Sensor Fusion with Enhanced Kalman Filter for Altitude Control of Quadrotors

The Unmanned Aerial Vehicles like quadrocopters, thanks to the increasing computational capacity of embedded systems, are being used at wide range of tasks i.e. aerial mapping, scouting etc. To control the position of these UAV's, a proper altitude measurement is necessary, however due to the noisiness of these flying systems the design of such controls is a difficult task. The aim of this paper is to expand the capabilities of the sensors of our quadcopter project. Process and fusion their signals to compose a cost efficient, stable and accurate height measurement solution designed for an embedded low-cost microcontroller. The Kalman Filter was chosen to fusion the signals of the sonar and the accelerometer. The realized filter on the embedded platform was field tested in real conditions and modified after the analysis process of the results.