Fault-Tolerant Spacecraft Attitude Determination using State Estimation Techniques

TL;DR

This paper evaluates the performance of advanced state estimation filters like Kalman and particle filters for fault-tolerant spacecraft attitude determination, focusing on fault detection, isolation, and recovery in low earth orbit conditions.

Contribution

It compares the effectiveness of different filters and fault management techniques for improving spacecraft attitude estimation robustness.

Findings

Kalman and particle filters effectively detect and isolate faults.

Filter performance varies with fault types and modes.

Proposed techniques enhance fault recovery capabilities.

Abstract

The extended and unscented Kalman filter, and the particle filter provide a robust framework for fault-tolerant attitude estimation on spacecraft. This paper explores how each filter performs for a large satellite in a low earth orbit. Additionally, various techniques, built on these filters, for fault detection, isolation and recovery from erroneous sensor measurements, are analyzed. Key results from this analysis include filter performance for various fault modes.