Distance Estimation on Ultrasonic Sensor Using Kalman Filter

This research discusses about the distance estimation on ultrasonic sensor using Kalman Filter method. Accuracy level problem on ultrasonic sensor will be increased using Kalman Filter. Kalman Filter consists of two parts which are prediction and update. This research applies Kalman Filter method using Arduino Uno and Ultrasonic sensor HC-SR04. The test result compares the sensor data before and after Kalman Filter is applied. The test result of sensor value after given Kalman Filter depends on the value of noise sensor covariance matrix (R) and process noise covariance (Q). The best value of R and Q is 100 and 0.01. If the distance value between R and Q is too small, the filtering result will be invisible. In contrast, if the distance value between R and Q is too far, the filtering result could remove the original measured sensor data. In conclusion, applying Kalman Filter method in Ultrasonic sensor could estimate and increase the accuracy of sensor value up to 7%.