Customizable Stochastic High Fidelity Model of the Sensors and Camera onboard a Low SWaP Fixed Wing Autonomous Aircraft

The navigation systems of autonomous aircraft rely on the readings provided by a suite of onboard sensors to estimate the aircraft state. In the case of fixed wing vehicles, the sensor suite is composed by triads of accelerometers, gyroscopes, and magnetometers, a Global Navigation Satellite System (GNSS) receiver, and an air data system (Pitot tube, air vanes, thermometer, and barometer), and is often complemented by one or more digital cameras. An accurate representation of the behavior and error sources of each of these sensors, together with the images generated by the cameras, in indispensable for flight simulation and the evaluation of novel inertial or visual navigation algorithms, and more so in the case of low SWaP (size, weight, and power) aircraft, in which the quality and price of the sensors is limited. This article presents realistic and customizable models for each of these sensors, which have been implemented as an open-source C ++ simulation. Provided with the true variation of the aircraft state with time, the simulation provides a time stamped series of the errors generated by all sensors, as well as realistic images of the Earth surface that resemble those taken from a real camera flying along the indicated state positions and attitudes.