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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Extended Kalman Filter for attitude estimation of the Earth Radiation Budget Satellite

The design and testing of an Extended Kalman Filter (EKF) for ground attitude determination, misalignment estimation and sensor calibration of the Earth Radiation Budget Satellite (ERBS) are described. Attitude is represented by the quaternion of rotation and the attitude estimation error is defined as an additive error. Quaternion normalization is used for increasing the convergence rate and for minimizing the need for filter tuning. The development of the filter dynamic model, the gyro error model and the measurement models of the sun sensors, the IR horizon scanner and the magnetometers which are used to generate vector measurements are also presented. The filter is applied to real data transmitted by ERBS sensors. Results are presented and analyzed and the EKF advantages as well as sensitivities are discussed. On the whole the filter meets the expected synergism, accuracy and robustness.

Deutschmann, Julie↗
NASA NTRS1992

A deterministic method for estimating attitude from magnetometer data only

A new deterministic algorithm which estimates spacecraft attitude utilizing magnetometer data only is presented. This algorithm exploits the dynamic equations of motion to propagate attitude and thus requires knowledge of both internal and external torques, except in the special case of a spacecraft rotating with constant angular velocity. Preliminary results obtained for the uncontrolled Relay Mirror Experiment satellite utilizing real telemetry data are reported.

Natanson, G. A.↗
NASA NTRS2007

Space Technology 5 Post-Launch Ground Attitude Estimation Experience

The Space Technology (ST)-5 satellites were launched March 22, 2006 on a Pegasus XL launch vehicle into a Sun-synchronous orbit. The three micro-satellites which constituted the ST-5 mission were kept in a formation which allowed three successive measurements taken of the Earth s magnetic field in order to study short term fluctuations of the field. The attitude of each satellite was computed on the ground using data from the science grade magnetometer as well as the miniature spinning Sun sensor (MSSS) which was the primary attitude sensor. Attitude and orbit maneuvers were performed using a single axial cold gas thruster. This paper describes the ground attitude estimation process and performance as well as anomaly resolutions.

Harman, Richard R.↗
NASA NTRS2016

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors.

estimation↗
NASA NTRS2016

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors

estimation↗
NASA NTRS1981

Efficient algorithms for single-axis attitude estimation

The computationally efficient algorithms determine attitude from the measurement of art lengths and dihedral angles. The dependence of these algorithms on the solution of trigonometric equations was reduced. Both single time and batch estimators are presented along with the covariance analysis of each algorithm.

Shuster, M. D.↗
NASA NTRS1997

Efficient Sequential Attitude Estimation from Vector Observations

This paper presents a computationally efficient, sequential method for attitude matrix estimation using gyro and vector measurements. The method is based on a recently introduced, minimal-parameter third-order method for solving the orthogonal matrix differential equation in R(sup n). In the three-dimensional case, these third-order attitude parameters can be interpreted as temporal-integrals of the body-frame angular velocity components. A nonlinear algorithm is developed, which uses this minimal set of three parameters to estimate the nine-parameter direction-cosine matrix. Having an extremely simple kinematic equation, these parameters render the resulting estimator highly computationally efficient. An orthogonalization procedure, incorporated into the measurement processing stage, enhances the accuracy and stability of the resulting algorithm, yet retains reasonable simplicity. The performance of the estimator is demonstrated via a Monte Carlo simulation study.

Oshman, Yaakov↗
NASA NTRS1999

How to Estimate Attitude from Vector Observations

The most robust estimators minimizing Wahba's loss function are Davenport's q method and the Singular Value Decomposition (SVD) method. The q method is faster than the SVD method with three or more measurements. The other algorithms are less robust since they solve the characteristic polynomial equation to find the maximum eigenvalue of Davenport's K matrix. They are only preferable when speed or processor power is an important consideration. Of these, Fast Optimal Attitude Matrix (FOAM) is the most robust and faster than the q method. Robustness is only an issue for measurements with widely differing accuracies, so the fastest algorithms, Quaternion ESTimator (QUEST), EStimator of the Optimal Quaternion (ESOQ), and ESOQ2, are well suited to star sensor applications.

