Attitude determination concepts for the Space Station Freedom

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.

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.

As part of our recent research to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicle (UAV) applications, we investigated the potential of carrier-phase Global Navigation Satellite System (GNSS) for attitude determination and control of small size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro- Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD)sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.

In designing the attitude determination and control system (ADCS) of a satellite, the system cannot be modeled as a dimensionless point object. A practical object has physical size and thus rotates as well as translates. Such bodies are termed rigid bodies. Its dynamics is characterized by six degrees of freedom. Three degrees of freedom represent the motion of the center of mass. The other three degrees address the rotational motion of the object. The 6-DoF must be dynamically controlled. Traditionally, attitude determination involved using both rate gyros and star trackers. Rate gyros are prone to mechanical failure. Hence it is proposed to study the feasibility of replacing rate gyros with star sensors for attitude determination. A Kalman filter provides an optimal means to estimate the state of the system. Results show that the rates can be estimated to within 10/sup -7/ rad/s which is as good as from a gyroscope.

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.

In order to enhance the accuracy and the robustness of the attitude determination and control system in observation satellites, a new way to fuse gyro and star tracker measurement with image registration is described. In this method, a novel and complete framework is proposed to estimate the on-orbit attitude variations from multi-spectrum remote sensing images. An extended Kalman filter is derived to calibrate the gyro bias drift and the star tracker error. The new framework is tested with realistically simulated data and remote sensing images based on JL-1 satellite. Simulation and experiment results indicate that based on the image registration, the satellite attitude variations could be detected in real time and applied for the accurate gyro and star tracker bias calibration.

This paper shows the design and development of a truly low cost attitude determination and navigation system based primarily on non-dedicated mass market GNSS receivers and antennas, aided by MEMS inertial sensors. GNSS/INS integration combines the advantages of absolute satellite-based positioning with the high dynamic performance and data rates of inertial sensors, having become the standard approach in navigation systems for Unmanned Aerial Vehicles (UAV) among other applications. We have used a Tightly-Coupled (TC) algorithm aimed at the integration of GPS and INS devices, designed to exploit the measurements provided by four GNSS receivers and a MEMS IMU. This task is accomplished by forming double differences (DD) of carrier-phase measurements and properly solving the ambiguities on-the-fly. The robustness of the algorithm is enhanced by exploiting unambiguous DD of code-phase observables or un-differenced pseudoranges when carrier phase ambiguity fix is not reliable. In order to limit the unwanted effects of vibration, the INS raw samples (i.e. gyro and accelerometer measurements) are passed through a proper low-pass filter before being used by the fusion algorithm. Furthermore, we have constrained the TC algorithm with the heading information obtained from the DD carrier-phase measurements of four GNSS receivers that are available in the final system. These carrier-phase measurements need to be processed and their ambiguities solved before becoming usable, for which proper integer ambiguity resolution methods are described too. Achieving the realization of the first prototype relies on advances beyond the state-of-the-art in the fields of multi-receiver GNSS-based attitude determination, inertial MEMS/GNSS data fusion and precise calibration of properly selected GNSS antennas. All these advances aim at optimizing the cost, weight, size and power consumption of the overall system to enable its use in one of the most demanding applications as is the control and navigation of small UAV. The feasibility of a real-time implementation has been demonstrated. We have run the designed TC algorithm first onboard a car for validating the implementation by gathering real data in different user configurations (i.e. static and dynamic) and environmental scenarios (open-sky, urban canyon, etc.). For performance evaluation of the real-time system the prototype was mounted onboard the target UAV as a sample case of aerial applications.

This paper presents a novel approach to the attitude determination problem of space vehicles. The proposed algorithm utilizes a modified Genetic Algorithm (GA) to solve the “lost in space” star pattern recognition problem associated with star tracker attitude determination systems. Characteristics of the stars that are visible within the Field of View (FOV) – reflected on an image taken by the onboard star tracker – are formulated using simple geometric descriptions. The proposed GA minimizes the discrepancy between the characteristics of the stars inside the actual FOV and a candidate FOV selected from the on board stored star map. The global minimum of the discrepancy represents the inertial coordinates of the FOV bore-sight. The concept of a Spiral Genetic Algorithms (SGA) is proposed where the search area decreases for consecutive GA, with consequently tighter constraints, making it converge to the desired location. Also the algorithm presented has the capability of determining the rotational angle between the spacecraft’s coordinate system and that of a real star map. Simulation results indicate competitive results to current star trackers in terms of accuracy.

