Journals / Havacılık ve Uzay Teknolojileri Dergisi / 2022 / Cilt: 15 - Sayı: 2

Fault Tolerant Attitude Estimation for a Nanosatellite Using Adaptive Kalman Filter with Single Scaling Factor

Tek Ölçekleme Faktörlü Uyarlanabilir Kalman Filtresi Kullanarak Bir Nanouydu için Hata Toleranslı Yönelim Tahmini

Pages
74–93
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

At the same time, the adaptive EKF readjusts the measurement noise covariance matrix by using a single scaling factor (SSF) in case of a sensor fault and makes the overall system more robust against the sensor malfunctions.

📌 3 Key Takeaways

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Objective & Hypothesis:In this study, an integrated adaptive TRIAD/Extended Kalman Filter (EKF) attitude estimation system is presented, in which the TRIAD and an adaptive EKF are combined to estimate the attitude of a nanosatellite.
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Key Findings & Data:As the first step of the system, the TRIAD algorithm produces an initial coarse quaternion estimation by using magnetometer and sun sensor measurements, and then, this coarse estimation is directly fed to the adaptive EKF.
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Conclusion & Impact:At the same time, the adaptive EKF readjusts the measurement noise covariance matrix by using a single scaling factor (SSF) in case of a sensor fault and makes the overall system more robust against the sensor malfunctions.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, an integrated adaptive TRIAD/Extended Kalman Filter (EKF) attitude estimation system is presented, in which the TRIAD and an adaptive EKF are combined to estimate the attitude of a nanosatellite. As the first step of the system, the TRIAD algorithm produces an initial coarse quaternion estimation by using magnetometer and sun sensor measurements, and then, this coarse estimation is directly fed to the adaptive EKF. This direct input of the attitude information to the filter relatively reduces the computational burden that an EKF brings. As the second step of the system, adaptive EKF filters the TRIAD solution and gives the final quaternion estimation. At the same time, the adaptive EKF readjusts the measurement noise covariance matrix by using a single scaling factor (SSF) in case of a sensor fault and makes the overall system more robust against the sensor malfunctions. Several simulations are performed, and the performance of the presented system is tested against two different fault types as noise increment and continuous bias in attitude sensors.

Özet

Bu çalışmada, bir nanouydunun yönelimini tahmin etmek için TRIAD ve uyarlamalı bir genişletilmiş Kalman süzgeci (GKS) algoritmasının birleştirildiği entegre bir uyarlamalı TRIAD/GKS yönelim tahmin algoritması sunulmaktadır. TRIAD tarafından manyetometre ve güneş sensörü ölçümleri kullanılarak üretilen kuaterniyon seti, uyarlanabilir GKS'ye girdi olarak sağlanır. Böylece GKS’nin sisteme getirmiş olduğu hesaplama yükü nispeten azaltılmış olur. Daha sonra uyarlanabilir GKS, TRIAD çözümündeki gürültüyü azaltarak nihai kuaterniyon setini verir. Uyarlanabilir GKS aynı zamanda tek ölçekleme faktörü (TÖF) kullanarak, yönelim sensörlerinde oluşabilecek bir hata durumunda ölçüm gürültüsü kovaryans matrisini yeniden ayarlayarak süzgeci arızalara karşı daha dirençli hale getirir. Önerilen entegre sistemin performansı, yönelim sensörlerinde devamlı bayas olması ya da sensör gürültülerinin aniden artması durumlarına karşı çeşitli benzetimlerle test edilmiştir.

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Cite This Article

HACIZADE, C., KINATAŞ, H. (2022). Fault Tolerant Attitude Estimation for a Nanosatellite Using Adaptive Kalman Filter with Single Scaling Factor. Havacılık ve Uzay Teknolojileri Dergisi, Cilt: 15 - Sayı: 2, 74–93. https://ajindex.com/articles/533577

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