An Accurate Device for Real-Time Altitude Estimation Using Data Fusion Algorithms

This paper presents an accurate system to estimate the altitude of a rigid body by fusing data from four low-cost sensors such as an accelerometer, a gyroscope, a magnetometer and an altimeter. Usually a MEMS altimeter barometric sensor allows to obtain the altitude signal from measures of atmospheric pressure and temperature but these measures are affected by noise that causes a significant error in the calculated altitude values. In order to get an accurate estimation of the altitude, in this work a complementary filter is used to fuse the raw signal of the altitude obtained from barometer sensor and vertical displacement signal calculated through a data fusion algorithm applied to the signals of the other three sensors. In order to evaluate the performance in human activity monitoring applications, the proposed device has been tested and compared with the system that currently presents the better performance for the same technology according to its experimental protocols. The results show that our device exceeds the performance provided by the currently systems reported in literature.