Abstract
With the rapid development of Mobile Internet and the popularity of mobile terminal equipment, demands on the Location-Based Services (LBS), especially the indoor localization are growing. The Access Point (AP) Filtering work is a very critical part in the indoor localization technology. Aiming at the problems which exist in the present AP filtering algorithms which include the low positioning accuracy, the long computation time and the high computational complexity, in this paper, we proposed an AP filtering algorithm based on the Cramer-Rao Lower Bound (CRLB) and Gradient standard. The AP filtering algorithm can effectively remove the APs with large noise to avoid them from negative effect to the results of localization, then to achieve the goals that reducing the calculation complexity in the positioning phase and improving the positioning accuracy. The experiment results show that the AP filtering algorithm proposed in this paper is superior to the traditional AP filtering algorithms in positioning performance, especially, it is applicable to the case of AP number limited and practical public places with multiple APs at the same time.
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Acknowledgment
This work is supported by the National Natural Science Foundation of China (Grant No. 61461037), and the Natural Science Foundation of Inner Mongolia Autonomous Region of China under Grant 2017JQ09.
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Duan, Q., Liu, M. (2018). An Access Point Filtering Method Based on CRLB in Indoor Localization Technology. In: Bi, Y., Chen, G., Deng, Q., Wang, Y. (eds) Embedded Systems Technology. ESTC 2017. Communications in Computer and Information Science, vol 857. Springer, Singapore. https://doi.org/10.1007/978-981-13-1026-3_3
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DOI: https://doi.org/10.1007/978-981-13-1026-3_3
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