 253000km. The orbit was seven days ground track repeated in order to maintain a perigee pass over the Malindi ground station to download scientific telemetry. But as studies went on, difficulties in mass budget, link budget, perigee maintenance and formation flying maintenance were raised. This was mainly due to the vicinity of the Moon and its disturbing effect on the satellites orbits. Alternative orbits have been proposed in order to demonstrate the feasibility of the mission. The problematic of bringing the two satellites from their injection orbit to their operational orbit 20 m apart from each other and then maintain this configuration is very challenging. It requires theoretical development of the relative motion between two satellites in high eccentric orbit with large differential disturbance on the two bodies. This paper will present the mission analysis for the Simbol-X satellites with the complex problematic of doing formation flying in high elliptic orbit.

Gamet, Philippe↗

The StarLight mission: a formation-flying stellar interferometer

The StarLight mission is designed to validate the technologies of formation flying and stellar interferometry in space. The mission consists of two spacecraft in an earth-trailing orbit that formation fly over relative ranges of 40 to 600 m to an accuracy of 10 cm.

formation-flying↗

Terrestrial Planet Finder Interferometer 2005

Activities Affected by Budget Adjustment: Formation Acquisition Sensor, Cryo Structures, Cryo Delay Line, Cryocooler, Design Team, System Modeling. Other Activities include: Formation Flying, Cryogenic Operations, Starlight suppression, and System Design and Modeling.

interferometry↗

SPHERES Facility

Synchronized Position Hold, Engage, Reorient, Experimental Satellites (SPHERES) are bowling-ball sized satellites that provide a test bed for development and research into multi-body formation flying, multi-spacecraft control algorithms, and free-flying physical and material science investigations. Up to three self-contained free-flying satellites can fly within the cabin of the International Space Station (ISS), performing flight formations, testing of control algorithms or as a platform for investigations requiring this unique free-flying test environment. Each satellite is a self-contained unit with power, propulsion, computers, navigation equipment, and provides physical and electrical connections (via standardized expansion ports) for Principal Investigator (PI) provided hardware and sensors.

Material science investigations↗

2001 Flight Mechanics Symposium

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium held on June 19-21, 2001. Sponsored by the Guidance, Navigation and Control Center of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to attitude/orbit determination, prediction and control; attitude simulation; attitude sensor calibration; theoretical foundation of attitude computation; dynamics model improvements; autonomous navigation; constellation design and formation flying; estimation theory and computational techniques; Earth environment mission analysis and design; and, spacecraft re-entry mission design and operations. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight mechanics↗

NASA Tech Briefs, August 2009

Topics covered include: Aligning a Receiving Antenna Array to Reduce Interference; Collecting Ground Samples for Balloon-Borne Instruments; Tethered Pyrotechnic Apparatus for Acquiring a Ground Sample; Enhanced Video-Oculography System; Joint Carrier-Phase Synchronization and LDPC Decoding; Dual-Polarization, Sideband-Separating, Balanced Receiver for 1.5 THz Modular Battery Charge Controller; Efficient Multiplexer FPGA Block Structures Based on G4FETs; VLSI Microsystem for Rapid Bioinformatic Pattern Recognition; Low-Noise Amplifier for 100 to 180 GHz; Improved Fabrication of Ceramic Matrix Composite/Foam Core Integrated Structures; Inert Welding/Brazing Gas Filters and Dryers; Fabricating Copper Nanotubes by Electrodeposition; Reducing Aerodynamic Drag on Empty Open Cargo Vehicles; Rotary Percussive Auto-Gopher for Deep Drilling and Sampling; More About Reconfigurable Exploratory Robotic Vehicles; Thermostatic Valves Containing Silicone-Oil Actuators; Improving Heat Flux Performance of Flat Surface in Spray-Cooling Systems; Treating Fibrous Insulation to Reduce Thermal Conductivity; Silica-Aerogel Composites Opacified with La(sub0.7)Sr(sub0.3)MnO3; Cyclic Oxidation Behavior of CuCrAl Cold-Sprayed Coatings for Reusable Launch Vehicles; Ceramic Fiber Structures for Cryogenic Load-Bearing Applications; Elastomer Reinforced with Carbon Nanotubes; Biologically Inspired Purification and Dispersion of SWCNTs; A Technique for Adjusting Eigenfrequencies of WGM Resonators; Low-Pressure, Field-Ionizing Mass Spectrometer; Modifying Operating Cycles to Increase Stability in a LITS; Chamber for Simulating Martian and Terrestrial Environments; Algorithm for Detecting a Bright Spot in an Image; Extreme Programming: Maestro Style; Adaptive Behavior for Mobile Robots; Protocol for Communication Networking for Formation Flying; Planning Complex Sequences Using Compressed Representations; and Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors.

Source record↗