BADIL: accurate device-free indoor localization based on CSI spatial awareness

Ying Liu; Guoqing Li; Dan Liu; Shaofeng Xu

doi:10.1117/12.2668046

20 April 2023 BADIL: accurate device-free indoor localization based on CSI spatial awareness

Ying Liu, Guoqing Li, Dan Liu, Shaofeng Xu

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126020C (2023) https://doi.org/10.1117/12.2668046
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

To meet the application requirements of low cost and high reliability of passive indoor localization system, this paper proposes a device-free indoor localization method based on channel state information (CSI) spatial awareness (BADIL). Firstly, we obtain the CSI through the 5300 NIC, analyze the spatial relationship between CSI fingerprints at different locations, and combine the amplitude and phase information to establish a more stable CSI spatial awareness (CSA) model. Then we design the representation method used to construct the training and test sets of this model. Finally, we combine BP neural networks to implement a device-free localization method in different indoor environments. The results of the experiments have proved the effectiveness of the proposed scheme.

Citation Download Citation

Ying Liu, Guoqing Li, Dan Liu, and Shaofeng Xu "BADIL: accurate device-free indoor localization based on CSI spatial awareness", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126020C (20 April 2023); https://doi.org/10.1117/12.2668046

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