Having reliable information of the surrounding environment is crucial for any aerial vehicle. One way to improve the information quality is to combine data from several sensors. Two sensor fusion examples that are studied within the Aerial vehicles application area are the combination of radar and inertial measurement unit (IMU) signals in synthetic aperture radar and simultaneous localization and mapping using camera images and IMU data. Furthermore, tracking of multiple objects using unsynchronized data is another research topic that involves multiple sensors.
Having data from several sensors is also central when a model of an aerial vehicle is developed. Methods for monitoring the information content in data during flight tests are investigated as well as approaches to estimation of nonlinear models of aircraft operating in closed loop.
Having data from several sensors is also central when a model of an aerial vehicle is developed. Methods for monitoring the information content in data during flight tests are investigated as well as approaches to estimation of nonlinear models of aircraft operating in closed loop.
