ESGWKNN: Research on Indoor Localization Algorithm Based on Wi-Fi-Reference-Cited by-同舟云学术

ESGWKNN: Research on Indoor Localization Algorithm Based on Wi-Fi

Published:2024-06-13 Issue: Volume: Page:
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Author:

Ye Run¹,Pan Shun¹,Yan Bin¹,Zhang Cheng²,Zhou Xiaojia¹

Affiliation:

1. University of Electronic Science and Technology of China

2. Yangtze River Delta Research Institute(Huzhou), University of Electronic Science and Technology of China

Abstract

Aiming at the problem that the accuracy of the traditional WiFi-based K-Nearest Neighbor algorithm (KNN) indoor positioning algorithm cannot meet the requirements of precise positioning, this paper proposes a K-nearest neighbor indoor positioning algorithm based on location range limitation, namely the algorithm combining echo state network and Gaussian weighted K-nearest neighbors (ESGWKNN). The ESGWKNN algorithm first uses the echo state network to estimate the range to obtain the local spatial range information, and then uses the GWKNN algorithm to accurately locate within the local spatial range to reduce the positioning accuracy problem caused by excessive space. The experimental results show that compared with the traditional KNN algorithm, the ESGWKNN algorithm has higher positioning accuracy.

Publisher

Research Square Platform LLC

Reference15 articles.

1. Zhang, H., & Pan, S. (2023). LSOS: An FG Position Method Based on Group Phase Ranging Ambiguity Estimation of BeiDou Pseudolite[J]. Remote Sensing, 15(7): 1924.

2. Wenxiang Lin,Kunchan Lan,et al.Indoor Location Learning Over Wireless Fingerprinting System With Particle Markov Chain;Kian;Model[J] IEEE Access,2019

3. Validation of UWB positioning systems for player tracking in tennis[J];Umek A;Personal and Ubiquitous Computing,2020

4. Billa, A., Shayea, I., Alhammadi, A. (2020). An overview of indoor localization technologies: Toward IoT navigation services[C]//2020 IEEE 5th International Symposium on Telecommunication Technologies (ISTT). IEEE, : 76–81.

5. Liu, C., Wang, H., Liu, M. (2021). Research and analysis of indoor positioning technology[C]//2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE). IEEE, : 1212–1217.