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Simplex Back Propagation Estimation Method for Out-of-Sequence Attitude Sensor Measurements.

Shu Ting Goh¹, M S C Tissera¹, RongDe Darius Tan¹

¹Department of Electrical & Computer Engineering, National University of Singapore, Singapore 117583, Singapore.

Sensors (Basel, Switzerland)

|October 27, 2022

Summary

A new simplex-back-propagation Kalman filter (SBPKF) improves attitude estimation accuracy for small satellites by addressing asynchronous data issues. This method offers superior performance and reduced computational load compared to existing filters.

Keywords:

Kalman filter attitude estimation out-of-sequence measurement small satellite

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Area of Science:

Aerospace Engineering
Control Systems
Satellite Technology

Background:

Small satellite attitude determination and control systems (ADCS) processors face challenges with asynchronous data acquisition from sensors and actuators.
This data asynchronicity degrades the accuracy of traditional attitude estimation methods like the extended Kalman filter (EKF), which assume synchronous data.

Purpose of the Study:

To develop a novel Kalman filter algorithm that minimizes attitude estimation accuracy loss caused by asynchronous data in small satellites.
To ensure the proposed algorithm maintains reasonable computational complexity suitable for resource-constrained small satellite applications.

Main Methods:

Proposes the simplex-back-propagation Kalman filter (SBPKF), which integrates time delay, gyro instability, and navigation error into measurement and covariance estimation.
Compares SBPKF performance against extended Kalman filter (EKF), modified adaptive EKF (MAEKF), and moving-covariance Kalman filter (MC-KF) through simulations.

Main Results:

SBPKF demonstrates at least a 30% reduction in attitude estimation error compared to EKF and MC-KF.
SBPKF exhibits 17% lower computational complexity than MAEKF and 29% lower than MC-KF.

Conclusions:

The simplex-back-propagation Kalman filter (SBPKF) effectively mitigates accuracy degradation from asynchronous data in small satellite ADCS.
SBPKF offers a computationally efficient and accurate solution for attitude determination in small satellite applications.