English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This study aims to develop a Kalman filter algorithm in order to reduce the accelerometer sensor noise as effectively as possible. The accelerometer sensor is one part of the Inertial Measurement Unit (IMU) used to find the displacement distance of an object. The method used is modeling the system to model the accelerometer system to form mathematical equations. Then the state space method is used to change the system modeling to the form of matrix operations so that the process of the data calculating to the Kalman Filter algorithm is not too difficult. It also uses the threshold algorithm to detect the sensor's condition at rest. The present study had good results, which of the four experiments obtained with an average accuracy of 93%. The threshold algorithm successfully reduces measurement errors when the sensor is at rest or static so that the measurement results more accurate. The developed algorithm can also detect the sensor to move forward or backward.

aviation electronics, information technology, telecommunications, electricals, and controls (avitec)/aviation electronics, information technology, telecommunications, electricals, and controls

Kalman Filter untuk Mengurangi Derau Sensor Accelerometer pada IMU Guna Estimasi Jarak