Magnetometer-Only Kalman Filter Based Algorithms for High Accuracy Spacecraft Attitude Estimation (A Comparative Analysis)

Kalman Filter (KF) based algorithms are the most frequently employed attitude estimation algorithms. Typically, a fully observable system necessitates the use of two distinct sensor types. Therefore, relying on a single sensor, such as a magnetometer, for spacecraft attitude estimation is deemed to be a challenge. The present investigation centers on utilizing magnetometers as the exclusive sensor. Several KF based estimation algorithms have been designed and evaluated to give the designer of spacecraft Attitude and Orbit Control System (AOCS) the choice of a suitable algorithm for his mission based on quantitative measures. These algorithms are capable of effectively addressing nonlinearity in both process and measurement models. The algorithms under examination encompass the Extended Kalman Filter (EKF), Sequential Extended Kalman Filter (SEKF), Pseudo Linear Kalman Filter (PSELIKA), Unscented Kalman Filter (USKF), and Derivative Free Extended Kalman Filter (DFEKF). The comparison of the distinct algorithms hinges on key performance metrics, such as estimation error for each axis, computation time, and convergence rate. The resulting algorithms provide numerous benefits, such as diverse levels of high estimation accuracy (with estimation errors ranging from 0.014o to 0.14o), varying computational demands (execution time ranges from 0.0536s to 0.0584s), and the capability to converge despite large initial attitude estimation errors (which reached 170o). These properties render the algorithms appropriate for utilization by spacecraft designers in all operational modes, supplying high-precision attitude estimations better than (0.5o) despite high magnetometer noise levels, which reached (200 nT)

A Sounding Rocket Attitude Determination Algorithm Suitable For Implementation Using Low Cost Sensors

Thesis (Ph.D.) University of Alaska Fairbanks, 2003The development of low-cost sensors has generated a corresponding movement to integrate them into many different applications. One such application is determining the rotational attitude of an object. Since many of these low-cost sensors are less accurate than their more expensive counterparts, their noisy measurements must be filtered to obtain optimum results. This work describes the development, testing, and evaluation of four filtering algorithms for the nonlinear sounding rocket attitude determination problem. Sun sensor, magnetometer, and rate sensor measurements are simulated. A quatenion formulation is used to avoid singularity problems associated with Euler angles and other three-parameter approaches. Prior to filtering, Gauss-Newton error minimization is used to reduce the six reference vector components to four quaternion components that minimize a quadratic error function. Two of the algorithms are based on the traditional extended Kalman filter (EKF) and two are based on the recently developed unscented Kalman filter (UKF). One of each incorporates rate measurements, while the others rely on differencing quaternions. All incorporate a simplified process model for state propagation allowing the algorithms to be applied to rockets with different physical characteristics, or even to other platforms. Simulated data are used to develop and test the algorithms, and each successfully estimates the attitude motion of the rocket, to varying degrees of accuracy. The UKF-based filter that incorporates rate sensor measurements demonstrates a clear performance advantage over both EKFs and the UKF without rate measurements. This is due to its superior mean and covariance propagation characteristics and the fact that differencing generates noisier rates than measuring. For one sample case, the "pointing accuracy" of the rocket spin axis is improved by approximately 39 percent over the EKF that uses rate measurements and by 40 percent over the UKF without rates. The performance of this UKF-based algorithm is evaluated under other-than-nominal conditions and proves robust with respect to data dropouts, motion other than predicted and over a wide range of sensor accuracies. This UKF-based algorithm provides a viable low cost alternative to the expensive attitude determination systems currently employed on sounding rockets

UNSCENTED GUIDANCE FOR POINT-TO-POINT REACTION WHEEL MANEUVERS

Attitude control system failures are often mission ending even when the mission payload remains operational. In this dissertation, the concept of unscented guidance is applied to reorient a reaction wheel satellite in the absence of feedback from star trackers or an inertial measurement unit (IMU). It is shown that an open-loop maneuver, properly designed using optimal control theory, can be used to achieve terminal attitude errors that are comparable with closed-loop control in the presence of uncertainty in the satellite inertia tensor. Typically, coarse closed-loop control is used to achieve < 1 degree pointing accuracy before more accurate pointing is done using fine guidance sensors to close the loop for science acquisition. It is shown that reaction wheel maneuvers designed using unscented guidance can also achieve sub-degree pointing accuracy of the spacecraft, making control hand-off to a functioning fine pointing control mode possible. The approach presented here enables large angle attitude control to be recovered so that mission operations may be continued despite IMU or star tracker failures.DoD Space, Chantilly, VA 20151Civilian, Department of the NavyApproved for public release. Distribution is unlimited

QMRPF-UKF Master-Slave Filtering for the Attitude Determination of Micro-Nano Satellites Using Gyro and Magnetometer

