Estimation of Altitude and Vertical Velocity for Multirotor Aerial Vehicle Using Kalman Filter

Abstract

Knowledge about precise robot localization is a key ingredient in controlling it, but the task is not trivial without any visual or GPS feedback. In this paper, authors concentrate on estimation of information about the robot’s altitude. One of the ways to acquire it, is a barometer. This type of sensor returns atmospheric pressure from which the height above the sea level can be computed. These readings have some disadvantages e.i.: vulnerability to pressure jumps and temperature drift as well as delay on the output. These problems can be solved by using Kalman filter algorithm for estimating altitude and vertical velocity, based not only on barometer readings, but also on accelerometer data. In the paper, derivation of the Kalman equations for the process to estimated are shown. Also improvements of the algorithm are described. The results of tests of this algorithm on real flying robot proved that estimates calculated with this method are precise and noise resistant.