AN ATTITUDE DETERMINATION SYSTEM WITH MEMS GYROSCOPE DRIFT COMPENSATION FOR SMALL SATELLITES

This thesis presents the design of an attitude determination system for small satellites that automatically corrects for attitude drift. Existing attitude determination systems suffer from attitude drift due to the integration of noisy rate gyro sensors used to measure the change in attitude. This attitude drift leads to a gradual loss in attitude knowledge, as error between the estimated attitude and the actual attitude increases. In this thesis a Kalman filter is used to complete sensor fusion which combines sensor observations with a projected attitude based on the dynamics of the satellite. The system proposed in this thesis also utilizes a novel sensor called the stellar gyro to correct for the drift. The stellar gyro compares star field images taken at different times to determine orientation, and works in the presence of the sun and during eclipse. This device provides a relative attitude fix that can be used to update the attitude estimate provided by the Kalman filter, effectively compensating for drift. Simulink models are developed of the hardware and algorithms to model the effectiveness of the system. The Simulink models show that the attitude determination system is highly accurate, with steady state errors of less than 1 degree

Comparisons of filtering methods for attitude determination of microsatellites

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2018.Subsistemas de pequenos satélites estão em constante desenvolvimento. Com o objetivo de contribuir com essas inovações, o Laboratório de Aplicação e Inovação em Pesquisas Aeroespaciais (LAICA), localizado na Universidade de Brasília, desenvolveu uma plataforma de testes de nanossatélites. Essa plataforma pode ser dividida em quatro subsistemas principais: sistemas de balanceamento e atuação, gaiola de Helmholtz e o sistema de determinação de orientação. O sistema de determinação de orientação é responsável por determinar a orientação do corpo e afeta diretamente em muitas das estratégias de controle empregadas em nanossatélites. Com o objetivo de melhorar os dados de orientação, que normalmente são corrompidos com ruído, quatro técnicas de filtragem foram empregadas. Os filtros utilizados foram: o Filtro de Kalman Extendido (EKF), Filtro de Kalman Unscented (UKF), Estimador de Quatérnio Unscented (USQUE) e o Filtro de Kalman Unscented Aditivo Esférico Riemanniano (RiSAdUKF). Esses filtros foram avaliados com dados experimentais e os resultados foram utilizados para indicar qual o filtro mais apropriado para diferentes condições experimentais.Small satellite subsystems are in constant improvement. In order to address this issue, the Laboratory of Application and Innovation in Aerospace Science (LAICA), located at the University of Brasilia, developed a nanosatellite test platform. This platform can be divided in four main subsystems: actuation and balancing systems, Helmholtz cage and attitude determination system. The attitude determination system is responsible for determining the body orientation, and consequently it has a direct impact on most of control strategies designed for nanosatellites. In order to improve orientation data, which are normally embedded with noise, four filtering strategies were employed. The utilized filters were: the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Unscented Quaternion Estimator (USQUE) and Riemannian-Spheric Additive Unscented Kalman Filter (RiSAdUKF). These filters were evaluated with experimental data and the results were used to indicate the appropriated filter and attitude representation for different real situations

Satellite Formation-Flying and Rendezvous

GNSS has come to play an increasingly important role in satellite formation-flying and rendezvous applications. In the last decades, the use of GNSS measurements has provided the primary technique for determining the relative position of cooperative co-orbiting satellites in low Earth orbit

BioSentinel: Monitoring DNA Damage Repair Beyond Low Earth Orbit on a 6U Nanosatellite

We are designing and developing a 6U nanosatellite as a secondary payload to fly aboard NASAs Space Launch System (SLS) Exploration Mission (EM) 1, scheduled for launch in late 2017. For the first time in over forty years, direct experimental data from biological studies beyond low Earth orbit (LEO) will be obtained during BioSentinels 12- to 18-month mission. BioSentinel will measure the damage and repair of DNA in a biological organism and allow us to compare that to information from onboard physical radiation sensors. This data will be available for validation of existing models and for extrapolation to humans.The BioSentinel experiment will use the organism Saccharomyces cerevisiae (yeast) to report DNA double-strand-break (DSB) events that result from space radiation. DSB repair exhibits striking conservation of repair proteins from yeast to humans. The flight strain will include engineered genetic defects that prevent growth and division until a radiation-induced DSB activates the yeasts DNA repair mechanisms. The triggered culture growth and metabolic activity directly indicate a DSB and its repair. The yeast will be carried in the dry state in independent microwells with support electronics. The measurement subsystem will sequentially activate and monitor wells, optically tracking cell growth and metabolism. BioSentinel will also include TimePix radiation sensors implemented by JSCs RadWorks group. Dose and Linear Energy Transfer (LET) data will be compared directly to the rate of DSB-and-repair events measured by the S. cerevisiae biosentinels. BioSentinel will mature nanosatellite technologies to include: deep space communications and navigation, autonomous attitude control and momentum management, and micropropulsion systems to provide an adaptable nanosatellite platform for deep space uses

