A Practical Implementation of a Low-Cost 6-DOF IMU by Kalman Algorithm

Abstract

In this study, the implementation of a 6 Degree of Freedom (DOF) Inertial Measurement Unit (IMU) via the Kalman Filter is aimed. High accuracy IMU units have been in practical use since the first space navigation practices. Today, the need for IMU's have been widespread among every aspect of life. The IMU sensors are mostly solid-state devices and are manufactured with Micro Electromechanical System (MEMS) technologies. The sensor noise has to be eliminated. The most popular method is the Kalman Filtering. The aim of this study is to better explain the IMU concept and make a practical implementation of the Kalman Filtering which is somehow complicated. In this study, a low cost IMU MEMS sensor has been selected and Kalman Filtering has been applied for both one and multi-dimensional outputs. The steps are explicitly explained to help the reader better understand the process. The study may be easily tailored to other sensor systems where noise is a concern.

A novel framework of building operation algorithm for the block of technical diagnostics of aircraft’s automatic control system

“…The DMP™ handles intricate 6-axis MotionFusion algorithms, measuring angle and acceleration values in three orthogonal directions [24], [25]. Kalman filters are used to remove electrical noise and sensor artifacts from the resulting signal [26]. A microcontroller that blends control algorithms, position stabilization, and technical diagnostic algorithms serves as the core of the flight instrumentation system.…”