Micro-satellite Attitude Determination Research Articles

Innovative Exploration of a Bio-Inspired Sensor Fusion Algorithm: Enhancing Micro Satellite Functionality through Touretsky's Decentralized Neural Networks

Insect-inspired sensor fusion algorithms have presented a promising avenue in the development of robust and efficient systems, owing to the insects' ability to process numerous streams of noisy sensory data. The ring attractor neural network architecture has been identified as a noteworthy model for the optimal integration of diverse insect sensors. Expanding on this, our research presents an innovative bio-inspired ring attractor neural network architecture designed to augment the performance of microsatellite attitude determination systems through the fusion of data from multiple gyroscopic sensors.Extensive simulations using a nonlinear model of the microsatellite, while incorporating specific navigational disturbances, have been conducted to ascertain the viability and effectiveness of this approach. The results obtained have been superior to those of alternative methodologies, thus highlighting the potential of our proposed bio-inspired fusion technique. The findings indicate that this approach could significantly improve the accuracy and robustness of microsatellite systems across a wide range of applications.

Microsatellite attitude determination based on skylight polarization and geomagnetic measurement

A new attitude determination method based on skylight polarization sensors and magnetometers is proposed for microsatellites in the low earth orbits. First, a two-channel polarization sensor is developed to measure skylight polarization and obtain the solar direction information. Second, the measurement model of the polarization sensor and three-axis magnetometer are derived. Finally, with the satellite attitude equation as the state equation, an extended Kalman filter is developed to estimate the satellite attitude. Simulation results manifested the feasibility of using polarization sensors and magnetometers to determine the attitude information of low earth orbit microsatellite.

Analytical study of microsatellite attitude determination algorithms

An analytical approach to study of attitude determination algorithms is considered. The approach is applicable for quasi-stationary motion determination. It is based on filter post-convergence computation of the Kalman filter covariance matrix and allows one to estimate the influence of unaccounted perturbations on motion determination accuracy. The dependence of attitude determination accuracy on filter parameters and perturbations is obtained. The proposed method of improving the Kalman filter performance is applied on board a microsatellite of the TabletSat series.

Microsatellite Attitude Determination and Control Subsystem Design and Implementation: Software-in-the-Loop Approach

The paper describes the development of a microsatellite attitude determination and control subsystem (ADCS) and verification of its functionality by software-in-the-loop (SIL) method. The role of ADCS is to provide attitude control functions, including the de-tumbling and stabilizing the satellite angular velocity, and as well as estimating the orbit and attitude information during the satellite operation. In Taiwan, Air Force Institute of Technology (AFIT), dedicating for students to design experimental low earth orbit micro-satellite, called AFITsat. For AFITsat, the operation of the ADCS consists of three modes which are initialization mode, detumbling mode, and normal mode, respectively. During the initialization mode, ADCS collects the early orbit measurement data from various sensors so that the data can be downlinked to the ground station for further analysis. As particularly emphasized in this paper, during the detumbling mode, ADCS implements the thrusters in plus-wide modulation control method to decrease the satellite angular velocity. ADCS provides the attitude determination function for the estimation of the satellite state, during normal mode. The three modes of microsatellite adopted Kalman filter algorithm estimate microsatellite attitude. This paper will discuss using the SIL validation ADCS function and verify its feasibility.

The Research of Micro-Satellite Attitude Determination Based on Predictive Filter

— An extended predictive filter is presented for attitude determination of Micro-satellite based on the basic theory of predictive filter. This algorithm enhances the precision of kinematics equation, accurately estimates satellite attitude angle and angular velocity using measurement vectors from magnetometer and sun sensors by predicting model errors and angular velocity errors one step ahead. In addition, a new measurement model is derived about angular velocity, which improved the efficiency of the use of measurement vectors. Simulation results show both the high reliability and precision of this method.

Spherical Simplex Unscented Kalman Filter based on Modified Rodrigues Parameters for Attitude Determination of Micro Satellite

Spherical Simplex Unscented Kalman Filter based on Modified Rodrigues Parameters for Attitude Determination of Micro Satellite

LEO GPS attitude determination algorithm for a micro-satellite using boom-arm deployed antennas

This paper describes a low earth orbiter micro-satellite attitude determination algorithm using GPS phase and pseudorange data as the only observables. It is designed to run in real-time, at a rate of 10 Hz, on-board the spacecraft, using minimal chip and memory resources. The spacecraft design includes four GPS antennas deployed on boom arms to improve the antenna separations. The boom arms feature smart sensors, from which time-varying deformation data are used to calculate changes in the body-fixed system (BFS) co-ordinates of the attitude antennas. These data are used as input to the attitude algorithm to improve the accuracy of the output.