The AlfaCrux CubeSat mission description and early results

On 1 April 2022, the AlfaCrux CubeSat was launched by the Falcon 9 Transporter-4 mission, the fourth SpaceX dedicated smallsat rideshare program mission, from Space Launch Complex 40 at Cape Canaveral Space Force Station in Florida into a Sun-synchronous orbit at 500 km. AlfaCrux is an amateur radio and educational mission to provide learning and scientific benefits in the context of small satellite missions. It is an opportunity for theoretical and practical learning about the technical management, systems design, communication, orbital mechanics, development, integration, and operation of small satellites. The AlfaCrux payload, a software-defined radio hardware, is responsible for two main services, which are a digital packet repeater and a store-and-forward system. In the ground segment, a cloud-computing-based command and control station has been developed, together with an open access online platform to access and visualize the main information of the AlfaCrux telemetry and user data and experiments. It also becomes an in-orbit database reference to be used for different studies concerned with, for instance, radio propagation, attitude reconstruction, data-driven calibration algorithms for satellite sensors, among others. In this context, this paper describes the AlfaCrux mission, its main subsystems, and the achievements obtained in the early orbit phase. Scientific and engineering assessments conducted with the spacecraft operations to tackle unexpected behaviors in the ground station and also to better understand the space environment are also presented and discussed.Fundação de Apoio à Pesquisa del Distrito Federal (FAPDF), Brasil | Ref. N/

Multi-Sensor Fusion for Underwater Vehicle Localization by Augmentation of RBF Neural Network and Error-State Kalman Filter

The Kalman filter variants extended Kalman filter (EKF) and error-state Kalman filter (ESKF) are widely used in underwater multi-sensor fusion applications for localization and navigation. Since these filters are designed by employing first-order Taylor series approximation in the error covariance matrix, they result in a decrease in estimation accuracy under high nonlinearity. In order to address this problem, we proposed a novel multi-sensor fusion algorithm for underwater vehicle localization that improves state estimation by augmentation of the radial basis function (RBF) neural network with ESKF. In the proposed algorithm, the RBF neural network is utilized to compensate the lack of ESKF performance by improving the innovation error term. The weights and centers of the RBF neural network are designed by minimizing the estimation mean square error (MSE) using the steepest descent optimization approach. To test the performance, the proposed RBF-augmented ESKF multi-sensor fusion was compared with the conventional ESKF under three different realistic scenarios using Monte Carlo simulations. We found that our proposed method provides better navigation and localization results despite high nonlinearity, modeling uncertainty, and external disturbances.This research was partially funded by the Campus de Excelencia Internacional Andalucia Tech, University of Malaga, Malaga, Spain. Partial funding for open access charge: Universidad de Málag

ESTCube-2 attitude and orbit control subsystem sensor and actuator calibration and evaluation

