Pedestrian motion analysis and application in personal location
碩士 === 國立臺灣科技大學 === 機械工程系 === 96 === For the location determination of persons in indoor environments, a variety of systems have been developed in recent years. These systems utilized accelerometers , gyroscopes and barometer in order to determine distance , heading and height. The performance of th...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2008
|
Online Access: | http://ndltd.ncl.edu.tw/handle/21781986400387384757 |
id |
ndltd-TW-096NTUS5489055 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-096NTUS54890552016-05-13T04:15:15Z http://ndltd.ncl.edu.tw/handle/21781986400387384757 Pedestrian motion analysis and application in personal location 感測器於個人定位之步行分析與應用 Jian-liang Liu 劉建良 碩士 國立臺灣科技大學 機械工程系 96 For the location determination of persons in indoor environments, a variety of systems have been developed in recent years. These systems utilized accelerometers , gyroscopes and barometer in order to determine distance , heading and height. The performance of the pedestrian navigation system (PNS) depends on not only the accuracy of the sensors but also the measurement processing methods. This thesis proposed some effective methods to correct measurement data from accelerometer and gyroscope. Characteristics of human walking motions are analyzed by using the raw sensor data, and several signal processing methods for different sensors based on human motion characteristics are proposed to correct the errors resulting from sensor drift and biases. The 2D and 3D walking test is preformed using the implemented system consists of a 3-axes accelerometer, an 1-axis gyroscope, a barometer and a microprocessor. The results of walking test confirmed the proposed processing methods. Wei-Wen Kao 高維文 2008 學位論文 ; thesis 73 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立臺灣科技大學 === 機械工程系 === 96 === For the location determination of persons in indoor environments, a variety of systems have been developed in recent years. These systems utilized accelerometers , gyroscopes and barometer in order to determine distance , heading and height. The performance of the pedestrian navigation system (PNS) depends on not only the accuracy of the sensors but also the measurement processing methods. This thesis proposed some effective methods to correct measurement data from accelerometer and gyroscope. Characteristics of human walking motions are analyzed by using the raw sensor data, and several signal processing methods for different sensors based on human motion characteristics are proposed to correct the errors resulting from sensor drift and biases.
The 2D and 3D walking test is preformed using the implemented system consists of a 3-axes accelerometer, an 1-axis gyroscope, a barometer and a microprocessor. The results of walking test confirmed the proposed processing methods.
|
author2 |
Wei-Wen Kao |
author_facet |
Wei-Wen Kao Jian-liang Liu 劉建良 |
author |
Jian-liang Liu 劉建良 |
spellingShingle |
Jian-liang Liu 劉建良 Pedestrian motion analysis and application in personal location |
author_sort |
Jian-liang Liu |
title |
Pedestrian motion analysis and application in personal location |
title_short |
Pedestrian motion analysis and application in personal location |
title_full |
Pedestrian motion analysis and application in personal location |
title_fullStr |
Pedestrian motion analysis and application in personal location |
title_full_unstemmed |
Pedestrian motion analysis and application in personal location |
title_sort |
pedestrian motion analysis and application in personal location |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/21781986400387384757 |
work_keys_str_mv |
AT jianliangliu pedestrianmotionanalysisandapplicationinpersonallocation AT liújiànliáng pedestrianmotionanalysisandapplicationinpersonallocation AT jianliangliu gǎncèqìyúgèréndìngwèizhībùxíngfēnxīyǔyīngyòng AT liújiànliáng gǎncèqìyúgèréndìngwèizhībùxíngfēnxīyǔyīngyòng |
_version_ |
1718267736485789696 |