Initial Attitude Determination Using a Single Star Sensor

2003

In this paper, two different algorithms are presented for the estimation of spacecraft body angular rates in the absence of gyro rate data for a star tracker mission. In first approach, body angular rates are estimated with the spacecraft attitude using a dynamical model of the spacecraft. The second approach makes use of a rapid update rate of star camera to estimate the spacecraft body angular rates independent of spacecraft attitude. Essentially the image flow of the stars is used to establish a Kalman filter for estimating the angular velocity. The relative merits of both the algorithms are then studied for the spacecraft body angular rates measurements. The second approach has an

An efficient Kalman filter based algorithm has been proposed for the spacecraft attitude estimation problem using a novel split-field-of-view star camera and three-axis rate gyros. The conventional spacecraft attitude algorithm has been modified for on-orbit estimation of interlock angles between the two fields of view of star camera, gyro axis, and the spacecraft body frame. Real time estimation of the interlock angles makes the attitude estimates more robust to thermal and environmental effects than in-ground estimation, and makes the overall system more tolerant of off-nominal structural, mechanical, and optical assembly anomalies.

The Journal of the Astronautical Sciences, 2007

An efficient Kalman filter based algorithm has been proposed for the spacecraft attitude estimation problem using a novel split-field-of-view star camera and three-axis rate gyros. The conventional spacecraft attitude algorithm has been modified for on-orbit estimation of interlock angles between the two fields of view of star camera, gyro axis, and the spacecraft body frame. Real time estimation of the interlock angles makes the attitude estimates more robust to thermal and environmental effects than in-ground estimation, and makes the overall system more tolerant of off-nominal structural, mechanical, and optical assembly anomalies.

1997

This paper presents the ESOQ-2 algorithm which, based on vector observations, optimally estimates the quaternion describing the spacecraft attitude. The q-Method solution equation, written in terms of the principal axis and angle, allows the computation of the optimal principal axis as a simple vector cross product. The optimal quaternion is then immediately derived. The introduced singularity, which occurs when the principal angle is very small, is optimally avoided by employing only one sequential rotation. The resulting proposed ESOQ-2 algorithm is reliable, nonsingular, easy to code, and able to identify the "quasi-parallel" condition, when the attitude computation is impossible. Numerical tests in computational speed show ESOQ-2 faster than ESOQ, up to now the fastest available optimal attitude estimation algorithm. Nomenclature A, T = Estimation and true attitude matrix (direction-cosine matrix) 2 e, Φ = principal axis (eigenaxis, Euler axis) and principal angle (eigenangle, Euler angle) s, v = Observed and referenced direction (unit vector) α = Relative precision of attitude sensor B, z = Attitude data matrix and vector λ = Eigenvalue, Lagrangian multiplier

2000

A novel split field of view star tracker is being developed for the EO-3 GIFTS mission (2004). The camera is designed to be autonomously selfcalibrating, and capable of a rapid/reliable solution of the lost-in-space problem as well as recursive attitude estimation. Two efficient Kalman filter algorithms for attitude, camera principal point offset, and focal length estimation are developed. These algorithms make use of three axis gyros for the rate data and star camera split field-of-view line-of-sight vector measurements. To model the optics of the camera the pinhole model is used, which is found to be sufficiently accurate for most of star cameras. The relative merits of the two algorithms are then studied for estimating the principal point offset, focal length and attitude of a simulated spacecraft motion. Simulation results indicate that both algorithms produce precise attitude estimates by determining the principal point offset, focal length and rate bias; however, reliability and robustness characteristics favor the second algorithm.

Journal of Aerospace Engineering, Sciences and Applications, 2011

The aim of this work is to test an algorithm to estimate, in real time, the attitude of an artificial satellite using real data supplied by attitude sensors that are on board of the CBERS-2 satellite China Brazil Earth Resources Satellite . The real-time estimator used in this work for attitude determination is the Unscented Kalman Filter. This filter is a new alternative to the extended Kalman filter usually applied to the estimation and control problems of attitude and orbit. This algorithm is capable of carrying out estimation of the states of nonlinear systems, without the necessity of linearization of the nonlinear functions present in the model. This estimation is possible due to a transformation that generates a set of vectors that, suffering a nonlinear transformation, preserves the same mean and covariance of the random variables before the transformation. The performance will be evaluated and analyzed through the comparison between the Unscented Kalman filter and the extended Kalman filter results, by using real onboard data.

Transactions of the Japan Society for Aeronautical and Space Sciences, Space Technology Japan

Advances in Estimation, Navigation, and Spacecraft Control, 2015

Attitude determination, along with attitude control, is critical to functioning of every space mission. In this paper, we investigate and compare, through simulation, the application of two autonomous sequential attitude estimation algorithms, adopted from the literature, for attitude determination using attitude sensors (sun sensor and horizon sensors) and rate-integrating gyros. The two algorithms include a direction cosine matrix (DCM) based steady-state Kalman Filter and the classic quaternion-based Extended Kalman Filter. To make the analysis realistic, as well as to improve the design of the attitude determination algorithms, detailed sensor measurement models are developed. Modifications in the attitude determination algorithms, through estimation of additional states, to account for sensor biases and misalignments have been presented. A modular six degree-of-freedom closed-loop simulation, developed in house, is used to observe and compare the performances of the attitude determination algorithms.