https://www.ester.ee/record=b5381537*es

Radio Aurora Explorer: A Mission Overview

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140647/1/1.a32436.pd

Augmented stellar sensor for a small spacecraft

Thesis (MEng)--Stellenbosch University, 2019.ENGLISH ABSTRACT: With the maturity of the CubeSat industry and advancements in commercial off-the-shelf components, CubeSat-based projects have become an attractive option for advanced outer space missions. This increase in mission complexity has given rise to the necessity of a new generation of accurate attitude determination subsystems. The purpose of this work, therefore, entailed the design and development of an augmented stellar sensor. The focus was not only on the development of a suitable high-performance, lowpower hardware platform, but also on the identification, implementation, and development of suitable software techniques as well as the simulation, integration and testing of the augmented platform. This developed sensor delivers accurate attitude and rate estimates, whilst conforming to the small satellite power and size requirements. The augmented system uses inertial rate sensor data, with error compensation performed by use of matched vector measurements obtained from a star sensor. Measurements are combined in an Extended Kalman filter, providing both high rate attitude propagation and bias drift compensation. The designed system features a robust tracking mode as well as a stellar gyro algorithm to deliver accurate, low-frequency rate estimates independent of host dynamics. To prove overall system functionality, the sensor has undergone verification during simulated conditions, testing in an in-house developed star emulation environment, as well as testing under night sky conditions. During these tests, it was exposed to conditions typically experienced by satellites throughout their mission lifetimes. These conditions range from low-rate tumbling, to fine pointing. Initial testing shows that the system offers a robust response regardless of satellite rate and orientation whilst simultaneously adhering to CubeSat standards. IMU bias compensation worked successfully, and estimated results show that the average 3σ stellar gyro rate accuracies were in the order of 0.01 °/s whilst the cross-axis 3σ orientation accuracy was close to 0.01° during low rates.AFRIKAANSE OPSOMMING: Met die volwassewording van die CubeSat-industrie en vooruitgang van kommersieël beskikbare elektroniese komponente, het die CubeSat-platform ’n aantreklike keuse geword vir ruimtevaartsendings. Hierdie belangstelling in die CubeSat-platform het tot ’n vermeerdering van sendingskompleksiteit gelei wat die behoefte vir ’n nuwe generasie akkurate oriëntasiebeheer-substelsels geskep het. Gevolglik was die doel van hierdie werk die ontwerp en ontwikkeling van ’n uitgebreide stersensor. Die fokus was egter nie net om ’n gepaste hardewarestelsel te ontwerp nie, maar ook om geskikte sagtewaretegnieke en algoritmes te identifiseer, te ontwikkel, en toe te pas. Die ontwikkelde stelsel lewer akkurate oriëntasie- en hoeksnelheidafskattings, terwyl dit geskik vir gebruik in ’n nanosatelliet is. Hierdie uitgebreide stelsel gebruik inersiële sensormetings waarop foutkorrigering, soos afgeskat deur middel van vektorinligting vanaf ’n sterkamera, toegepas is. Die sensormetings word gekombineer in ’n uitgebreide Kalman filter, wat beide hoë-frekwensie oriëntasie-afskattings kan verskaf, sowel as om die inersiële sensor foutkorrigering te beheer. Die ontwerpte stelsel bevat verder ’n robuuste stervolgmodus om die mikroverwerker se berekeninge te verminder, sowel as ’n hoeksnelheid-afskattingsalgoritme om baie akkurate lae-frekwensie afskattings te bied. Die laasgenoemde algoritme kan onafhanklik van ’n dinamiese model funksioneer. Om die oorhoofse stelsel se werking te bevestig, is die sensor tydens gesimuleerde, geëmuleerde, en praktiese omstandighede getoets. Gedurende hierdie toetse is die stelsel blootgestel aan tipiese gebruikstoestande soos lae-snelheid tuimel en fyn oriëntasiebeheer. Aanvanklike toetse wys dat die stelsel goed werk ongeag die hoeksnelheidstoestande waaraan dit blootgestel word. Inersiële sensor hoeksnelheidsmetings kon suksesvol gekorrigeer word. Afgeskatte resultate toon daarop dat ’n stervektor se hoeksnelheid oor die kruisas akkuraat tot 0.01 °/s, op die 3σ-vlak, afgeskat kon word. Resultate aangaande oriëntasie-akkuraatheid was in die orde van 0.01°, 3σ, oor die kruisas tydens ’n lae hoeksnelheid

Satellite Attitude Determination with Low-Cost Sensors.

This dissertation contributes design and data processing techniques to maximize the accuracy of low-cost attitude determination systems while removing pre-flight calibration requirements. This enables rapid development of small spacecraft to perform increasingly complex missions. The focus of this work is magnetometers and sun sensors, which are the two most common types of attitude sensors. Magnetometer measurements are degraded by the magnetic fields of nearby electronics, which traditionally limit their utility on satellites unless a boom is used to provide physical separation between the magnetometer and the satellite. This dissertation presents an on-orbit, attitude-independent method for magnetometer calibration that mitigates the effect of nearby electronics. With this method, magnetometers can be placed anywhere within the spacecraft, and as demonstrated through application to flight data, the accuracy of the integrated magnetometer is reduced to nearly that of the stand-alone magnetometer. Photodiodes are light sensors that can be used for sun sensing. An individual photodiode provides a measurement of a single sun vector component, and since orthogonal photodiodes do not provide sufficient coverage due to photodiode field-of-view limitations, there is a tradeoff between photodiode orientation and sun sensing angular accuracy. This dissertation presents a design method to optimize the photodiode configuration for sun sensing, which is also generally applicable to directional sensors. Additionally, an on-orbit calibration method is developed to estimate the photodiode scale factors and orientation, which are critical for accurate sun sensing. Combined, these methods allow a magnetometer to be placed anywhere within a spacecraft and provide an optimal design technique for photodiode placement. On-orbit calibration methods are formulated for both types of sensors that correct the sensor errors on-orbit without requiring pre-flight calibration. The calibration methods are demonstrated by application to on-orbit data, and attitude determination accuracies of 0.5 degrees 1-sigma are achieved with commercial-off-the-shelf magnetometers, photodiodes, and a MEMS rate gyroscope, which to the author's knowledge, is the best accuracy reported in the literature for this class of sensors.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102312/1/jspringm_1.pd