Sharif Digital Repository

The thermal energy received by each surface of an Earth-orbiting satellite strongly depends on its position and orientation. In this sense, simultaneous orbit and attitude estimation (SOAE) using the surface temperature data has been focused in the present study. The Earth infrared (IR) radiation and the Earth's top-of-atmosphere (TOA) albedo are two key sources of radiation affecting the satellite surface temperature rate. The Earth's radiation information has been monitored for the past two decades by the Clouds and the Earth's Radiant Energy System (CERES) project, producing a comprehensive set of Earth radiation budget (ERB) data for climate, weather and applied science research. The... 

Solar panel flexibility plays an important role in the attitude control of satellites. Therefore, traditionally the deformations of flexible solar panels are measured with a series of sensors along the panels itself. This paper presents a novel maiden attempt to simultaneously estimate the attitude and deformation of a flexible satellite using only 2 low-cost attitude sensors namely the sun sensor and magnetometer measurements. The flexible satellite is considered as a central rigid body with two attached flexible panels in order to derive the governing dynamic equations based on the Lagrange's equation. Both Extended Kalman filter (EKF) and Unscented Kalman Filter (UKF) are employed for the... 

A modified unscented Kalman filter is presented to estimate the quaternion parameters as well as the angular velocities of a rigid gyro-less satellite under faulty sensor conditions. The task is carried out using the Sun sensor and magnetometers as attitude sensors with bounded noise and unknown fault(s). Following the presentation of the satellite attitude dynamics and filtering formulations, a new fault detection and isolation algorithm is proposed. The latter is based on a modified unscented Kalman filter structure for improved fault detection, sensor isolation, and attitude control (AC). A Backtracking Search Algorithm (BSA) is also used to design and optimize the PID controller gains,... 

Localization-capable inertial motion capture algorithms rely on zero-velocity updates (ZUPT), usually as measurements in a Kalman filtering scheme, for position and attitude error control. As ZUPTs are only applicable during the static phases a link goes through, estimation errors grow during dynamic ones. This error growth may somewhat be mitigated by imposing biomechanical constraints in multi-sensor systems. Error reduction is also possible by optimization-based methods that incorporate the dynamic and static constraints governing the system behavior over a period of time (e.g. the dynamic network algorithm); when this period includes multiple static phases for a link, its estimation... 

We present an asymptotically convergent nonlinear attitude estimator using a rate gyro and GPS. Double-difference (DD) carrier phase measurements are provided by at least two GPS antennas. The unknown integer ambiguity factor related to GPS carrier phase measurement is estimated along with the attitude. An observability condition is derived to guarantee the convergence of the estimator when a single baseline vector is available with more than four satellites in view. A systematic procedure for tuning observer parameters is also presented. Finally, the experimental test from a light fixed-wing aircraft illustrates the performance of the proposed observer. © 1993-2012 IEEE  

Inspired by algorithms utilized in inertial navigation, an inertial motion capturing algorithm capable of position and heading estimation is introduced. The fusion algorithm is capable of real-time link geometry estimation, which allows for the imposition of biomechanical constraints without a priori knowledge regarding sensor placements. Furthermore, the algorithm estimates gyroscope and accelerometer bias, scaling, and non-orthogonality parameters in real-time. The stationary phases of the links, during which pseudo-measurements such as zero velocity or heading stabilization updates are applied, are detected using optically trained neural networks with buffered accelerometer and gyroscope... 

Geophysical information such as the Earth geomagnetic field and gravity gradient (GG) data can provide a basis for autonomous concurrent orbit and attitude estimation (COAE) of satellites in low earth orbits (LEO), as magnetometers and gravity gradiometer measurements are in general functions of time, position as well as the vehicle's orientation. While gradiometer has recently been investigated just for orbit estimation (OE), the current study is focused on COAE via only utility of the GG data. To this aim, observability conditions are analyzed, where the sensitivity of the proposed COAE approach with respect to various system and roto-translational elements is also examined. Considering... 

