A time-varying Kalman filter for low-acceleration attitude estimation

This work shows an attitude estimator (AE) based on a time-varying Kalman filter (TVKF) and adapted to those cases where a low-acceleration assumption can be applied. This filter is an extended version of a previously published time-varying Kalman filter attitude estimator (TVKAE). A comparative analysis of the accuracies of those two estimators is provided. The efficiencies of both filters are also compared with those of other published AEs. The results show that the new AE achieves the best overall performance, followed by the original one.

Automated summary

This study presents a new attitude estimator based on a time-varying Kalman filter adapted for cases with low-acceleration assumption. Comparative analysis is conducted to compare the accuracies of this new estimator with the original one, as well as their efficiency with other published attitude estimators. The results demonstrate that the new AE achieves the best overall performance, followed by the original one.