Estimating Sun Vector Based on Limited In-Orbit Data

A gyroless deterministic attitude determination algorithm based on simulation of sun in eclipse is stated in this paper and has been compared to stochastic filters like extended Kalman filter and unscented Kalman filter. Attitude determination with low cost sensors such as magnometer and sun sensor results in usage of recursive algorithms such as Kalman filter which has the probability of divergence, but with deterministic point to point algorithm such as the one introduced in this paper we can be sure to have an attitude determination with a fixed maximum error. Proposed method has been compared with Extended Kalman Filter and Unscented Kalman filter due to its modeling error, robustness and amount of calculations. Attitude determination is based on magnetic sensors and sun sensors. Solar panels are modeled for a hexagonal satellite as an alternative for sun sensors and sun vector is derived from panels current.

Fault detection and isolation algorithms for LEO satellite attitude determination and control system using an approach for checking the statistical characteristics of EKF innovation sequence are proposed. The fault detection algorithm is based on statistic for the mathematical expectation of the spectral norm of the normalized innovation matrix of the EKF. This approach permits simultaneous real-time checking of the mathematical expectation and the variance of the innovation sequence and does not require a priori information about the faults and statistical characteristics of the system in fault cases. In this study an attitude estimation and control system for LEO satellite is proposed. To determine the attitude of the satellite, this system use algebraic method (two-vector algorithm). As a reference direction, the unit vectors toward the Sun, the Earth’s center, and the Earth magnetic field are used. Thus, it includes three different two-vector algorithms based on using the Earth’s magnetic field – the Sun vector, the Earth’s magnetic field – nadir vector, and nadir vector – the Sun vector couples. In order to increase the attitude determination accuracy, the redundant data processing algorithm, based on the Maximum Likelihood Method, is used. An extended Kalman filter has been developed for nonlinear rotational dynamics estimation of LEO satellite. Failures in the sensors affect the characteristics of the innovation sequence of the EKF. The failures that affect the mean and variance of the innovation sequence have been considered. The application of the proposed fault detection algorithm to the LEO satellite attitude determination and control system has shown that, sensor fault detection by the presented algorithm is possible in real time. Assuming that the effect of the faulty sensor on its channel is more significant than on the other channels, a sensor isolation method is presented by transforming n-dimensional innovation process to n one-dimensional processes. The simulations, carried out on a nonlinear dynamic model of the rotational motion of LEO satellite, confirm the theoretical results. The future work is to investigate the faults affecting the attitude dynamics e.g., actuator faults and to perform the integrated sensor/actuator FDI via innovation approach.

In this paper, an autonomous relative navigation and joint attitude determination algorithm in asteroid exploration descent stage is researched based on feature point information of perpendicular asteroid surface image observed by optical navigation camera, distance vectors from spacecraft to asteroid measured by three angled installed lidars and relative velocity increment measured by accelerometer when the relative distance vector to the centroid of asteroid can not be obtained. The inertial attitude of spacecraft is determined by sun vector, star vectors and inertial angular velocity respectively measured by sun sensor, star trackers and inertial reference unit. Also, in order to obtain measurement error model transferred from sensor noise, a covariance matrix solver considering error correlation is presented via the error model of normalized vector to first order. Numerical simulation and improved observability evaluation of filtering are undertaken to discuss the results of complete sensor observation and weak observation of lidars, and verify the effectiveness of the presented relative navigation and attitude determination algorithm.

Design and on-orbit performance of the attitude determination and control system for the ZDPS-1A pico-satellite

Midcourse Space Experiment attitude system performance for gyro disabled operations

