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Beyond 200 Hz : An Evaluation of Low-Rate IMU Sampling for Pedestrian Inertial Odometry

Hrechko, Pavlo (2025) Beyond 200 Hz : An Evaluation of Low-Rate IMU Sampling for Pedestrian Inertial Odometry.

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Abstract:Mobile and wearable devices with limited energy resources increasingly rely on inertial measurement unit (IMUs) for pedestrian localisation. This is necessary in situations where the global navigation satellite system (GNSS) or Wi-Fi signals are not available. Although state-of-the-art neural inertial odometry models such as RoNIN achieve meter-level accuracy at high sampling rates such as 200 Hz [9], operating at these rates significantly drain battery life and computational resources. This paper investigates the minimum viable IMU sampling rate capable of maintaining acceptable pedestrian inertial odometry accuracy. To maintain comparable localisation accuracy at lower sampling rates, two compensation strategies are investigated: (i) temporal upsampling of low-rate IMU data, and (ii) training neural odometry models directly with downsampled data. Extensive experiments conducted using the RoNIN dataset and custom-collected iOS pedestrian IMU data show a rapid increase in drift as sampling rate decreases. Temporal upsampling, even with sophisticated Kalman–RTS smoothing, fails to recover lost high-frequency information, resulting in severe localisation errors (>170 m). Direct retraining of RoNIN at reduced frequencies (10–150 Hz) significantly outperformed naive interpolation methods, yet accuracy remained below the 200 Hz baseline. Findings indicate that 40 Hz represents a practical lower bound for applications tolerant of moderate drift (~10 m after several minutes), while rates below 30 Hz lead to unacceptable error (≥14 m after several minutes).
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Business & IT BSc (56066)
Link to this item:https://purl.utwente.nl/essays/107273
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