A main problem in autonomous vehicles in general, and in UAV in particular, is the determination of the attitude angles. A novel method to estimate these angles using off-the-shelf components is presented. This paper introduces an AHRS based on the UKF using the TRIAD algorithm as the observation model. The performance of the method is assessed through simulations and compared to an AHRS based on the EKF . The paper presents field experiment results using a real fixed-wing UAV . The results show good real-time performance with low computational cost in a microcontroller.
Two computationally efficient algorithms are presented for determining three-axis attitude from two or more vector observations. The first of these, the TRIAD algorithm, provides a deterministic (i.e., nonoptimal) solution for the attitude based on two vector observations. The second, the QUEST algorithm, is an optimal algorithm which determines the attitude that achieves the best weighted overlap of an arbitrary number of reference and observation vectors. Analytical expressions are given for the covariance matrices for the two algorithms using a fairly realistic model for the measurement errors. The mathematical relationship of the two algorithms and their relative merits are discussed and numerical examples are given. The advantage of computing the covariance matrix in the body frame rather than in the inertial frame (e.g., in terms of Euler angles) is emphasized. These results are valuable when a single-frame attitude must be computed frequently. They will also be useful to the mission analyst or spacecraft engineer for the evaluation of launch-window constraints or of attitude accuracies for different attitude sensor configurations. Significant developments and technical trends in the area of navigation systems are reviewed. In particular, the integration of the Global Positioning System (GPS) and Inertial Navigation System (INS) has been an important development in modern navigation. The review concentrates also on the analysis, investigation, assessment and performance evaluation of existing integrated navigation systems of accuracy, performance, low cost and all the issues that aid in optimizing their operating efficiency. The integration of GPS and INS has been successfully used in practice during the past decades. However, much of the work has focused on the use of a high accuracy Inertial Measurement Unit (IMU), which is an inertial sensors block without navigation solution output, and hence, this research area is also reviewed in this paper.