Kalman Filter Algorithm Design for HC-SR04 Ultrasonic Sensor Data Acquisition System

https://doi.org/10.22146/ijitee.36646

Adnan Rafi Al Tahtawi(1*)

(1) Politeknik Sukabumi
(*) Corresponding Author

Abstract


In the control system application, the existence of noise measurement may impact on the performance degradation. The noise measurement of the sensor is produced due to several reasons, such as the low specification, external signal disturbances, and the complexity of measured state. Therefore, it should be avoided to achieve the good control performance. One of the solutions is by designing a signal filter. In this paper, the design of Kalman Filter (KF) algorithm for ultrasonic range sensor is presented. KF algorithm is designed to overcome the existence of noise measurement on the sensor. The type of ultrasonic range sensor used is HC-SR04 which is capable to detect the distance from 2 cm to 400 cm. The discrete KF algorithm is implemented using ATMega 328p microcontroller on Arduino Uno board. The algorithm is then tested with different three covariance values of process noise. The test result shows that the KF algorithm is able to reduce the measurement noise of the ultrasonic sensor. The analysis of variance conducted shows that the smaller value of covariance matrix of the process and measured noises, the better filtering process performed. However, this results in a longer generated response time. Thus, an optimization is required to obtain the best filtering performance.

Keywords


distance sensor, signal, Kalman Filter, optimization, HC-SR04

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References

R.E. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Journal of Basic Engineering, Vol. 82, No. 1, pp. 35-45, 1960.

A. Alawiah and A.R. Al Tahtawi, “Sistem Kendali dan Pemantauan Ketinggian Air pada Tangki Berbasis Sensor Ultrasonik,” KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer, Vol. 01, No. 01, pp. 25-30, 2017.

F. Suryatini, J. Kustija, and E. Haritman, “Robot Cerdas Pemadam Api Menggunakan Ping Ultrasonic Range Finder dan Uvtron Flame Detector Berbasis Mikrokontroler ATmega128,” Electrans, Vol. 12, No. 1, pp. 29-38, 2013.

N.C. Basjaruddin, Kuspriyanto, Suhendar, D. Saefudin, and V.A. Azis, “Hardware Simulation of Automotive Braking System Based on Fuzzy Logic Control,” Journal Of Mechatronics, Electrical Power, and Vehicular Technology, Vol. 7, No. 1, pp. 1-6, 2016.

O. Bischoff, X. Wang, N. Heidmann, R. Laur, and S. Paul, “Implementation of an Ultrasonic Distance Measuring System with Kalman Filtering in Wireless Sensor Networks for Transport Logistics,” Proc. Eurosensors XXIV, 2010, pp. 196-199.

A.A.M. de Araujo, R.L. de Lima, P.C. de Mello, M.L. Carneiro, and E.A. Tannuri,, “Kalman Filter Applied to Ultrasonic Based Level Sensoring,” ABCM Symposium Series in Mechatronics, 2012, Vol. 5, pp. 1257- 1267.

Z. Wang, “Motion Measurement Using Inertial Sensors, Ultrasonic Sensors, and Magnetometers with Extended Kalman Filter,” IEEE Sensors Journal, Vol. 12, No. 5, pp. 943-953, 2012.

G. Welch, and G. Bishop, “An Introduction to the Kalman Filter,” UNC-Chapel Hill, TR 95-041, 2006.



DOI: https://doi.org/10.22146/ijitee.36646

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