Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU
碩士 === 國立暨南國際大學 === 資訊工程學系 === 100 === In this paper, a pedestrian dead reckoning (PDR) method is proposed based on the particle filter framework with map information and measurements from a foot-mounted inertial measurement unit (IMU) and a global positioning system (GPS). The main challenging of c...
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ndltd-TW-100NCNU03920072015-10-13T21:12:08Z http://ndltd.ncl.edu.tw/handle/27504089002648591404 Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU 使用低成本慣性量測單元推算行人航位之偏差補償法 Yi-Lin Hsu 許翼麟 碩士 國立暨南國際大學 資訊工程學系 100 In this paper, a pedestrian dead reckoning (PDR) method is proposed based on the particle filter framework with map information and measurements from a foot-mounted inertial measurement unit (IMU) and a global positioning system (GPS). The main challenging of computing PDR with IMU signals is that the biases of IMU sensors will result in unbounded integration drift. Therefore, a new method that uses non-zero velocity data for zero-velocity update of the accelerometer biases is proposed. Also, a measurement equation for the rate-gyro biases using accelerometer measurements are derived. We also show that some heuristic drift canceling rules can be easily incorporated into the particle filter framework. Experimental results show that the proposed method can effectively reduce the accumulation error. Sheng-Wen Shih 石勝文 2012 學位論文 ; thesis 29 en_US |
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碩士 === 國立暨南國際大學 === 資訊工程學系 === 100 === In this paper, a pedestrian dead reckoning (PDR) method is proposed based on the particle filter framework with map information and measurements from a foot-mounted inertial measurement unit (IMU) and a global positioning system (GPS). The main challenging of computing PDR with IMU signals is that the biases of IMU sensors will result in unbounded integration drift. Therefore, a new method that uses non-zero velocity data for zero-velocity update of the accelerometer biases is proposed. Also, a measurement equation for the rate-gyro biases using accelerometer measurements are derived. We also show that some heuristic drift canceling rules can be easily incorporated into the particle filter framework. Experimental results show that the proposed method can effectively reduce the accumulation error.
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Sheng-Wen Shih |
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Sheng-Wen Shih Yi-Lin Hsu 許翼麟 |
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Yi-Lin Hsu 許翼麟 |
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Yi-Lin Hsu 許翼麟 Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU |
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Yi-Lin Hsu |
title |
Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU |
title_short |
Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU |
title_full |
Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU |
title_fullStr |
Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU |
title_full_unstemmed |
Bias Compensation Methods for Pedestrian Dead Reckoning with a Low-Cost IMU |
title_sort |
bias compensation methods for pedestrian dead reckoning with a low-cost imu |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/27504089002648591404 |
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