In this paper, a new nonlinear heuristic filter based on the hybridization of an extended Kalman filter and an ant colony estimator is proposed to estimate the states of a nonlinear system. In this filter, a group of virtual ants searches the state space stochastically and dynamically to find and track the best state estimation while the position of each ant is updated at the measurement time using the extended Kalman filter. The performance of the proposed filter is compared with well-known heuristic filters using a nonlinear benchmark problem. The statistical results show that this algorithm is able to provide promising and competitive results. Then, the new filter is tested on a nonlinear... 

In this paper, a new nonlinear heuristic filter based on the hybridization of an extended Kalman filter and an ant colony estimator is proposed to estimate the states of a nonlinear system. In this filter, a group of virtual ants searches the state space stochastically and dynamically to find and track the best state estimation while the position of each ant is updated at the measurement time using the extended Kalman filter. The performance of the proposed filter is compared with well-known heuristic filters using a nonlinear benchmark problem. The statistical results show that this algorithm is able to provide promising and competitive results. Then, the new filter is tested on a nonlinear... 

This paper is focused on the development and verification of a heat attitude model (HAM) for satellite attitude determination. Within this context, the Sun and the Earth are considered as the main external sources of radiation that could effect the satellite surface temperature changes. Assuming that the satellite orbital position (navigational data) is known, the proposed HAM provides the satellite surface temperature with acceptable accuracy and also relates the net heat flux (NHF) of three orthogonal satellite surfaces to its attitude via the inertial to satellite transformation matrix. The proposed HAM simulation results are verified through comparison with commercial thermal analysis... 

Gaussian approximation filters have increasingly been developed to enhance the accuracy of attitude estimation in space missions. The effective employment of these algorithms demands accurate knowledge of system dynamics and measurement models, as well as their noise characteristics, which are usually unavailable or unreliable. An innovation-based adaptive filtering approach has been adopted as a solution to this problem; however, it exhibits two major challenges, namely appropriate window size selection and guaranteed assurance of positive definiteness for the estimated noise covariance matrices. The current work presents two novel techniques based on relative entropy and confidence level... 

This paper proposes a globally and exponentially convergent predictive observer for attitude and position estimation based on landmark measurements and velocity (angular and linear) readings. It is assumed that landmark measurements are available with time-delay. The maximum value of the sensor delay under which the estimation error converges to zero is calculated. Synthesis of the observer is based on a representation of rigid-body kinematics and sensor delay, formulated via ordinary and partial differential equations (ODE-PDE). Observability condition specifies necessary and sufficient landmark configuration for convergence of attitude and position estimation error to zero. Finally, for... 

A combination of low-cost micro-electoro-mechanical sensors (MEMSs) and nonlinear attitude estimation algorithm techniques can provide an inexpensive and accurate system for navigation and attitude determination. The features of MEMSs are their light weight and small size; hence, the MEMSs have found significant attention in low-cost navigation and control systems [1]. A common disadvantage of these sensors is the significant errors that accompany the corresponding measurements. The accuracy obtained using MEMSs depends on a number of factors, such as scale factor, bias, and random noise corrections [2]. However, these low-cost sensors suffer from large noise and errors, making calibration... 

The presence of bias in measurement of rate gyros is a performance limiting factor for satellite attitude determination systems. Gyro bias is usually handled by Kalman filtering methods which are mostly based on linearization approaches and lack global convergence properties. On the other hand, the existing asymptotically convergent nonlinear observers take into account the gyro bias only when multiple vector measurements are available. We present an asymptotically convergent attitude estimator which uses only one vector measurement and a rate gyro whose output is contaminated with an unknown and constant bias. The effect of unknown bias is compensated by means of a parameter adaptation law.... 

This study investigates the effect of noisy measurements of the angular rate in a non-linear attitude estimator for satellites. The attitude estimator uses measurement of a single attitude sensor such as Sun, Earth-horizon, star tracker or magnetometer together with a rate gyro, and guarantees exponential convergence of the attitude estimation error to zero under a no-noise condition. In view of a realistic situation where the presence of noise in gyro measurement is not negligible, this study presents stochastic and deterministic upper bounds for the attitude estimation error resulting from noisy angular rate measurement. A realistic simulation is presented to illustrate the results