Stability is the key to maintain and control the drone, which is challenged by significant noise from drone motors during operation. The paper presents the Kalman filter and Complementary filter based on the quaternion to optimize drone stability. An exponential moving average (EMA) filter is used to minimize the significant vibration noise inside angular rates. The designed models optimize the misleading data from the Inertial Measurement Unit (IMU) sensor on the drone caused by noise. A real test bench was constructed to verify the proposed methods. An MPU 6050 (triaxial accelerometer and triaxial gyroscope) is equipped with a Racing Drone; then, the sensor data is logged in a MicroSD Card for signal analysis. The results demonstrate that the Complementary filter attenuates variation due to the noise, but it has an issue with drift. On the other hand, the Kalman filter accomplishes more stable output surrounding the drone's balanced point.

Noise Attenuation on IMU Measurement for Drone Balance by Sensor Fusion

Hoang M. L.;Carratù M.;Paciello V.;Pietrosanto A.
2021-01-01

Abstract

Stability is the key to maintain and control the drone, which is challenged by significant noise from drone motors during operation. The paper presents the Kalman filter and Complementary filter based on the quaternion to optimize drone stability. An exponential moving average (EMA) filter is used to minimize the significant vibration noise inside angular rates. The designed models optimize the misleading data from the Inertial Measurement Unit (IMU) sensor on the drone caused by noise. A real test bench was constructed to verify the proposed methods. An MPU 6050 (triaxial accelerometer and triaxial gyroscope) is equipped with a Racing Drone; then, the sensor data is logged in a MicroSD Card for signal analysis. The results demonstrate that the Complementary filter attenuates variation due to the noise, but it has an issue with drift. On the other hand, the Kalman filter accomplishes more stable output surrounding the drone's balanced point.
2021
978-1-7281-9539-1
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4769145
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 5
social impact