Real-time inverse estimation of multi-directional random waves from vessel-motion sensors using Kalman filter

Kim, HanSung; Park, JeongYong; Jin, Chungkuk; Kim, Moo‐Hyun; Lee, Dongyoung

doi:10.1016/j.oceaneng.2023.114501

Cited by 1 publication

(1 citation statement)

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“…The state estimate is a vector that represents the best guess of the current state of the system, based on all available information up to the current time. The covariance matrix is a measure of the uncertainty or error in the state estimate [5].…”

Section: Fig 9 Axes Projection Demonstrationmentioning

confidence: 99%

Motion Capture With Mems Sensors

Dashkov

Liashenko

2023

A.I.S.

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The object of this article is the registration and analysis of human movements based on sensors. This paper presents a comparison of the basic methods of data processing from inertial micromechanical sensors to collect data a device was implemented that captures movements. As result the device uses the motion data from accelerometer and gyroscope to calculate the motion trajectory: the angle of rotation and acceleration. The data is read by the microcontroller, after which it is filtered and processed by one of the filters (Complementary, Kalman), and finally transferred to a computer for further analysis and display. The purpose of the article is to compare several methods of data processing from microelectromechanical. The results obtained: device was developed, obtained data that can be used to characterize the methods and analyze their work in the system. Conclusions: In the course of the study, a device was developed for collecting and processing data from MEMS sensors, which showed the effectiveness of the complementary filter in comparison with the Kalman filter in real-time systems with limited computing power. Real results confirmed that the results of the complementary method using less computational resources are not far behind the more costly Kalman filter without the use of auxiliary sensors, like a digital compass.

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Section: Fig 9 Axes Projection Demonstrationmentioning

confidence: 99%