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Algorithms were developed for magnetometer biases and spin axis attitude calculation. Numerical examples of the performance of the algorithm are given.
An algorithm is presented that incorporates real time data from two infrared cameras and computes the attitude parameters of the Spacecraft COntrol Lab Experiment (SCOLE), a lab apparatus representing an offset feed antenna attached to the Space Shuttle by a flexible mast. The algorithm uses camera position data of three miniature light emitting diodes (LEDs), mounted on the SCOLE platform, permitting arbitrary camera placement and an on-line attitude extraction. The continuous nature of the algorithm allows identification of the placement of the two cameras with respect to some initial position of the three reference LEDs, followed by on-line six degrees of freedom attitude tracking, regardless of the attitude time history. A description is provided of the algorithm in the camera identification mode as well as the mode of target tracking. Experimental data from a reduced size SCOLE-like lab model, reflecting the performance of the camera identification and the tracking processes, are presented. Computer code for camera placement identification and SCOLE attitude tracking is listed.
In this paper, a new algorithm for GPS (Global Positioning System) integer ambiguity resolution is shown. The algorithm first incorporates an instantaneous (static) integer search to significantly reduce the search space using a geometric inequality. Then a batch-type loss function is used to check the remaining integers in order to determine the optimal integer. This batch function represents the GPS sightline vectors in the body frame as the sum of two vectors, one depending on the phase measurements and the other on the unknown integers. The new algorithm has several advantages: it does not require an a-priori estimate of the vehicle's attitude; it provides an inherent integrity check using a covariance-type expression; and it can resolve the integers even when coplanar baselines exist. The performance of the new algorithm is tested on a dynamic hardware simulator.
A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.
A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.
The Far Ultraviolet Spectroscopic Explorer (FUSE) is equipped with two ring laser gyros on each of the spacecraft body axes. In May 2001 one gyro failed. It is anticipated that all of the remaining gyros will also fail, based on intensity warnings. In addition to the gyro failure, two of four reaction wheels failed in late 2001. The spacecraft control, now relies heavily on magnetic torque to perform the necessary science maneuvers. The only sensor available during slews is a magnetometer. This paper documents the testing and development of gyroless attitude and rate estimation algorithms for FUSE. The results of two approaches are presented, one relies on a kinematics model for propagation, a method used in aircraft tracking, and the other is a traditional Extended Kalman filter that utilizes Euler's equations in the propagation of the estimated rate. Finally, the question of closed-loop stability is addressed. The ability of the controller to meet the science slew requirements, without the gyros, is tested through simulations.
The Far Ultraviolet Spectroscopic Explorer (FUSE) is equipped with two ring laser gyros on each of the spacecraft body axes. In May 2001 one gyro failed. It is anticipated that all of the remaining gyros will fail, based on intensity warnings. In addition to the gyro failure, two of four reaction wheels failed in late 2001. The spacecraft control now relies heavily on magnetic torque to perform the necessary science maneuvers and hold on target. The only sensor consistently available during slews is a magnetometer. This paper documents the testing and development of magnetometer-based gyroless attitude and rate estimation algorithms for FUSE. The results of two approaches are presented, one relies on a kinematic model for propagation, a method used in aircraft tracking. The other is a pseudo-linear Kalman filter that utilizes Euler's equations in the propagation of the estimated rate. Both algorithms are tested using flight data collected over a few months after the reaction wheel failure. Finally, the question of closed-loop stability is addressed. The ability of the controller to meet the science slew requirements, without the gyros, is analyzed.
