scholarly journals Attitude determination for nano-satellites – II. Dead reckoning with a multiplicative extended Kalman filter

2021 ◽  
Author(s):  
János Takátsy ◽  
Tamás Bozóki ◽  
Gergely Dálya ◽  
Kornél Kapás ◽  
László Mészáros ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Gamma Ray ◽  
Attitude Determination ◽  
Initial Conditions ◽  
Low Earth Orbit ◽  
Detection Accuracy ◽  
The Sun ◽  
Projection Function ◽  
The Earth

AbstractThis paper is the second part of a series of studies discussing a novel attitude determination method for nano-satellites. Our approach is based on the utilization of thermal imaging sensors to determine the direction of the Sun and the nadir with respect to the satellite with sub-degree accuracy. The proposed method is planned to be applied during the Cubesats Applied for MEasuring and LOcalising Transients (CAMELOT) mission aimed at detecting and localizing gamma-ray bursts with an efficiency and accuracy comparable to large gamma-ray space observatories. In our previous work we determined the spherical projection function of the MLX90640 infrasensors planned to be used for this purpose. We showed that with the known projection function the direction of the Sun can be located with an overall accuracy of $$\sim 40^\prime$$ ∼ 40 ′ . In this paper we introduce a simulation model aimed at testing the applicability of our attitude determination approach. Its first part simulates the orbit and rotation of a satellite with arbitrary initial conditions while its second part applies our attitude determination algorithm which is based on a multiplicative extended Kalman filter. The simulated satellite is assumed to be equipped with a GPS system, MEMS gyroscopes and the infrasensors. These instruments provide the required data input for the Kalman filter. We demonstrate the applicability of our attitude determination algorithm by simulating the motion of a nano-satellite on Low Earth Orbit. Our results show that the attitude determination may have a 1$$\sigma$$ σ error of $$\sim 30'$$ ∼ 30 ′ even with a large gyroscope drift during the orbital periods when the infrasensors provide both the direction of the Sun and the Earth (the nadir). This accuracy is an improvement on the point source detection accuracy of the infrasensors. However, the attitude determination error can get as high as 25$$^{\circ }$$ ∘ during periods when the Sun is occulted by the Earth. We show that following an occultation period the attitude information is immediately recovered by the Kalman filter once the Sun is observed again.

scholarly journals Dynamics of Space Particles and Spacecrafts Passing by the Atmosphere of the Earth

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Vivian Martins Gomes ◽  
Antonio Fernando Bertachini de Almeida Prado ◽  
Justyna Golebiewska
Keyword(s):  
Initial Conditions ◽  
Equations Of Motion ◽  
Center Of Mass ◽  
The Sun ◽  
Three Body Problem ◽  
The Earth ◽  
Before And After ◽  
Three Body ◽  
Body Energy ◽  
Spacecraft Position

The present research studies the motion of a particle or a spacecraft that comes from an orbit around the Sun, which can be elliptic or hyperbolic, and that makes a passage close enough to the Earth such that it crosses its atmosphere. The idea is to measure the Sun-particle two-body energy before and after this passage in order to verify its variation as a function of the periapsis distance, angle of approach, and velocity at the periapsis of the particle. The full system is formed by the Sun, the Earth, and the particle or the spacecraft. The Sun and the Earth are in circular orbits around their center of mass and the motion is planar for all the bodies involved. The equations of motion consider the restricted circular planar three-body problem with the addition of the atmospheric drag. The initial conditions of the particle or spacecraft (position and velocity) are given at the periapsis of its trajectory around the Earth.

Influence analysis of measurement errors in satellite attitude determination based on extended Kalman filter

2012 ◽  
Vol 116 (1178) ◽  
pp. 373-389
Author(s):  
Y. Jiao ◽  
J. Wang ◽  
X. Pan ◽  
H. Zhou
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Measurement Errors ◽  
Attitude Determination ◽  
Previous Analysis ◽  
Measurement Model ◽  
Experimental Results ◽  
Influence Analysis ◽  
Satellite Attitude ◽  
Structural Error

Abstract The satellite attitude determination approach based on the Extended Kalman Filter (EKF) has been widely used in many real applications. However, the accuracy of this method largely depends on the fitness of measurement model. We aim to analyse the influence of measurement errors to the accuracy of EKF based attitude determination approach in this paper. The measurement errors, which are divided into structural error and nonstructural error by their influences, are analysed in principle. In the setting of the combination of star sensors and gyros, according to the property of innovation, we employ the technique of correlation test to analyse the influences of different kinds of measurement errors. Experimental results demonstrate the effectiveness of our previous analysis.

