Basic Techniques for Filtering Noise Out of Accelerometer Data

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F15%3A43873634" target="_blank" >RIV/70883521:28140/15:43873634 - isvavai.cz</a>
Výsledek na webu
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Jazyk výsledku
angličtina
Název v původním jazyce
Basic Techniques for Filtering Noise Out of Accelerometer Data
Popis výsledku v původním jazyce
This research paper describes the evaluation of an indoor localization system based only on commercially available minimized low-cost micro-electro-mechanical (MEMS) inertial sensors. The low-cost inertial sensors are very predisposed to noise and error.In order to filter out the noise, there must be applied some filtration algorithms. So, the aim of this research paper is to compare different filtration techniques to filter the noise out of measured data. The techniques used in this experiment were simple moving average (SMA), exponential moving average (EMA) and simple Kalman filter (KF).
Název v anglickém jazyce
Basic Techniques for Filtering Noise Out of Accelerometer Data
Popis výsledku anglicky
This research paper describes the evaluation of an indoor localization system based only on commercially available minimized low-cost micro-electro-mechanical (MEMS) inertial sensors. The low-cost inertial sensors are very predisposed to noise and error.In order to filter out the noise, there must be applied some filtration algorithms. So, the aim of this research paper is to compare different filtration techniques to filter the noise out of measured data. The techniques used in this experiment were simple moving average (SMA), exponential moving average (EMA) and simple Kalman filter (KF).

Rok uplatnění
2015
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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