Markley, F. Landis↗
NASA NTRS1993

H(sub infinity)-type filter for spacecraft attitude estimation

A nonlinear filtering theory from a deterministic point of view is presented and an application to attitude determination is considered. The approach that is taken in this paper is motivated largely by the H(sun infinity) control and estimation theory for linear systems which has been evolved within the last decade. Rather than formulating the estimation problem as a game played by two adversaries, as has been done in the linear case, we employ in this work some notions from the theory of dissipative systems as a vehicle for arriving at certain Hamilton-Jacobi inequality, which in turn, provides a solution to the filtering problem, whenever it is satisfied. Application of this method to a linear estimation problem and to the problem of estimating a spacecraft attitude quaternion and gyro drift bias vector are presented. In limiting cases, these give the Kalman filter and the extended Kalman filter, respectively. The main advantages of this approach over its probabilistic counterpart are that this approach does not require a prior knowledge of any statistics, and that in general it is more amenable to a quantitative assessment regarding approximations such as linearization, and that in certain cases this approach yields an exact solution to the nonlinear filtering.

Markley, F. Landis↗
NASA NTRS2010

System and method for correcting attitude estimation

A system includes an angular rate sensor disposed in a vehicle for providing angular rates of the vehicle, and an instrument disposed in the vehicle for providing line-of-sight control with respect to a line-of-sight reference. The instrument includes an integrator which is configured to integrate the angular rates of the vehicle to form non-compensated attitudes. Also included is a compensator coupled across the integrator, in a feed-forward loop, for receiving the angular rates of the vehicle and outputting compensated angular rates of the vehicle. A summer combines the non-compensated attitudes and the compensated angular rates of the to vehicle to form estimated vehicle attitudes for controlling the instrument with respect to the line-of-sight reference. The compensator is configured to provide error compensation to the instrument free-of any feedback loop that uses an error signal. The compensator may include a transfer function providing a fixed gain to the received angular rates of the vehicle. The compensator may, alternatively, include a is transfer function providing a variable gain as a function of frequency to operate on the received angular rates of the vehicle.

Josselson, Robert H.↗
NASA NTRS1993

Computationally efficient algorithms for real-time attitude estimation

For many practical spacecraft applications, algorithms for determining spacecraft attitude must combine inputs from diverse sensors and provide redundancy in the event of sensor failure. A Kalman filter is suitable for this task, however, it may impose a computational burden which may be avoided by sub optimal methods. A suboptimal estimator is presented which was implemented successfully on the Delta Star spacecraft which performed a 9 month SDI flight experiment in 1989. This design sought to minimize algorithm complexity to accommodate the limitations of an 8K guidance computer. The algorithm used is interpreted in the framework of Kalman filtering and a derivation is given for the computation.

Pringle, Steven R.↗
NASA NTRS2006

Deep impact attitude estimator design and flight performance

In July, 2005 Deep Impact successfully impacted comet Tempel-1 and imaged the crater evolution. To achieve this, an onboard autonomous navigation system had to estimate the trajectory and maneuver the Impactor spacecraft into the comet's path. A similar system, operating on the Flyby spacecraft, calculated the impact location for imaging. At the heart of each autonomous navigation system is the attitude and gyro bias estimator using star trackers and gyros. The encounter geometry and timing placed stringent demands on attitude bias magnitude and drift calling for sequenced tuning of the respective filters. This paper describes the attitude and gyro bias estimator algorithms, the estimator flight performance and particular challenges overcome by the team leading up to a spectacular encounter.

Tempel-1↗
NASA NTRS1997

The use of magnetic field data to estimate attitude and trajectory for the Rossi X-Ray Timing Explorer (RXTE)

A single augmented extended Kalman filter (EKF) is proposed for the simultaneous and autonomous estimation of spacecraft trajectory and attitude with data from the Rossi X-ray timing explorer (RXTE) magnetometer and gyro-measured body rates. The derivation of the EKF is outlined, including the measurement update and the propagation. The results from a 12 hour span of data are processed and compared with operational estimations computed at the NASA Goddard Space Flight Center (MD). The filter was found to be able to overcome very large initial errors and converge to steady state averages of less than 30 km in position, 0.05 km/s in velocity and 3 deg in attitude.

Deutschmann, Julie↗
NASA NTRS1984

Yaw Attitude Estimation for the Tracking and Data Relay Satellite System

The Tracking and Data Relay Satellite System (TDRSS) uses a groundbased attitude determination algorithm to open loop point the satellite's high data rate antennas. The spacecraft is able to measure its pitch and roll attitude, but its yaw attitude is periodically unobservable. The ground software uses a state-space estimator, an adaptation of a Luenberger observer, to predict the spacecraft yaw angle during these unobservable periods. It contains states associated with the roll/yaw dynamics and the on-board control law. The accuracy is limited by the modeling fidelity of the disturbance torques acting on the spacecraft. After initial operating problems were cleared up, the operation of the estimator has converged to predicted performance.

Staich, S.↗
NASA NTRS2021

Mars 2020 Radiometric Data and Telemetry Processing, Attitude Estimation, and Thruster Calibration for Orbit Determination

The Mars 2020 spacecraft was spin-stabilized during cruise, just like its predecessor, the Mars Science Laboratory. This spinning motion imparts a signature in the radiometric tracking data that must be dealt with in order to properly model the motion of the spacecraft's center of mass. We discuss how the Orbit Determination team pre-processed the data for efficient computations while also providing other benefits such as high-fidelity attitude modeling and on-board clock verification. Finally, we discuss the analysis and results of the in-flight thruster calibration activity.

Seubert, Jill↗
NASA NTRS1999

How to Estimate Attitude from Vector Observations

In many spacecraft attitude systems, the attitude observations are naturally represented as unit vectors. Typical examples are the unit vectors giving the direction to the sun or a star and the unit vector in the direction of the Earth's magnetic field. In 1965, Grace Wahba, proposed the following problem: Find the orthogonal matrix A with determinant +1 that minimizes the loss function L(A) is identity with 1/2(Sum from i a(sub i) (absolute value of b(sub i - A(r(sub i))(exp 2))) where the set of b(sub i) is a set of unit vectors measured in a spacecraft's body frame, the set of r(sub i) are the corresponding unit vectors in a reference frame, and the set of a(sub i) are non-negative weights. Wahba's problem can be related to Maximum Likelihood Estimation if the weights are chosen to be inverse variances, a(sub i) = sigma((sub -2). Wahba didn't assume this, but it will be convenient to assume it in this paper. Wahba'soptimality condition has provided the basis for many attitude determination algorithms. The purpose of this paper is to give an overview of the most popular and most promising algorithm and to provide accuracy and speed comparisons.

Markley,F. Landis↗
NASA NTRS1978

On attitude estimation schemes for fine-pointing control

This paper studies single-axis equations of motion that are applicable to a spacecraft or to a space experiment pointing assembly whose motion has been perfectly isolated from the carrier vehicle. It considers four state estimators for implementation in the control loop for a stellar observation experiment. The first three estimators are very general and do not make use of input torque in their prediction models, while the proposed fourth estimator utilizes this information. It is shown via closed-loop covariance analysis that the best achievable pointing performance with the best of the first three estimators is limited to about 0.125 arc-sec (rms) with the given rate-gyro and star-tracker inaccuracies. It is also shown that the fourth estimator has the capability of achieving a pointing performance far superior to the performance achievable using the first three estimators. The fourth estimator relies on the ability to accurately generate the desired control torque (i.e., low input noise).

Joshi, S. M.↗