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Indoor Pedestrian Trajectory Reconstruction Using Spatial–Temporal Error Correction and Dynamic Time Warping-Based Path Matching for Fingerprints Map Creation

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Abstract

The fingerprinting-based positioning has great potential for indoor location estimation where GPS signals are mostly blocked. However, fingerprinting-based methods need a calibration step for establishing a fingerprint map. The site survey process should be performed to record fingerprints which is a labor-intensive task essentially in large buildings. In this paper, we address the pedestrian trajectory reconstruction problem for fingerprint map creation. Where the goal is to predict and refine users’ trajectories obtained from smartphone sensor measurements. Our proposed spatial–temporal matching mechanism consists of three stages. First, the initial trajectory is calculated using the PDR algorithm. Then, landmarks error is eliminated using the proposed forward/backward error correction (FEC/BEC) algorithm. Afterward, the proposed dynamic time warping-based path-matching (DTW-PM) method applies to handle map-related errors. The evaluation results show positioning accuracy improves up to 53.69%. Finally, a traditional KNN algorithm is performed to evaluate the positioning efficiency over generated radio map, which validates the quality of the obtained radio map.

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Correspondence to Hamid Jazayeriy.

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Alitaleshi, A., Jazayeriy, H. & Kazemitabar, J. Indoor Pedestrian Trajectory Reconstruction Using Spatial–Temporal Error Correction and Dynamic Time Warping-Based Path Matching for Fingerprints Map Creation. Arab J Sci Eng 48, 2101–2119 (2023). https://doi.org/10.1007/s13369-022-07095-8

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