The Far Ultraviolet Spectroscopic Explorer (FUSE) is equipped with two ring laser gyros on each of the spacecraft body axes. In May 2001 one gyro failed. It is anticipated that all of the remaining gyros will also fail based on intensity warnings. In addition to the gyro failure, two of four reaction wheels failed in late 2001. The spacecraft control now relies heavily on magnetic torque to perform the necessary science maneuvers and hold on target. The only sensor consistently available during slews is a magnetometer. This paper documents the testing and development of magnetometer-based gyroless attitude and rate estimation algorithms for FUSE. The results of two approaches are presented, one relies on a kinematic model for propagation, a method used in aircraft tracking, and the other is a pseudo-linear Kalman filter that utilizes Euler's equations in the propagation of the estimated rate. Both algorithms are tested using flight data collected over a few months before and after the reaction wheel failure. Finally, the question of closed-loop stability is addressed. The ability of the controller to meet the science slew requirements, without the gyros, is tested through simulations.
Long range space missions will require high operational efficiency as well as autonomy to enhance the effectivity of performance. Fuzzy logic technology has been shown to be powerful and robust in interpreting imprecise measurements and generating appropriate control decisions for many space operations. Several applications are underway, studying the fuzzy logic approach to solving control and decision making problems. Fuzzy logic algorithms for relative motion and attitude control have been developed and demonstrated for proximity operations. Based on this experience, motion control algorithms that include obstacle avoidance were developed for a Mars Rover prototype for maneuvering during the sample collection process. A concept of an intelligent sensor system that can identify objects and track them continuously and learn from its environment is under development to support traffic management and proximity operations around the Space Station Freedom. For safe and reliable operation of Lunar/Mars based crew quarters, high speed controllers with ability to combine imprecise measurements from several sensors is required. A fuzzy logic approach that uses high speed fuzzy hardware chips is being studied.
A general star pattern recognition algorithm has been used to develop JPL's redundant, microcomputer-equipped ASTROS II CCD star tracker into a full-sky autonomous star tracker (FAST), capable of determining its attitude about all three axes without requiring any a priori attitude knowledge. A large field of view allows the number of guide stars in the all-sky data-base of the tracker to be limited to a manageable number, while high accuracy ensures that the pattern formed by the observed guide stars is unique. The recognition algorithm can also be used for automating the acquisition of celestial targets by astronomy telescopes, for autonomously updating the attitude of gyro-based attitude control systems, and for automating ground-based attitude recognition. Using both Monte Carlo simulations and a quasi-analytical method, it is shown that the general recognition algorithm and a less software-intensive special algorithm can be used to reliably automate the acquisition of celestial targets by astronomy telescopes.
During the Mars Exploration Rovers (MER) landings, the Descent Image Motion Estimation System (DIMES) was used for horizontal velocity estimation. The DIMES algorithm combines measurements from a descent camera, a radar altimeter and an inertial measurement unit. To deal with large changes in scale and orientation between descent images, the algorithm uses altitude and attitude measurements to rectify image data to level ground plane. Feature selection and tracking is employed in the rectified data to compute the horizontal motion between images. Differences of motion estimates are then compared to inertial measurements to verify correct feature tracking. DIMES combines sensor data from multiple sources in a novel way to create a low-cost, robust and computationally efficient velocity estimation solution, and DIMES is the first use of computer vision to control a spacecraft during planetary landing. In this paper, the detailed implementation of the DIMES algorithm and the results from the two landings on Mars are presented.
This work describes two algorithms for computing the angular rate and attitude in case of a gyro and a Star Tracker failure in the Microwave Anisotropy Probe (MAP) satellite, which was placed in the L2 parking point from where it collects data to determine the origin of the universe. The nature of the problem is described, two algorithms are suggested, an observability study is carried out and real MAP data are used to determine the merit of the algorithms. It is shown that one of the algorithms yields a good estimate of the rates but not of the attitude whereas the other algorithm yields a good estimate of the rate as well as two of the three attitude angles. The estimation of the third angle depends on the initial state estimate. There is a contradiction between this result and the outcome of the observability analysis. An explanation of this contradiction is given in the paper. Although this work treats a particular spacecraft, the conclusions have a far reaching consequence.
