Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 174618, 20 pages
Research Article

Detection of Sensor Faults in Small Helicopter UAVs Using Observer/Kalman Filter Identification

1Robotics, Vision and Control Group, University of Seville, Camino de los Descubrimientos s/n, 41092 Seville, Spain
2Center for Advanced Aerospace Technologies (CATEC), Aeropolis, Seville, Spain

Received 1 April 2011; Accepted 14 July 2011

Academic Editor: Horst Ecker

Copyright © 2011 Guillermo Heredia and Anibal Ollero. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Reliability is a critical issue in navigation of unmanned aerial vehicles (UAVs) since there is no human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be installed in small UAVs. Therefore, other approaches like analytical redundancy should be used to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters based on analytical redundancy. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the Observer/Kalman Filter Identification (OKID) method. The OKID method is able to identify the system and an observer with properties similar to a Kalman filter, directly from input-output experimental data. Results are similar to the Kalman filter, but, with the proposed method, there is no need to estimate neither system matrices nor sensor and process noise covariance matrices. The system has been tested with real helicopter flight data, and the results compared with other methods.