2012

This paper describes a path toward the development of theory for using a low noise high frame rate camera as a star tracker for spacecraft attitude estimation. The benefit of using a low noise high frame rate camera is that s ar data can be sampled at a faster rate while allowing one to measure very di m stars, increasing the number of stars available for attitude estimation. The d evelopment of a noise model is discussed and an algorithm to process raw data is sho wn. An attitude estimation method is discussed and simulated data is shown. A simulated star tracker for attitude estimation is shown and attitude estim ation results are shown.

AIAA Guidance, Navigation, and Control Conference, 2012

2000

A novel attitude determination approach is presented and results from night sky validation tests are discussed. The central ideas are extensions of the K-Vector method recently introduced by Mortari. It involves a construction of a judicious "star pair catalog" prior to launch, wherein all cataloged stars are considered as star pairs and are ordered {k = 1, 2 , …. N~O(10 6 )}, over the whole sky, sorted in the order of increasing inter-star angle. From this, we have a "searchless" means to access the candidate set of stars for each measured star pair, but this K-Vector method may still give 10s and sometimes 100s of candidate stars for each measured pair. We introduce in this paper a method to identify the measured stars in the subset of candidate stars accessed using the K-vector. The new method is based upon a logical process which pivots about two stars (the first identified pair) to more efficiently identify or ignore the remaining measured stars. Using this Pivot Method, we show that star identification can be reliably and efficiently implemented on-orbit, even for the Lost-In-Space case, and thereby this paper introduces a globally valid process, consistent with real-time, on-board computational constraints, that solves the most fundamental problem associated with star pattern identification. Results from night sky experiments are discussed which support the validity of the analysis and practicality of this approach. Also discussed are plans for on-orbit experiments. The StarNav experiment is planned for Shuttle Mission STS 107, January 2000; this will represent the first ever onorbit demonstration of a star sensor implementing a Lost-In-Space star identification and attitude determination process.

Acta Astronautica, 2010

Spacecraft attitude estimation based on the nonlinear unscented filter is addressed to fully utilize capabilities of the unscented transformation. To overcome significant computational load, an efficient technique is proposed by appropriately eliminating correlation between random variables. This modification leads to a considerable reduction of computational burden in matrix square-root calculation for most nonlinear systems. The unscented filter makes use of a set of sample points to predict mean and covariance. For attitude estimation based on quaternions, an approach to computing quaternion means from sampled quaternions with guarantee of the normalization constraint is described by using a constrained optimization technique. Finally, the performance of the new approach is demonstrated by attitude determination using a star tracker and rate-gyro measurements.

Astrophysics and Space Science Library, 1978

2012

A stellar gyroscope is a star based attitude propagator that is capable of propagating a spacecraft's attitude in three degrees of freedom by tracking the motion of the stars in an imager's field of view. The modeling and algorithm development has been done by the Space Systems Laboratory at the University of Kentucky. This paper discusses a realization of the stellar gyroscope concept on a CubeSat attitude determination and control system (ADCS) designed by SSBV Space & Ground Systems UK. The stellar gyroscope can be used to measure attitude changes from a known initial condition without drift while sufficient stars are common across frames, because absolute attitude changes are measured and not angular rates. Algorithms to perform the star detection, correspondence, and attitude propagation are presented in this paper. The Random Sample Consensus (RANSAC) approach is applied to the correspondence problem which is challenging due to spurious false-star detections, missed stars, stars leaving the field of view, and new stars entering the field of view. The CubeSat attitude determination and control system described in this paper uses a stellar gyroscope, implemented using inexpensive optics and sensor, to augment a MEMS gyroscope attitude propagation algorithm to minimize drift in the absence of an absolute attitude sensor. The MEMS device provides the high frequency measurement updates required by the control system, and the stellar gyroscope, at a lower update rate, resets the drift accumulated in the MEMS inertial gyroscope integrator. This in effect could allow sun-sensing satellites to maintain a high quality attitude estimate in eclipse, where the sun sensors can no longer contribute in absolute attitude estimates. This paper describes an algorithm to solve the relative attitude problem by identifying the change in attitude between two star field images. RANSAC is applied to solve the correspondence problem in the presence of false star detections and misses. The camera and attitude determination and control system are described, prototype hardware is used to generate night-sky datasets of known attitude changes to demonstrate the performance of the algorithm, and a simulation is developed to evaluate the stellar gyroscope's ability in limiting the drift of an attitude propagator based on MEMS gyroscope rates. The CubeSat ADCS system developed by SSBV is an experiment on TechDemoSat-1, to be launched in early 2013.

2003

This paper presents a study using Genetic Algorithms (GA) to solve the star pattern recognition problem associated with star tracker attitude determination systems. Characteristics of the stars that are visible within the Field of View (FOV) of an imager are defined with regard to relative distances and angles. The proposed GA minimizes the discrepancy between the characteristics of the stars inside the actual FOV and a candidate FOV selected from the star map in order to determine the inertial coordinates of the FOV bore sight. The proposed algorithm has the capability of determining the rotational angle between the spacecraft's coordinate system and that of a standardized star map. Simulations indicate that the GA approach is highly suited for this type of problem.