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

Rio Ikhsan Alfian, Alfian Ma'arif, Sunardi Sunardi

Abstract


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.

Keywords


Noise Reducer; Noise Reduction; Kalman Filter; Accelerometer Sensor; Gyroscope Sensor.

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References


M. Riyadi et al., “Pendeteksi Posisi Menggunakan Sensor Accelerometer MMA7260Q,” Semarang, Tek. Elektro Univ. Diponegoro, vol. 12, no. 2, pp. 76–81, 2010, doi: 10.1093/geront/gns022.

S. A. Quadri and O. Sidek, “Error and Noise Analysis in an IMU using Kalman Filter,” Int. J. Hybrid Inf. Technol., vol. 7, no. 3, pp. 39–48, 2014, doi: 10.14257/ijhit.2014.7.3.06.

A. Sugih, M. Huda, T. A. Zuraiyah, and F. L. Hakim, “Prototype Alat Pengukur Jarak Dan Sudut Kemiringan Digital Menggunakan Sensor Ultrasonik Dan Accelerometer Berbasis Arduino Nano,” vol. 6, no. 2, pp. 185–194, 2019.

W. Widada, “Metode Adaptif Frekuensi-Cutoff Untuk Complementary Filter Pada Accelerometer Dan Gyroscope Untuk Sudut Pitch Dan Roll Wahana Terbang.,” J. Teknol. Dirgant., vol. 13, pp. 15–24, 2015.

W. A. Kusuma, Z. Sari, A. T. Sari, and U. M. Malang, “Sensor Fusion Accelerometer dan Gyroscope untuk Pengukuran Perubahan Kinematik Pergelangan Kaki,” vol. 1, no. 1, pp. 17–22, 2016.

M. Narasimhappa, J. Nayak, M. H. Terra, and S. L. Sabat, “ARMA model based adaptive unscented fading Kalman filter for reducing drift of fiber optic gyroscope,” Sensors Actuators, A Phys., vol. 251, pp. 42–51, 2016, doi: 10.1016/j.sna.2016.09.036.

M. Safitri and N. H. Wijaya, “SISTEM PENAPISAN DERAU PADA SENSOR INERSIA WAHANA TANPA AWAK QUADROTOR,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 7, no. 2, p. 753, Nov. 2016, doi: 10.24176/simet.v7i2.791.

M. Safitri, A. Cahyadi, E. Firmansyah, and J. Grafika, “Estimasi Posisi UAV dengan Kalman Filter,” no. September, pp. 240–245, 2015.

L. Xue, C. Y. Jiang, H. L. Chang, Y. Yang, W. Qin, and W. Z. Yuan, “A novel Kalman filter for combining outputs of MEMS gyroscope array,” Meas. J. Int. Meas. Confed., vol. 45, no. 4, pp. 745–754, 2012, doi: 10.1016/j.measurement.2011.12.016.

N. TARYANA, D. NATALIANA, and A. R. ANANDA, “Pendeteksi Sikap pada Model Wahana Terbang menggunakan Inertial Measurement Unit,” ELKOMIKA J. Tek. Energi Elektr. Tek. Telekomun. Tek. Elektron., vol. 3, no. 1, p. 16, 2015, doi: 10.26760/elkomika.v3i1.16.

M. Fikri, B. Prasetio, and R. Maulana, “Perancangan Dan Implementasi Real Segway Pada Skateboard Roda Satu Menggunakan Gyroscope Dan Accelerometer,” J. Pengemb. Teknol. Inf. dan Ilmu Komput. Univ. Brawijaya, vol. 1, no. 1, pp. 1–9, 2017.

A. S. Samosir and N. S. Widodo, “Gyroscope and Accelerometer Sensor on the Lanange Jagad Dance Robot Balance System Sensor Gyroscope dan Accelerometer pada Sistem Keseimbangan Robot Seni Tari Lanange Jagad,” Bul. Ilm. Sarj. Tek. Elektro, vol. 2, no. 2, pp. 51–58, 2020, doi: 10.12928/biste.v2i2.922.

L. Lasmadi, “Attitude Estimation for Quadrotor Based on IMU with Kalman-Filter,” Conf. Senat. STT Adisutjipto Yogyakarta, vol. 4, no. 0, pp. 351–358, Nov. 2018, doi: 10.28989/senatik.v4i0.267.

E. Nurraharjo and Z. Budiarso, “Implementasi Gyroscope-Arduino Pada Kendali Keseimbangan,” Dinamik, vol. 23, no. 1, pp. 11–14, 2019, doi: 10.35315/dinamik.v23i1.7173.

A. Maarif, R. D. Puriyanto, and F. R. T. Hasan, “Robot Keseimbangan dengan Kendali PID dan Kalman Filter,” IT J. Res. Dev., vol. 4, no. 2, Feb. 2020, doi: 10.25299/itjrd.2020.vol4(2).3900.