This paper briefly explains the Attitude Determination and Control System of a 2U class nano-satellite. The primary sensors used for attitude determination are Sun Sensors and Magnetometer. The readings from these sensors, along with the values obtained from the International Geomagnetic Reference Field (IGRF) and sun model, are provided as inputs to the Quaternion Estimation (QUEST) algorithm. QUEST uses these values to calculate the optimum quaternion for obtaining the desired orientation. Then, the PD controller has been used for calculating the torque that needs to be applied to achieve the required orientation with the help of actuators (Magnetorquers and Reaction Wheel). However, in case of failure, if any of the sensors or actuators is unavailable, the system would not be able to provide the required accuracy for payload action. Hence, the requirement for different modes of ADCS by switching between sensors, actuators, or quaternion estimators was felt. This paper describes various possible failure cases and accordingly used ADCS modes. It schemes for different tolerance methods that can be used in the failure of one or more ADCS hardware. The paper is so structured that proper description of fault detection techniques for every sensor and actuator is done, which is later followed with a reconfiguration of ADCS onboard to overcome a failure autonomously. This paper also describes the implementation of a seven-state nonlinear filter, an Extended Kalman Filter (EKF) model which takes readings of Magnetometer and Gyroscope as input values, for quaternion estimation. The seven variable state vector consists of quaternion for aligning the body reference frame with the orbit reference frame, and the angular rate of the satellite concerning the inertial frame, and the six variable measurement vector consists of readings of Magnetometer and Gyroscope. The paper has an inclusion of a detailed explanation of the filter along with mathematical equations with the required series of graphs. Thus, this paper aims at explaining the controller as well as the hardware used in failure or eclipse conditions in nano-satellites where there is hardware limitation due to space environment constraints or failure and which gives the best possible pointing accuracy for the payload action.

Nanosatellites have become a common choice for certain space missions, principally in universities, due to their low production and launching costs and reduced developing time. However, they present some technological challenges. In a CubeSat, total mass and available electric power are very restricted. Therefore, subsystem components and payload must be designed to have the smallest size, mass, and power consumption possible for the mission. Regarding to Attitude Determination and Control System, one of restrictions in developing CubeSats is the need to use small and low-cost sensors which fulfill satellite building restrictions. Thus, commercial-off-the-shelf components are a common choice in CubeSat development, but these parts normally present high noise levels. Therefore, a multiplicative Kalman filter for attitude determination algorithm based on quaternions is proposed. Data are simulated using typical values for low-cost sensors, namely, 3-axes magnetometer, 3-axes gyroscope, and a sun sensor. Results are compared to the extended Kalman filter proposed for AAUSAT-3 satellite and to the QUEST method, showing a better precision and low execution time compared to other methods.

This paper proposes using TRIAD and Unscented Kalman Filter (UKF)algorithms in a sequential architecture as a part of the small satellite attitude estimation algorithm. This TRIAD+UKF approach can provide accurate attitude estimates for the satellite by calibrating the magnetometers in real-time. A complete calibration model for the magnetometers, considering bias, scale factor, soft iron and nonorthogonality errors, is assumed. In algorithm's first stage, the TRIAD uses the available vector measurements (e.g. from Sun sensor and magnetometers)to estimate a coarse attitude. In the second stage, these estimated values are used as quaternion measurements in the UKF algorithm, together with angular rate measurements provided by a triad of gyros. The state vector for the UKF is composed of the attitude, gyro biases and the magnetometer error terms. In result, we get fine attitude estimate for the satellite by calibrating the magnetometers against scaling, soft iron, nonorthogonality and bias errors in real-time. We evaluate the algorithm for a hypothetical nanosatellite by numerical simulations. The results show that the attitude of the satellite can be estimated with accuracy better than 1deg and the magnetometers can be fully calibrated.

The attitude determination system of the RAX satellite

This paper shows the design of a self-powered wireless digital sun sensor (including magnetometer). The information of satellite attitude and magnetic field intensity can be transferred to the attitude determination and control system (ADCS) through Bluetooth. Four solar cells in parallel connection and a super capacitor make sure that the sun sensor can work both in sunshine and shadow areas. The sun sensor meets the needs of microsatellite, which has small volume (30mm×30mm×12.5mm), low power (<50mW), large field of view (120°) and high precision (0.5°).

The requirements, technical approach, and key features of the attitude determination system (ADS) being developed for the Space Station Freedom are described. Use of current technology provides new capabilities for all attitude autonomous operation and rapid determination of attitude in a debris-filled environment. The ADS is implemented using star trackers with fixed mosaic array detectors and inertial sensors based on laser gyro technology. Star catalog characteristics, star identification techniques, the functional implementation of the ADS system, and the results of preliminary covariance performance analyses are presented. Covariance analysis indicates that the stringent accuracy requirements of the Space Station can be met with the baseline system. The automated ADS mechanization provides rapid attitude acquisition from any orientation where stars are visible; astronaut intervention is not required. The inertial sensors and the star trackers are on-orbit replaceable, are highly reliable, and promise long-life operation. >

