Abstract
In complex indoor environments, non-line-of-sight propagation, multipath fading and shadowing effects can have a significant impact on indoor positioning, resulting in large positioning errors. Aiming at the problem of low positioning accuracy in wireless indoor positioning algorithm, this paper combines the advantages of RSS and CSI features to propose a wireless indoor positioning algorithm combining RSS and CSI features. Firstly, CSI data is filtered in time domain to diminish the impact of complex indoor environment on positioning accuracy. Secondly, use the principle of coherent bandwidth to decrease the CSI data dimension. Finally, the relationship between RSS and CSI is fused by confidence degree to determine the final position estimate. The experimental results show that the time domain filtering can reduce the environmental interference effectively. Compared with the algorithm of positioning using RSS or CSI only, the fusion algorithm has higher positioning accuracy. At the same time, the coherence bandwidth principle is used to lower the dimension, which reduces the complexity of the fusion algorithm.
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Zhang, SX., Fan, XY., Luo, XY. (2020). Wireless Indoor Positioning Algorithm Based on RSS and CSI Feature Fusion. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_249
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DOI: https://doi.org/10.1007/978-981-13-9409-6_249
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