Unmanned spacecraft guidance and control
Unmanned spacecraft guidance and control technology for lunar and planetary exploration
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Unmanned spacecraft guidance and control technology for lunar and planetary exploration
Computations and equations for accelerated flight and coasting flight navigation, and powered flight and midcourse guidance for manned spacecraft
Unified lunar spacecraft guidance of major and minor maneuvers during accelerated and coasting flight
Required weight of spacecraft minimized. Report describes conceptual algorithm for guidance of spacecraft launched from surface of Mars. Spacecraft to carry canister of specimens from surface to another spacecraft in orbit about Mars; second spacecraft then to carry canister back to Earth. Algorithm sufficiently general to be adaptable to prediction/correction algorithms for other spacecraft configurations.
Lunar Orbiter Spacecraft Guidance and Control, discussing design and flight results
Visual sensing and spacecraft guidance for earth orbit rendezvous maneuvers
Spacecraft trajectory initial conditions expressions as parameters dependent functions, applying results to Mars lander mission
This work develops a method for Robust Controller for Vision-based Spacecraft (RCVS) guidance and control, integral to the robust autonomy framework for multi-spacecraft for- mation control and reconfiguration applications. The method is built around the use of a photo-realistic simulator, where a camera is deployed on a tracking spacecraft (ego) in order to observe an uncontrolled spacecraft (target) in a Low Earth Orbit (LEO). In this direction, the proposed approach performs the relative state (attitude and position) estimation of the target spacecraft using Convolutional Neural Network (CNN). The state estimation error is then modeled and the corresponding error-bounds are obtained around a nominal trajectory of the ego and target spacecraft. Next, this work proposes a linear matrix inequalities (LMIs) based approach to controller synthesis, guaranteed to be robust against both model uncertainties and measurement errors, resulting from vision-based estimation. This controller is comprised of two distinct components, one synthesized based on the nominal trajectory, while the “robust” component corrects for deviations from the nominal trajectory. Finally, a tracking scenario that directly utilize the image data for spacecraft guidance and control, is presented to showcase the performance of the proposed robust autonomy framework.
G-View is a 3D visualization tool for supporting spacecraft guidance, navigation, and control (GN&C) simulations relevant to small-body exploration and sampling (see figure). The tool is developed in MATLAB using Virtual Reality Toolbox and provides users with the ability to visualize the behavior of their simulations, regardless of which programming language (or machine) is used to generate simulation results. The only requirement is that multi-body simulation data is generated and placed in the proper format before applying G-View.
By the next decade, spacecraft will be highly miniaturized and automated to realize much lower life-cycle costs in comparison to todays counterparts. These small spacecraft will have highly autonomous control systems for spacecraft attitude, maneuver, and orbit control.
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Successful planetary exploration missions have been completed by unmanned Mariner spacecraft, which were designed at the Jet Propulsion Laboratory. Mariner II completed a 109-day flyby mission to Venus on December 14, 1962. This mission was followed by the flyby of Mars and return of 21 historic photographs of its surface by Mariner IV in July 1965. Further successful missions followed: Mariner V to Venus in 1967, Mariners VI and VII to Mars in 1969. In all of these missions, a Central Computer and Sequencer onboard the spacecraft was used to provide on-board control functions, although complete ground backup was also available.
The combination of a strap-down analog sun acquisition sensor (AS) and an on-board digital programmable signal processor results in a versatile guidance and control system. The combination can orient the rotation axis of a spin-stabilized spacecraft to the sun no matter what the initial attitude of the spacecraft. During the sun orientation process, spacecraft spin rate can be sensed and supplied as an input to the control algorithm. If needed, the AS-signal processor combination can be used to perform a rhumb-line turn maneuver. In case of unexpected spacecraft operating conditions, or unplanned pointing directions, the signal processor program can be updated via earth-based transmission of another program to cover the new situation. Using only three radiation-hard cadmium-sulfide detectors, containing no moving parts, needing only a few microwatts of power, included in a volume of 550 cubic cm (a redundant pair), and weighing only 540 grams, the AS is a small, simple, sturdy sensing device.
In this paper, we present an end-to-end simulation framework for tracking an uncooperative Target spacecraft in Low Earth Orbit using a CubeSat-class Ego spacecraft outfitted with a camera. Currently, capturing high-fidelity realistic images in space for this scenario is difficult and exorbitantly expensive. Therefore, we developed a framework to simulate the spacecraft orbits in Basilisk software and generate high-fidelity realistic images of spacecraft in Unreal Engine, including the effects from Sun, Earth, Moon and stars. The Ego spacecraft uses cameras to capture images of the uncooperative Target and estimates its position and attitude using a CNN based 6DOF pose estimation pipeline, eliminating need for large SWAP-C(Size, Weight, Power and Cost) sensors like LIDAR or reliance on inter-spacecraft communication, This CNN, which is motivated by ESA’s Pose Estimation challenge of 2019, is trained using simulated data from our end-to-end simulation framework. We compare the performance of two distinct CNNbased algorithms for pose estimation along a nominal trajectory. In presence of non-Gaussian modeling uncertainties, the statedependent estimation error is characterized with a quadratic upper-bound. The quadratically-bounded error can be used by a robust controller to maneuver
The Cassini-Huygens mission ended on September 15, 2017, after nearly two decades in ight. The well-designed Cassini spacecraft had robust hardware that permitted two extended missions, lasting nine years longer than the expected prime mission. At the end of the mission, the Attitude and Articulation Control Subsystem (AACS) was using two pieces of redundant back-up of hardware, one reaction wheel and the hydrazine thruster branch, due to hardware anomalies earlier in the mission. The back-up hardware performed nominally through the rest of mission. The prime reaction wheels at the end of the mission had reached more than 130% of the consumable limit for number of revolutions. No thruster on either thruster branch accumulated more than 45% of the consumable limits. The inertial reference unit slightly exceeded the pre-launch requirements on bias error, but as the software continuously estimated this value in ight, the attitude estimation was not adversely a ected. The star trackers performed nominally, and though there was a spacecraft anomaly in 1998 related to the star trackers, the origin was not in hardware itself. The Sun sensors and accelerometer both performed as expected and met all requirements throughout the mission. Ultimately, the lifetime of the Cassini spacecraft was not limited by hardware performance. Planetary protection requirements necessitated the end of the mission as the spacecraft's propellant reserves depleted, and Cassini plunged into Saturn's atmosphere with a healthy attitude control system.
The objective of this research is to design an intelligent plug-n-play avionics system that provides a reconfigurable platform for supporting the guidance, navigation and control (GN&C) requirements for different elements of the space exploration mission. The focus of this study is to look at the specific requirements for a spacecraft that needs to go from earth to moon and back. In this regard we will identify the different GN&C problems in various phases of flight that need to be addressed for designing such a plug-n-play avionics system. The Apollo and the Space Shuttle programs provide rich literature in terms of understanding some of the general GN&C requirements for a space vehicle. The relevant literature is reviewed which helps in narrowing down the different GN&C algorithms that need to be supported along with their individual requirements.
A star scanner for the Galileo Project is described. Because it must function in the intense Jupiter radiation field, which consists primarily of high-energy electrons and protons, this star scanner is designed with radiation-hardness as a prime objective. The optics and the multiplier phototube are specially designed to minimize fluorescence and Cerenkov effects, and the electronic components to minimize ionization and displacement damage. The star-scanner layout provides maximum shielding for the optics and phototube. Test results predict successful operation in the expected Jovian radiation environment.
(Previously cited in issue 21, p. 3643, Accession no. A81-44138)