Abstract
Applications on location-based services (LBSs) have driven the increasingly demand for indoor localization technology. Motivated by the widely deployed wireless local area network (WLAN) infrastructure and the corresponding easily accessible WLAN received signal strength (RSS) data, the Wi-Fi signal-based localization has become one of the superior positioning techniques in GPS-denied scenes. Meanwhile, the error bound estimation for the Wi-Fi localization has been attracting much attention due to its significant guidance meaning in practice. In this survey, the error bound estimation approaches for different categories of Wi-Fi localization approaches are overviewed and compared, including the error bound estimation with temporal and spatial signal features, and that with the RSS characteristics. Regarding the temporal and spatial signal feature-based Wi-Fi localization, we present how to utilize the time of arrival (TOA), the time difference of arrival (TDOA) as well as the arrival of angle (AOA) to analyze the error bound of localization systems. Regarding the received signal strength (RSS) characteristic-based Wi-Fi localization, we clarify the error bound estimation approaches for both the wireless signal propagation-based and location fingerprinting-based localization schemes. In addition, some future directions with respect to the error bound estimation for Wi-Fi localization are also discussed.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China (61771083, 61704015), Program for Changjiang Scholars and Innovative Research Team in University (IRT1299), Special Fund of Chongqing Key Laboratory (CSTC), Fundamental and Frontier Research Project of Chongqing (cstc2017jcyjAX0380, cstc2015jcyjBX0065), University Outstanding Achievement Transformation Project of Chongqing (KJZH17117), and Postgraduate Scientific Research and Innovation Project of Chongqing (CYS17221).
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Zhou, M., Wang, Y., Wang, S., Yuan, H., Xie, L. (2020). Error Bound Estimation for Wi-Fi Localization: A Comprehensive Survey. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_153
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DOI: https://doi.org/10.1007/978-981-13-6504-1_153
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