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Special Issue "Attitude Estimation Based on Data Processing of Sensors"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 20 January 2022.

Special Issue Editor

Prof. Dr. Daniele Mortari
E-Mail Website
Guest Editor
Department of Aerospace Engineering, Texas A&M University - 3141 TAMU, College Station, TX, USA
Interests: attitude and position estimation; sensor data processing; algorithms; satellite constellations design; linear algebra
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Space navigation highly depends on the fast and accurate estimation of spacecraft attitude which, in turn, completely depends on the data processing of attitude sensors, a critical task for any space vehicle. The performance of all space systems (communication, observation, interferometry, navigation, etc.) strongly depends on how fast, reliable, and optimal the estimation of attitude information is, and that estimation always follows the task of attitude sensor’s data-processing.

Novel ideas about attitude sensors, new methods to increase the measurement accuracy of the sun, stars or horizon attitude sensors, new algorithms to increase the robustness of star-identification, extraction of meaningful information from degraded sensors, or from those with poor knowledge of sensor parameters, more accurate or faster star centroid algorithms, or new methods of post-flight recalibration new methods. These is an incomplete list of subjects this Special Issue is particularly interested in.

Contributions to the theory of attitude estimation (single-point or filtered) are also of great interest. This involves, for instance, new, more accurate, and/or faster filtering techniques, state and parameter estimation, estimation using dual quaternions and multiplicative approaches. New filtering to estimate attitude and attitude rate provides another exampled of a subject this Special Issue is particularly interested in.

Finally, surveys with comparisons on different data-processing techniques as well as on attitude estimation methods providing rational summary of competing approaches are also of great interest.

Prof. Dr. Daniele Mortari
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • attitude sensors
  • attitude estimation algorithms
  • measurement filtering
  • recalibration
  • uncertainty quantification and propagation

Published Papers (6 papers)