“Implementasi Algoritma 2 Step Kalman Filter Untuk Mengurangi Noise Pada Estimasi Data Accelerometer,” STIKOM Tunas Bangsa Pematangsiantar, vol. Vol 3, No, 2019.

A. Ma’arif, I. Iswanto, A. A. Nuryono, and R. I. Alfian, “Kalman Filter for Noise Reducer on Sensor Readings,” Signal Image Process. Lett., vol. 1, no. 2, pp. 11–22, Jul. 2019, doi: 10.31763/SIMPLE.V1I2.2.

D. Wang, Y. Bao, and J. Shi, “Online lithium-ion battery internal resistance measurement application in state-of-charge estimation using the extended kalman filter,” Energies, vol. 10, no. 9, 2017, doi: 10.3390/en10091284.

G. Fathoni, S. A. Widayat, P. A. Topan, A. Jalil, A. I. Cahyadi, and O. Wahyunggoro, “Comparison of State-of-Charge (SOC) estimation performance based on three popular methods: Coulomb counting, open circuit voltage, and Kalman filter,” in Proceedings of the 2nd International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology, ICACOMIT 2017, Jul. 2017, vol. 2018-January, pp. 70–74, doi: 10.1109/ICACOMIT.2017.8253389.

P. A. Topan, M. N. Ramadan, G. Fathoni, A. I. Cahyadi, and O. Wahyunggoro, “State of Charge (SOC) and State of Health (SOH) estimation on lithium polymer battery via Kalman filter,” in Proceedings - 2016 2nd International Conference on Science and Technology-Computer, ICST 2016, Mar. 2017, pp. 93–96, doi: 10.1109/ICSTC.2016.7877354.

V. Firmansyah, “Aplikasi kalman filter pada pembacaan sensor suhu untuk pemantauan kondisi ruangan laboratorium vera firmansyah†,” J. Mater. dan Energi Indones., vol. 08, no. 01, pp. 1–7, 2018, doi: https://doi.org/10.24198/jmei.v8i01.16624.

A. R. Al Tahtawi, “Kalman Filter Algorithm Design for HC-SR04 Ultrasonic Sensor Data Acquisition System,” IJITEE (International J. Inf. Technol. Electr. Eng., vol. 2, no. 1, pp. 2–6, 2018, doi: 10.22146/ijitee.36646.

K. H. Eom, S. J. Lee, Y. S. Kyung, C. W. Lee, M. C. Kim, and K. K. Jung, “Improved kalman filter method for measurement noise reduction in multi sensor RFID systems,” Sensors, vol. 11, no. 11, pp. 10266–10282, 2011, doi: 10.3390/s111110266.

H. Z. Fahmi, R. Maulana, and W. Kurniawan, “Implementasi Complementary Filter Menggunakan Sensor Accelerometer dan Gyroscope pada Keseimbangan Gerak Robot Humanoid,” vol. 1, no. 11, pp. 1376–1384, 2017.

R. I. Putra, S. Sunardi, and R. D. Puriyanto, “Monitoring Tegangan Baterai Lithium Polymer pada Robot Line Follower Secara Nirkabel,” Bul. Ilm. Sarj. Tek. Elektro, vol. 1, no. 2, p. 73, 2019, doi: 10.12928/biste.v1i2.907.

M. I. Febryansah, A. Yudhana, and A. Ma’arif, “Urinoir Analyzer Pintar Pendeteksi Kelainan Pada Fungsi Ginjal Dengan Analisis Kadar Ph Dan Warna Pada Urin,” Mob. Forensics, vol. 2, no. 1, pp. 36–44, May 2020, doi: 10.12928/MF.V2I1.2032.

K. Kunal, A. Z. Arfianto, J. E. Poetro, F. Waseel, and R. A. Atmoko, “Accelerometer Implementation as Feedback on 5 Degree of Freedom Arm Robot,” J. Robot. Control, vol. 1, no. 1, pp. 31–34, 2020, doi: 10.18196/jrc.1107.

A. A. Rafiq, W. N. Rohman, and S. D. Riyanto, “Development of a Simple and Low-cost Smartphone Gimbal with MPU-6050 Sensor,” J. Robot. Control, vol. 1, no. 4, pp. 136–140, 2020, doi: 10.18196/jrc.1428.

M. Kamaludin and W. S. Aji, “Manuver Robot Manual Menggunakan PID pada Robot Manual KRAI 2018,” Bul. Ilm. Sarj. Tek. Elektro, vol. 1, no. 3, p. 91, 2019, doi: 10.12928/biste.v1i3.978.

Lasmadi, A. Cahyadi, S. Herdjunanto, and R. Hidayat, “Inertial navigation for quadrotor using kalman filter with drift compensation,” Int. J. Electr. Comput. Eng., vol. 7, no. 5, pp. 2596–2604, Oct. 2017, doi: 10.11591/ijece.v7i5.pp2596-2604.




DOI: https://doi.org/10.18196/jrc.2375

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