As the satellite attitude determination system is a typical non-linear system, the application of non-linear Kalman filter in the satellite attitude determination system is necessary. Aiming at the satellite Star-sensor/Gyro attitude determination system, the application of Cubature Kalman filter in satellite Star-sensor/Gyro attitude determination system is discussed in this paper. Firstly, 2n cubature point are generated basing on the cubature principle; then transform the points into new ones by non-linear system equations; finally, apply the new points to the update of system state. Simulation results show that CKF is better than EKF and UKF in accuracy and stability.

The attitude determination system of the RAX satellite

In this paper, a laboratory model is designed to evaluate the performance of star tracker algorithms for attitude determination of a satellite. Star tracker is the most accurate attitude sensor that determines satellite direction by applying centroiding algorithm, star identification and attitude determination. To utilize such algorithms, first, high quality of star images are needed which should be provided through the star tracker camera. Then, such images are given to processors and it determines the attitude of camera and satellite in three axes based on mentioned algorithms. First, in preliminary design, we define important star tracker parameters, like accuracy, detector, processor and field of view. In this paper, we have considered the range accuracy in yaw/pitch axis less than 20 arcsec and for roll axis less than 100 arcsec. To improve the attitude determination accuracy, we have applied an adaptive structure in centroiding algorithm, as only brightness stars are selected and identification algorithm is done based on them. Another important parameter is speed of identification algorithm which is handled by an ARM processor and improving pyramid algorithm, we reached less than 25 ms. Duo to this time, updating rate would be desired. Also knowing the coordination of bore sight direction that is distance between focal lens and imager is another important parameter that affects the accuracy of attitude and by ground calibration of camera, this parameter could be estimated carefully. Finally, implementation results on real images that are captured by a star tracker demonstrate optimum performance of algorithms.

Attitude determination system is one of the most important system to control the moving object of any type. GNSS attitude determination systems have been actively developed in the last decade. Such systems have obvious drawbacks associated with the need for the visibility of a sufficient number of satellites. GNSS/Inertial integration is the best way to reduce satellite visibility dependence. The new concept of multiple antenna integrated inertial-satellite system design is proposed. System structure allows to exclude accelerometers from inertial measurement unit replacing it with gyro unit only. An important feature of the system is the availability of the initialization mode in motion and in conditions of limited satellite visibility. System performance was estimated in simulation and car test.

TUGSAT-1/BRITE-Austria—The first Austrian nanosatellite

This paper presents a new scheme for fault detection and diagnosis in spacecraft Attitude Determination (AD) sensors. An integrated attitude determination system, which includes measurements of rate and angular position using rate gyros and vector sensors, is developed. Measurement data from all sensors are fused by a linearized Kalman filter, which is designed based on the system kinematics, to provide attitude estimation and the values of the gyro bias. Using this information the erroneous sensor measurements are corrected, and unbounded sensor measurement errors are avoided. The resulting bias-free data are used in the Fault Detection and Diagnosis (FDD) scheme. The FDD algorithm uses model-based state estimation, combining the information from the rotational dynamics and kinematics of a spacecraft with the sensor measurements to predict the future sensor outputs. Fault isolation is performed through Extended Kalman Filters (EKFs). The innovation sequences of EKFs are monitored by several statistical tests to detect the presence of a failure and to localize the failures in all AD sensors. The isolation procedure is developed in two phases. In the first phase, two EKFs are designed, which use subsets of measurements to provide state estimates and form residuals, which are used to verify the source of the fault. In the second phase of isolation, testing of multiple hypotheses is performed. The generalized likelihood ratio test is utilized to identify the faulty components. In the scheme developed in this paper a relatively small number of hypotheses is used, which results in faster isolation and highly distinguishable fault signatures. An important feature of the developed FDD scheme is that it can provide attitude estimations in presence of fault in one type of sensors.