Noise Reduction in the Accelerometer and Gyroscope Sensor with the Kalman Filter Algorithm

Rio Ikhsan Alfian (Universitas Ahmad Dahlan)
Alfian Ma'arif ((SCOPUS ID: 57195619646), Universitas Ahmad Dahlan)
Sunardi Sunardi (Universitas Ahmad Dahlan)

Journal of Robotics and Control (JRC)
Vol 2, No 3 (2021): May

Noise is unwanted signals in a communication or information system. Kalman filter has a good ability to handle noise. This study uses the Kalman filter algorithm that works to reduce noise at the accelerometer and gyroscope sensor output. Data were taken using the accelerometer sensor and the gyroscope sensor in a stationary condition. The device is Arduino Uno for processing the data and MPU6050 for accelerometer and gyroscope sensor. In the Kalman filter algorithm, there is process variance matrix and measurement variance matrix parameters that affect noise attenuation or reduction at the accelerometer and gyroscope output. If the difference between the two parameters is too large, then the attenuation becomes very large and eliminates the original value of the sensor output. Thus, the value cannot be chosen carelessly. The best value is the measurement variance matrix must bigger than the process variance matrix.