Influence of supernovae, gamma-ray bursts, solar flares, and cosmic rays on the terrestrial environment

2008 ◽  
Author(s):  
Arnon Dar
Keyword(s):  
Solar Activity ◽  
Cosmic Rays ◽  
Gamma Ray ◽  
Cosmic Ray ◽  
Gamma Ray Bursts ◽  
The Sun ◽  
Terrestrial Environment ◽  
The Earth ◽  
The Galaxy ◽  
Threat To Life

Changes in the solar neighbourhood due to the motion of the sun in the Galaxy, solar evolution, and Galactic stellar evolution influence the terrestrial environment and expose life on the Earth to cosmic hazards. Such cosmic hazards include impact of near-Earth objects (NEOs), global climatic changes due to variations in solar activity and exposure of the Earth to very large fluxes of radiations and cosmic rays from Galactic supernova (SN) explosions and gamma-ray bursts (GRBs). Such cosmic hazards are of low probability, but their influence on the terrestrial environment and their catastrophic consequences, as evident from geological records, justify their detailed study, and the development of rational strategies, which may minimize their threat to life and to the survival of the human race on this planet. In this chapter I shall concentrate on threats to life from increased levels of radiation and cosmic ray (CR) flux that reach the atmosphere as a result of (1) changes in solar luminosity, (2) changes in the solar environment owing to the motion of the sun around the Galactic centre and in particular, owing to its passage through the spiral arms of the Galaxy, (3) the oscillatory displacement of the solar system perpendicular to the Galactic plane, (4) solar activity, (5) Galactic SN explosions, (6) GRBs, and (7) cosmic ray bursts (CRBs). The credibility of various cosmic threats will be tested by examining whether such events could have caused some of the major mass extinctions that took place on planet Earth and were documented relatively well in the geological records of the past 500 million years (Myr). A credible claim of a global threat to life from a change in global irradiation must first demonstrate that the anticipated change is larger than the periodical changes in irradiation caused by the motions of the Earth, to which terrestrial life has adjusted itself. Most of the energy of the sun is radiated in the visible range. The atmosphere is highly transparent to this visible light but is very opaque to almost all other bands of the electromagnetic spectrum except radio waves, whose production by the sun is rather small.

scholarly journals Satellite Inertia Parameters Estimation Based on Extended Kalman Filter

2019 ◽  
Author(s):  
Abdellatif Bellar ◽  
Mohammed Arezki Si Mohammed
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Critical Role ◽  
Low Earth Orbit ◽  
Parameters Estimation ◽  
Moment Of Inertia ◽  
Satellite Mission ◽  
Inertia Matrix ◽  
Inertia Parameters ◽  
The Moment

The moment of inertia parameters play a critical role in assuring the spacecraft mission throughout its lifetime. However, determination of the moment of inertia is a key challenge in operating satellites. During satellite mission, those parameters can change in orbit for many reasons such as sloshing, fuel consumption, etc. Therefore, the inertia matrix should be estimated in orbit to enhance the attitude estimation and control accuracy. This paper investigates the use of gyroscope to estimate the attitude rate and inertia matrix for low earth orbit satellite via extended Kalman filter. Simulation results show the effectiveness and advantages of the proposed algorithm in estimating these parameters without knowing the nominal inertia. The robustness of the proposed algorithm has been validated using the Monte-Carlo method. The obtained results demonstrate that the accuracy of the estimated inertia and angular velocity parameters is satisfactory for satellite with coarse accuracy mission requirements. The proposed method can be used for different types of satellites.

On the Drag parameter of ICME propagation models

2020 ◽  
Author(s):  
Gianluca Napoletano ◽  
Raffaello Foldes ◽  
Dario Del Moro ◽  
Francesco Berrilli ◽  
Luca Giovannelli ◽  
...  
Keyword(s):  
Solar Wind ◽  
Travel Time ◽  
Initial Conditions ◽  
Solar Wind Speed ◽  
Distribution Functions ◽  
Model Parameters ◽  
Wind Condition ◽  
The Sun ◽  
The Earth ◽  
External Fluid