The navigation algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) were designed to meet the requirement of 1-pixel accuracy-a standard deviation (sigma) of 2. The objective has been to extract the best possible accuracy from the spacecraft telemetry and avoid the need for costly manual renavigation or geometric rectification. The requirement is addressed by postprocessing of both the Global Positioning System (GPS) receiver and Attitude Control System (ACS) data in the spacecraft telemetry stream. The navigation algorithms described are separated into four areas: orbit processing, attitude sensor processing, attitude determination, and final navigation processing. There has been substantial modification during the mission of the attitude determination and attitude sensor processing algorithms. For the former, the basic approach was completely changed during the first year of the mission, from a single-frame deterministic method to a Kalman smoother. This was done for several reasons: a) to improve the overall accuracy of the attitude determination, particularly near the sub-solar point; b) to reduce discontinuities; c) to support the single-ACS-string spacecraft operation that was started after the first mission year, which causes gaps in attitude sensor coverage; and d) to handle data quality problems (which became evident after launch) in the direct-broadcast data. The changes to the attitude sensor processing algorithms primarily involved the development of a model for the Earth horizon height, also needed for single-string operation; the incorporation of improved sensor calibration data; and improved data quality checking and smoothing to handle the data quality issues. The attitude sensor alignments have also been revised multiple times, generally in conjunction with the other changes. The orbit and final navigation processing algorithms have remained largely unchanged during the mission, aside from refinements to data quality checking. Although further improvements are certainly possible, future evolution of the algorithms is expected to be limited to refinements of the methods presented here, and no substantial changes are anticipated.
A comparison of six selected control moment gyro steering laws for use on the HEAO spacecraft is reported. Basic equations are developed to project the momentum and torque of four skewed, single gimbal CMGs into vehicle coordinates. In response to the spacecraft attitude error signal, six algorithms are derived for controlling the CMG gimbal movements. HEAO performance data are obtained using each steering law and compared on the basis of such factors as accuracy, complexity, singularities, gyro hang-up and failure adaption. Moreover, each law is simulated with and without a magnetic momentum management system. The performance of any steering law is enhanced by the magnetic system. Without magnetics, the gimbal angles get large and there are significant differences in steering law performances due to cross coupling and nonlinearities. The performance of the pseudo inverse law is recommended for HEAO.
An original technique for determining the optimal magnetic torque strategy for control of the attitude of spin stabilized spacecraft is presented. By employing Lagrange multipliers and the Calculus of Variations, optimal control equations are derived which define minimum time and minimum energy attitude maneuvers. Computer program algorithms to numerically solve these optimal control equations are also described. The performance of this technique is compared with a commonly employed planning method.
An adaptive concept which combines gain-scheduled control laws with explicit maximum likelihood estimation (MLE) identification to provide the scheduling values is described. The MLE algorithm was improved by incorporating attitude data, estimating gust statistics for setting filter gains, and improving parameter tracking during changing flight conditions. A lateral MLE algorithm was designed to improve true air speed and angle of attack estimates during lateral maneuvers. Relationships between the pitch axis sensors inherent in the MLE design were examined and used for sensor failure detection. Design details and simulation performance are presented for each of the three areas investigated.
The methods developed for analyses of the winds and of aircraft performance during an investigation of a downburst wind-shear-induced accident have been utilized in a more general study of aircraft performance in such encounters. The computed responses of a generic, large transport aircraft to take-off and approach encounters with a downburst wind field were used in examining the effects of performance factors and control procedures on the ability of the aircraft to survive. Obvious benefits are seen for higher initial encounter speeds, maximum thrust-weight values typical of two-engined aircraft, and immediacy of pilot response. The results of controlling to a constant, predetermined, pitch attitude are demonstrated. Control algorithms that sacrifice altitude for speed appear to provide a higher level of survivability, but guidance displays more explicitly defining flightpath than those commonly in use might be required.
A global algorithm for transforming rotation matrices to Euler parameters is presented. Although it has no apparent computational or numerical advantage over the known algorithms, it elucidates the relationship between the rotation matrix form and the Euler parameter form. It employs the singular-value decomposition, a numerically ideal algorithm involving orthogonal transformations. Attitude parameterization is reviewed and an analytical framework is provided.