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Research

Article
An Efficient and Robust Star Identification Algorithm Based on Neural Networks
Sensors 2021, 21(22), 7686; https://doi.org/10.3390/s21227686 - 19 Nov 2021
Viewed by 213
Abstract
A lost-in-space star identification algorithm based on a one-dimensional Convolutional Neural Network (1D CNN) is proposed. The lost-in-space star identification aims to identify stars observed with corresponding catalog stars when there is no prior attitude information. With the help of neural networks, the [...] Read more.
A lost-in-space star identification algorithm based on a one-dimensional Convolutional Neural Network (1D CNN) is proposed. The lost-in-space star identification aims to identify stars observed with corresponding catalog stars when there is no prior attitude information. With the help of neural networks, the robustness and the speed of the star identification are improved greatly. In this paper, a modified log-Polar mapping is used to constructed rotation-invariant star patterns. Then a 1D CNN is utilized to classify the star patterns associated with guide stars. In the 1D CNN model, a global average pooling layer is used to replace fully-connected layers to reduce the number of parameters and the risk of overfitting. Experiments show that the proposed algorithm is highly robust to position noise, magnitude noise, and false stars. The identification accuracy is 98.1% with 5 pixels position noise, 97.4% with 5 false stars, and 97.7% with 0.5 Mv magnitude noise, respectively, which is significantly higher than the identification rate of the pyramid, optimized grid and modified log-polar algorithms. Moreover, the proposed algorithm guarantees a reliable star identification under dynamic conditions. The identification accuracy is 82.1% with angular velocity of 10 degrees per second. Furthermore, its identification time is as short as 32.7 miliseconds and the memory required is about 1920 kilobytes. The algorithm proposed is suitable for current embedded systems. Full article
(This article belongs to the Special Issue Attitude Estimation Based on Data Processing of Sensors)
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Article
In-Orbit Attitude Determination of the UVSQ-SAT CubeSat Using TRIAD and MEKF Methods
Sensors 2021, 21(21), 7361; https://doi.org/10.3390/s21217361 - 05 Nov 2021
Viewed by 373
Abstract
Ultraviolet and infrared sensors at high quantum efficiency on-board a small satellite (UVSQ-SAT) is a CubeSat dedicated to the observation of the Earth and the Sun. This satellite has been in orbit since January 2021. It measures the Earth’s outgoing shortwave and longwave [...] Read more.
Ultraviolet and infrared sensors at high quantum efficiency on-board a small satellite (UVSQ-SAT) is a CubeSat dedicated to the observation of the Earth and the Sun. This satellite has been in orbit since January 2021. It measures the Earth’s outgoing shortwave and longwave radiations. The satellite does not have an active pointing system. To improve the accuracy of the Earth’s radiative measurements and to resolve spatio-temporal fluctuations as much as possible, it is necessary to have a good knowledge of the attitude of the UVSQ-SAT CubeSat. The attitude determination of small satellites remains a challenge, and UVSQ-SAT represents a real and unique example to date for testing and validating different methods to improve the in-orbit attitude determination of a CubeSat. This paper presents the flight results of the UVSQ-SAT’s attitude determination. The Tri-Axial Attitude Determination (TRIAD) method was used, which represents one of the simplest solutions to the spacecraft attitude determination problem. Another method based on the Multiplicative Extended Kalman Filter (MEKF) was used to improve the results obtained with the TRIAD method. In sunlight, the CubeSat attitude is determined at an accuracy better than 3° (at one σ) for both methods. During eclipses, the accuracy of the TRIAD method is 14°, while it reaches 10° (at one σ) for the recursive MEKF method. Many future satellites could benefit from these studies in order to validate methods and configurations before launch. Full article
(This article belongs to the Special Issue Attitude Estimation Based on Data Processing of Sensors)
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Article
Evaluation of Murrell’s EKF-Based Attitude Estimation Algorithm for Exploiting Multiple Attitude Sensor Configurations
Sensors 2021, 21(19), 6450; https://doi.org/10.3390/s21196450 - 27 Sep 2021
Viewed by 488
Abstract
Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell’s implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non [...] Read more.
Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell’s implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non redundant attitude sensors. The paper describes such an implementation involving a sun sensor suite and a magnetometer as attitude sensors. The implementation exploits Murrell’s EKF to enable three sensor configurations, which can be operationally commanded, for satellite attitude estimation. Among the three attitude estimation schemes, (i) sun sensor suite and magnetometer, (ii) magnetic field vector and its time derivative and (iii) magnetic field vector, it is shown that the third configuration is better suited for attitude estimation in terms of precision and accuracy, but can consume more time to converge than the other two. Full article
(This article belongs to the Special Issue Attitude Estimation Based on Data Processing of Sensors)
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Article
High Accurate Mathematical Tools to Estimate the Gravity Direction Using Two Non-Orthogonal Inclinometers
Sensors 2021, 21(17), 5727; https://doi.org/10.3390/s21175727 - 25 Aug 2021
Viewed by 390
Abstract
This study provides two mathematical tools to best estimate the gravity direction when using a pair of non-orthogonal inclinometers whose measurements are affected by zero-mean Gaussian errors. These tools consist of: (1) the analytical derivation of the gravity direction expectation and its covariance [...] Read more.
This study provides two mathematical tools to best estimate the gravity direction when using a pair of non-orthogonal inclinometers whose measurements are affected by zero-mean Gaussian errors. These tools consist of: (1) the analytical derivation of the gravity direction expectation and its covariance matrix, and (2) a continuous description of the geoid model correction as a linear combination of a set of orthogonal surfaces. The accuracy of the statistical quantities is validated by extensive Monte Carlo tests and the application in an Extended Kalman Filter (EKF) has been included. The continuous geoid description is needed as the geoid represents the true gravity direction. These tools can be implemented in any problem requiring high-precision estimates of the local gravity direction. Full article
(This article belongs to the Special Issue Attitude Estimation Based on Data Processing of Sensors)
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Article
Design, Ground Testing and On-Orbit Performance of a Sun Sensor Based on COTS Photodiodes for the UPMSat-2 Satellite
Sensors 2021, 21(14), 4905; https://doi.org/10.3390/s21144905 - 19 Jul 2021
Viewed by 553
Abstract
This paper presents the development of the UPMSat-2 sun sensor, from the design to on-orbit operation. It also includes the testing of the instrument, one of the most important tasks that needs to be performed to operate a sensor with precision. The UPMSat-2 [...] Read more.
This paper presents the development of the UPMSat-2 sun sensor, from the design to on-orbit operation. It also includes the testing of the instrument, one of the most important tasks that needs to be performed to operate a sensor with precision. The UPMSat-2 solar sensor has been designed, tested, and manufactured at the Universidad Politécnica de Madrid (UPM) using 3D printing and COTS (photodiodes). The work described in this paper was carried out by students and teachers of the Master in Space Systems (Máster Universitario en Sistemas Espaciales—MUSE). The solar sensor is composed of six photodiodes that are divided into two sets; each set is held and oriented on the satellite by its corresponding support printed in Delrin. The paper describes the choice of components, the electrical diagram, and the manufacture of the supports. The methodology followed to obtain the response curve of each photodiode is simple and inexpensive, as it requires a limited number of instruments and tools. The selected irradiance source was a set of red LEDs and halogen instead of an AM0 spectrum irradiance simulator. Some early results from the UPMSat-2 mission have been analyzed in the present paper. Data from magnetometers and the attitude control system have been used to validate the data obtained from the sun sensor. The results indicate a good performance of the sensors during flight, in accordance with the data from the ground tests. Full article
(This article belongs to the Special Issue Attitude Estimation Based on Data Processing of Sensors)
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Article
Characterization of Degenerate Configurations in Attitude Determination of Three-Vehicle Heterogeneous Formations
Sensors 2021, 21(14), 4631; https://doi.org/10.3390/s21144631 - 06 Jul 2021
Viewed by 448
Abstract
The existence of multiple solutions to an attitude determination problem impacts the design of estimation schemes, potentially increasing the errors by a significant value. It is therefore essential to identify such cases in any attitude problem. In this paper, the cases where multiple [...] Read more.
The existence of multiple solutions to an attitude determination problem impacts the design of estimation schemes, potentially increasing the errors by a significant value. It is therefore essential to identify such cases in any attitude problem. In this paper, the cases where multiple attitudes satisfy all constraints of a three-vehicle heterogeneous formation are identified. In the formation considered herein, the vehicles measure inertial references and relative line-of-sight vectors. Nonetheless, the line of sight between two elements of the formation is restricted, and these elements are denoted as deputies. The attitude determination problem is characterized relative to the number of solutions associated with each configuration of the formation. There are degenerate and ambiguous configurations that result in infinite or exactly two solutions, respectively. Otherwise, the problem has a unique solution. The degenerate configurations require some collinearity between independent measurements, whereas the ambiguous configurations result from symmetries in the formation measurements. The conditions which define all such configurations are determined in this work. Furthermore, the ambiguous subset of configurations is geometrically interpreted resorting to the planes defined by specific measurements. This subset is also shown to be a zero-measure subset of all possible configurations. Finally, a maneuver is simulated to illustrate and validate the conclusions. As a result of this analysis, it is concluded that, in general, the problem has one attitude solution. Nonetheless, there are configurations with two or infinite solutions, which are identified in this work. Full article
(This article belongs to the Special Issue Attitude Estimation Based on Data Processing of Sensors)
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