In this paper, the problem of estimating the attitude of a micro-nano satellite, obtaining geomagnetic field measurements via a three-axis magnetometer and obtaining angle rate via gyro, is considered. For this application, a QMRPF-UKF master-slave filtering method is proposed, which uses the QMRPF and UKF algorithms to estimate the rotation quaternion and the gyro bias parameters, respectively. The computational complexicity related to the particle filtering technique is eliminated by introducing a multiresolution approach that permits a significant reduction in the number of particles. This renders QMRPF-UKF master-slave filter computationally efficient and enables its implementation with a remarkably small number of particles. Simulation results by using QMRPF-UKF are given, which demonstrate the validity of the QMRPF-UKF nonlinear filter

Design and implementation of an attitude determination and control system for the AntelSat

This thesis describes the design, analysis and construction of the Attitude Determination and Control System (ADCS) for the first Uruguayan nanosatellite, the AntelSat. The AntelSat project is a joint venture between the Electrical Engineering Institute (IIE) of Faculty of Engineering, Universidad de la República (UdelaR University) and Antel, the Uruguayan national telecommunications company. The satellite consists of a two-unit (2U) CubeSat, which implies that the ADCS is designed under tight mass, size, and energy constraints. In addition, these kind of satellites usually have limited sensing, computational and communication capabilities, motivating the need for autonomous and computationally eficient algorithms. Under these strict restraints, developing an effective attitude control system poses a significant challenge. As presented in this thesis, for the attitude determination section of the ADCS, data available from sensors is taken as inputs for the computation of an optimal quaternion estimator. The use of a quaternion implementation of an unscented Kalman filter is also discussed. Additionally, attitude control is based on magnetic actuation with magnetorquers being commanded by pulse width modulation. It is shown that the control system is able to achieve the detumbling of the satellite after separation from the launch interface using the reliable B-dot control law. Nadirpointing control is achieved with the use of a simple Linear Quadratic Regulator. Also pertinent is the simulation environment that was implemented to develop the attitude determination and control algorithms and also to validate their performance. ADCS hardware prototypes and flight versions that were designed and constructed are introduced.Este documento de tesis describe el diseño, análisis y construcción de el Sistema de Determinación y Control de Actitud (ADCS por sus siglas en inglés) del primer satélite uruguayo, el AntelSat. El proyecto AntelSat es una actividad conjunta entre el Instituto de Ingeniería Eléctrica (IIE) de la Facultad de Ingeniería de la Universidad de la República y Antel, la empresa de telecomunicaciones nacional de Uruguay. El satélite consiste en un CubeSat de dos unidades (2U), lo que implica que el ADCS es diseñado bajo estrictas restricciones de masa, tamaño y energía. Además, este tipo de satélites posee una capacidad computacional, de comunicaciones y de medición limitada, lo que motiva la necesidad de lograr algoritmos computacionalmente eficientes. Bajo estas estrictas limitaciones, el desarrollo de un sistema de control de actitud efectivo se traduce en un reto importante. Como se presenta en esta tesis, para el segmento de determinación de actitud del ADCS, la información proveniente de los sensores es tomada como entrada para el cálculo de un estimador de cuaternión óptimo. Se discute también el uso de una implementación con cuaterniones de un filtro de Kalman "unscented". Por otro lado, el control de actitud está basado en actuación magnética con magnetorquers comandados con modulación de ancho de pulso. Se demuestra que el sistema de control es capaz de reducir el valor de velocidad angular del satélite en la fase previa a la separación con la interfaz de lanzamiento, mediante la utilización del algoritmo B-dot. La estabilización de la actitud en modo de apunte al nadir se logra con el uso de un simple regulador lineal cuadrático. Por otra parte, se presenta el entorno de simulación que fue implementado para el desarrollo de algoritmos de determinación y control de actitud, y también para validar el desempeño de los mismos. A su vez, se exhiben el hardware del ADCS que fue diseñado y construido, tanto prototipos como versiones de vuelo

On-Orbit Calibration of Photodiodes for Attitude Determination

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140645/1/1.g000175.pd

Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter

This paper presents the Quaternion-based Robust Adaptive Unscented Kalman Filter (QRAUKF) for attitude estimation. The proposed methodology modifies and extends the standard UKF equations to consistently accommodate the non-Euclidean algebra of unit quaternions and to add robustness to fast and slow variations in the measurement uncertainty. To deal with slow time-varying perturbations in the sensors, an adaptive strategy based on covariance matching that tunes the measurement covariance matrix online is used. Additionally, an outlier detector algorithm is adopted to identify abrupt changes in the UKF innovation, thus rejecting fast perturbations. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as external magnetic field interference and linear accelerations. Comparative experimental results that use an industrial manipulator robot as ground truth suggest that our method overcomes a trusted commercial solution and other widely used open source algorithms found in the literature