English

A Distributed Quaternion Kalman Filter With Applications to Fly-by-Wire Systems

Systems and Control 2016-07-22 v2 Applications Machine Learning

Abstract

The introduction of automated flight control and management systems have made possible aircraft designs that sacrifice arodynamic stability in order to incorporate stealth technology intro their shape, operate more efficiently, and are highly maneuverable. Therefore, modern flight management systems are reliant on multiple redundant sensors to monitor and control the rotations of the aircraft. To this end, a novel distributed quaternion Kalman filtering algorithm is developed for tracking the rotation and orientation of an aircraft in the three-dimensional space. The algorithm is developed to distribute computation among the sensors in a manner that forces them to consent to a unique solution while being robust to sensor and link failure, a desirable characteristic for flight management systems. In addition, the underlying quaternion-valued state space model allows to avoid problems associated with gimbal lock. The performance of the developed algorithm is verified through simulations.

Keywords

Cite

@article{arxiv.1605.05588,
  title  = {A Distributed Quaternion Kalman Filter With Applications to Fly-by-Wire Systems},
  author = {Sayed Pouria Talebi},
  journal= {arXiv preprint arXiv:1605.05588},
  year   = {2016}
}

Comments

It had to be noted that the assumption was made that all sensors have access to all observations and state estimate vectors. In addition, the summations in the DAQKF Algorithm are on all sensors, not just the neighbouring sensors

R2 v1 2026-06-22T14:03:47.041Z