COMPARISON OF PAL2V FILTER AND KALMAN FILTER USED IN MPU6050 ACCELEROMETER GYROSCOPE SENSOR

Many signals exhibit noise as a component that cannot be ignored; thus, a serie of methods are used with the intention of reducing it. This study compares the Kalman Filter and the PAL2V Filter based on Annotated Paraconsistent Logic using data from the MPU6050 gyroscope accelerometer.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-18
DOI
https://doi.org/10.5281/zenodo.15459964
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
0.00
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article

COMPARISON OF PAL2V FILTER AND KALMAN FILTER USED IN MPU6050 ACCELEROMETER GYROSCOPE SENSOR

Zenodo (CERN European Organization for Nuclear Research)
Inertial Sensor and Navigation
article

COMPARISON OF PAL2V FILTER AND KALMAN FILTER USED IN MPU6050 ACCELEROMETER GYROSCOPE SENSOR

article en

Abstract

Many signals exhibit noise as a component that cannot be ignored; thus, a serie of methods are used with the intention of reducing it. This study compares the Kalman Filter and the PAL2V Filter based on Annotated Paraconsistent Logic using data from the MPU6050 gyroscope accelerometer.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 35%
Inertial Sensor and Navigation
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COMPARISON OF PAL2V FILTER AND KALMAN FILTER USED IN MPU6050 ACCELEROMETER GYROSCOPE SENSOR · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS