In this paper, an effective target locating approach based on the fingerprint fusion posi-tioning (FFP) method is proposed which integrates the time-difference of arrival (TDOA) and the received signal strength according to the statistical variance of target position in the stationary 3D scenarios. The FFP method fuses the pedestrian dead reckoning (PDR) estimation to solve the moving target localization problem. We also introduce auxiliary parameters to estimate the target motion state. Subsequently, we can locate the static pedestrians and track the the moving target. For the case study, eight access stationary points are placed on a bookshelf and hypermarket; one target node is moving inside hypermarkets in 2D and 3D scenarios or stationary on the bookshelf. We compare the performance of our proposed method with existing localization algorithms such as k-nearest neighbor, weighted k-nearest neighbor, pure TDOA and fingerprinting combining Bayesian frameworks including the extended Kalman filter, unscented Kalman filter and particle fil-ter (PF). The proposed approach outperforms obviously the counterpart methodologies in terms of the root mean square error and the cumulative distribution function of localization errors, espe-cially in the 3D scenarios. Simulation results corroborate the effectiveness of our proposed approach.

Haoyu Yang;Yuanshuo Wang;Dongchen Li;Tiancheng Li

Key Laboratory of Information Fusion Technology(Ministry of Education),School of Automation,Northwest-ern Polytechnical University,Xi'an 710072,China;CSSC Systems Engineering Research Institute,Beijing 100094,China

北京理工大学学报（英文版）

[1]Haoyu Yang;Yuanshuo Wang;Dongchen Li;Tiancheng Li-.An Indoor Localization Approach Based on Fingerprint and Time-Difference of Arrival Fusion)[J].北京理工大学学报（英文版）,2022(06):570-583

bookshelf,hypermarket,hypermarkets

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