A three-axis, magnetometer/Kalman filter, attitude-determination system for a spacecraft in low-altitude Earth orbit is developed, analyzed, and simulation tested. The motivation for developing this system is to achieve three-axis knowledge using magnetic field measurements only. The extended Kalman filter estimates the attitude, attitude rates, and constant disturbance torques. Covariance computation and simulation testing are used to evaluate performance. One test case, a gravity-gradient stabilized spacecraft with a pitch momentum wheel and a magnetically anchored damper, is a real satellite on which this attitude determination system will be used. The application to a nadir-pointing satellite and the estimation of disturbance torques represent the significant extensions contributed by this paper. Beyond its usefulness purely for attitude determination, this system could be used as a part of a low-cost, three-axis attitude stabilization system. I. Introduction T HE objective of this work has been to develop a low-cost system for estimation of three-axis, spacecraft-attitude information based solely on three-axis magnetometer measurements from one satellite orbit. Such a system will be useful for missions that operate in an inclined, low-Earth orbit and require only coarse attitude information. It can also serve as the sensor part of a low-cost, three-axis, closed-loop attitude control system or as a backup attitude estimator. A single three-axis magnetometer measurement can give only two-axes worth of attitude information and no attitude rate or disturbance torque information. Therefore, this attitude determination system must use a sequence of magnetometer measurements. It processes these measurements recursively in a Kalman filter. This paper describes the design, development, analysis, and simulation testing of a Kalman filter arid reports its expected peformance. A follow-on, postlaunch paper is planned to report actual performance.

A highly accurate, gyroless, attitude determination and control system for advanced environmental satellites is developed and validated by analysis and simulation. The features of this approach include an algorithm to determine satellite rates directly from the apparent motion of the stars on the focal plane and an extended square root Kalman filter algorithm to estimate attitude. This system is appropriate for satellites with slowly varying attitude dynamics and high priority accuracy. Missions of this variety are meteorology, Earth resources, communication and surveillance. Appropriate attitude control techniques are reaction wheel and bias momentum system providing three-axis pointing control. The simulation results of the attitude estimation with various noise statistics on the star data are shown. The results of this approach are also compared with the gyro-aided system in accuracy of the attitude estimation process. The results show that the concept presented in the paper does work and that the accuracy would meet a large variety of satellite mission requirements. The major result of this research is the realization of a space-capable stellar attitude determination system which does not require a rate gyro package.

Star Trackers are often the most accurate instrument in an Attitude Determination and Control Systems, but often present a slow update rate, requiring additional sensor and sensor fusion algorithms to provide a smoother and faster output. However, the available rate gyros are either noisy, or expensive and heavy. The proposed work investigates the feasibility of high-speed star trackers with modern optics, sensors, and computing systems. Firstly, we investigate the sensitivity of an optoelectrical acquisition system stimulated by dim stars, secondly, we propose and evaluate an algorithm designed to operate at high speed and to be compatible with an Field-Programmable Gate Array implementation, before evaluating the performance of the implementation on FPGA. Finally, we debate the usability of such a system, both in terms of compatibility with a mission and CubeSat ecosystems, and in terms of performance. As a result, aside from removing the need for a rate gyro, Attitude Determination and Control Systems overall pointing performances can be increased. The proposed attitude determination system achieved a 0.001° accuracy, with a 99.1% sky coverage and an ability to reject false-positive while performing a single-frame lost-in-space star identification at a 50 Hz update rate with a total delay of 19 ms, including 13 ms.

This paper discusses the attitude determination of the CNUSAIL-1 cube-satellite. The primary mission of the CNUSAIL-1 is sail deployment and operation in low Earth orbit, and the secondary mission is to look into influence of the sail deployment on satellite attitude and orbit. The attitude determination strategy is proposed depending on three mission phases, and its performance and applicability are verified through numerical simulations. This study considers the following sensors: Sun sensors and a three-axis magnetometer as attitude reference sensors, and a three-axis MEMS gyroscope as an inertial attitude sensor. Because sensors used for cube satellites have relatively low performances and worse noise characteristics, an Extended Kalman filter (EKF) is applied to attitude determination. Additionally, it has the merits to deal with the Gaussian noises and to predict the attitude even with no measurements from reference attitude sensors, especially in the eclipse of the cube satellite. The performance of the EKF is compared to a deterministic attitude determination technique, QUEST(QUaternion ESTimation).