<p>ICME (Interplanetary Coronal Mass Ejection) are violent phenomena of solar activity that affect the whole heliosphere and the prediction of their impact on different solar system bodies is one of the primary goals of the planetary space weather forecasting. The travel time of an ICME from the Sun to the Earth can be computed through the Drag-Based Model (DBM), which is based on a simple equation of motion for the ICME defining its acceleration as a=-Γ(v-w)v-w, where a and v are the CME acceleration and speed, w is the ambient solar-wind speed and Γ is the so-called drag parameter (Vršnak et al., 2013).<br>In this framework, Γ depends on the ICME mass and cross-section, on the solar-wind density and, to a lesser degree, on other parameters. The typical working hypothesis for DBM implies that both Γ and w are constant far from the Sun. To run the codes, forecasters use empirical<br>input values for Γ and w, derived by pre-existent knowledge of solar-wind condition and by solving the “inverted problem” (where the ICME travel time is known and the unknowns are Γ and/or w). In<br>the 'Ensemble' approaches (Dumbovich et al., 2018; Napoletano et al. 2018), the uncertainty about the actual values of such inputs are rendered by Probability Distribution Functions (PDFs), accounting for the values variability and our lack of knowledge. Among those PDFs, that of Γ is poorly defined due to the relatively scarce statistics of recorded values. </p><p>Employing a list of past ICME events, for which initial conditions when leaving the Sun and arrival conditions at the Earth are known, we employ a statistical approach to the Drag-Based Model to determine a measure of Γ and w for each case. This allows to obtain distributions for the model parameters on experimental basis and, more importantly, to test whether different conditions of relative velocity to the solar wind influence the value of the drag efficiency, as it must be expected for solid objects moving into an external fluid. In addition, we perform numerical simulations of a solid ICME-shaped structure moving into the solar-wind modelled as an external fluid. Outcomes from these simulations are compared with our experimental results, and thus employed to interpret them on physical basis.</p>

Advanced Flow Control for Supersonic Blowdown Wind Tunnel Using Extended Kalman Filter

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Jiaqi Xi ◽  
Mian Li ◽  
Qiang Zhang ◽  
Zhaoguang Wang
Keyword(s):  
Kalman Filter ◽  
Flow Control ◽  
Extended Kalman Filter ◽  
Control Strategy ◽  
Test Section ◽  
Initial Conditions ◽  
Stagnation Pressure ◽  
Operating Conditions ◽  
Wind Tunnels ◽  
Wide Range

Supersonic blowdown wind tunnels provide controlled test environments for aerodynamic research on scaled models. During the experiments, the stagnation pressure in the test section is required to remain constant. Due to nonlinearity and distributed characteristics of the controlled system, a robust controller with effective flow control algorithms is required for this type of wind tunnels. In this paper, an extended Kalman filter (EKF) based flow control strategy is proposed and implemented. The control strategy is designed based on state estimation of the blowdown process under the EKF structure. One of the distinctive advantages of the proposed approach is its adaptability to a wide range of operating conditions for blowdown wind tunnels. Furthermore, it provides a systematic approach to tune the control parameters to ensure the stability of the controlled air flow. Experiments with different initial conditions and control targets have been conducted to test the applicability and performance of the designed controller. The results demonstrate that the controller and its strategies can effectively control the stagnation pressure in the test section and maintain the target pressure during the stable stage of the blowdown process.

scholarly journals Unscented Kalman Filter Applied to the Spacecraft Attitude Estimation with Euler Angles

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Roberta Veloso Garcia ◽  
Helio Koiti Kuga ◽  
Maria Cecilia F. P. S. Zanardi
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Attitude Determination ◽  
Unscented Kalman Filter ◽  
Artificial Satellite ◽  
Real Data ◽  
Nonlinear Functions ◽  
Estimation And Control ◽  
And Control

The aim of this work is to test an algorithm to estimate, in real time, the attitude of an artificial satellite using real data supplied by attitude sensors that are on board of the CBERS-2 satellite (China Brazil Earth Resources Satellite). The real-time estimator used in this work for attitude determination is the Unscented Kalman Filter. This filter is a new alternative to the extended Kalman filter usually applied to the estimation and control problems of attitude and orbit. This algorithm is capable of carrying out estimation of the states of nonlinear systems, without the necessity of linearization of the nonlinear functions present in the model. This estimation is possible due to a transformation that generates a set of vectors that, suffering a nonlinear transformation, preserves the same mean and covariance of the random variables before the transformation. The performance will be evaluated and analyzed through the comparison between the Unscented Kalman filter and the extended Kalman filter results, by using real onboard data.

Sign in / Sign up

Export Citation Format

Share Document