5 uppsatser
Simulations of simulink models using Kalman filters are often very time-consuming. This problem depends mainly on the fact that the Kalman correction has to be performed at each sample instance through the whole simulation. The goal for this thesis work is to reduce that …
… nonlinear Simulink-models are simulated, it is often interesting to apply a Kalman filter to handle the noise that may occur within the process as well as corrupting the measurement. However, application of such a filter leads to an extensive time-consumption despite using fast …
… quality signals. A few trials were made to improve the velocity estimate thru Kalman filtering (Rauch-Tung-Striebel smoothing). The filtering was first made using only the position data from GrafNav as measurements and afterwards both position and velocity data from GrafNav was …
… with sensor fusion have been developed; one is a decentralized method with Kalman filtering using an error model and the other is a centralized particle filter using an all-embracing model of the vehicle. The two methods have been evaluated and compared. Test results show that …
… been developed in Simulink/Matlab. The implementation has been made using a Kalman filter where the sensor fusion takes place. Simulations for different scenarios have been made and the results from these simulations show that the drift in the vehicle’s attitude is avoided.
