INVESTIGATION OF MADGWICK FILTER IN PROCESSING IMU SIGNALS

Abstract

This paper presents a study on the use of the Madgwick filter to normalize
signals from Inertial Measurement Units (IMUs). IMUs are widely used systems
for measuring and tracking the motion of objects, but the signals from IMU
sensors are often corrupted by bias and accumulated noise, which reduces the
measurement accuracy. The Madgwick filter is a complementary filter that
combines data from accelerometers, gyroscopes, and magnetometers to
estimate the orientation of the sensor. The purpose of this study is to evaluate
the effectiveness of the Madgwick filter in improving the measurement accuracy
of IMU signals. The results show that the Madgwick filter significantly reduces
noise and errors in IMU signals while improving the measurement accuracy. This
article provides a detailed description of the Madgwick filter and its
implementation, which can be applied to human motion analysis systems, robot
navigation, and unmanned aerial vehicle control.