Using smart-phones and floor plans for indoor location tracking

Kun-Chan Lan,Wen-Yuah Shih

IEEE T. Human-Machine Systems(2014)

引用 83|浏览41
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摘要
We implement pedestrian dead reckoning (PDR) for indoor localization. With a waist-mounted PDR based system on a smart-phone, we estimate the user's step length that utilizes the height change of the waist based on the Pythagorean Theorem. We propose a zero velocity update (ZUPT) method to address sensor drift error: Simple harmonic motion and a low-pass filtering mechanism combined with the analysis of gait characteristics. This method does not require training to develop the step length model. Exploiting the geometric similarity between the user trajectory and the floor map, our map matching algorithm includes three different filters to calibrate the direction errors from the gyro using building floor plans. A sliding-window-based algorithm detects corners. The system achieved 98% accuracy in estimating user walking distance with a waist-mounted phone and 97% accuracy when the phone is in the user's pocket. ZUPT improves sensor drift error (the accuracy drops from 98% to 84% without ZUPT) using 8 Hz as the cut-off frequency to filter out sensor noise. Corner length impacted the corner detection algorithm. In our experiments, the overall location error is about 0.48 meter.
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关键词
floor plan,global positioning system,pedestrians,calibration,user walking distance estimation,circuit layout,waist-mounted pdr based system,pedestrian dead reckoning,harmonic motion,gyro,corner detection algorithm,zero velocity update (zupt),pedestrian dead reckoning (pdr),low-pass filters,pythagorean theorem,sensor drift error,smart-phone,zero velocity update method,sliding-window-based algorithm,zupt method,simple harmonic motion (shm),gait analysis,indoor location tracking,user step length estimation,smart phones,sensors,map matching algorithm,map matching,waist-mounted,low-pass filtering mechanism,trajectory,cutoff frequency,accuracy,acceleration,gyroscopes,low pass filters,noise
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