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http://dx.doi.org/10.7471/ikeee.2022.26.2.169

Interference Elimination Method of Ultrasonic Sensors Using K-Nearest Neighbor Algorithm  

Im, Hyungchul (Soongsil University)
Lee, Seongsoo (Soongsil University)
Publication Information
Journal of IKEEE / v.26, no.2, 2022 , pp. 169-175 More about this Journal
Abstract
This paper introduces an interference elimination method using k-nearest neighbor (KNN) algorithm for precise distance estimation by reducing interference between ultrasonic sensors. Conventional methods compare current distance measurement result with previous distance measurement results. If the difference exceeds some thresholds, conventional methods recognize them as interference and exclude them, but they often suffer from imprecise distance prediction. KNN algorithm classifies input values measured by multiple ultrasonic sensors and predicts high accuracy outputs. Experiments of distance measurements are conducted where interference frequently occurs by multiple ultrasound sensors of same type, and the results show that KNN algorithm significantly reduce distance prediction errors. Also the results show that the prediction performance of KNN algorithm is superior to conventional voting methods.
Keywords
Ultrasonic Sensor; Interference; k-Nearest Neighbor; Machine Learning; Obstacle Avoidance;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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