Education, Science, Technology, Innovation and Life
Open Access
Sign In

Ultra-wideband (UWB) precise location problem under signal interference based on Shark optimization algorithm

Download as PDF

DOI: 10.23977/jaip.2020.040108 | Downloads: 36 | Views: 967

Author(s)

Kai Xu 1, Canshi Zhu 1, Zhaosheng Shao 1, Ziqiang Wang 1, Yujie Gao 1

Affiliation(s)

1 School of Information Engineering, Xijing University, Xi 'an, China

Corresponding Author

Canshi Zhu

ABSTRACT

In indoor positioning applications, UWB technology can achieve centimeter-level positioning accuracy, and has good resistance to multipath interference and weakness, as well as strong penetration. However, due to the complex and changeable indoor environment, UWB communication signals are easily blocked. Although UWB technology has penetration capability, it still produces errors. When there is strong interference, abnormal fluctuations of data will occur, and indoor positioning cannot be basically completed, or even serious accidents will occur. Therefore, the problem of ultra-wideband (UWB) precise location under signal interference becomes an urgent problem to be solved. An algorithm is established to find the correct distance between the "abnormal data" processed by the minimum sum of absolute distance differences and "normal data". Optimal target optimization A model based on shark optimization and UWB localization based on least square method are used to establish a comparison model, using shark optimization model can better calculate the exact location of Tag point.

KEYWORDS

Positioning, UWB, Kmeans, Radar map, Matching algorithm, Shark optimization, Least square method

CITE THIS PAPER

Kai Xu, Canshi Zhu, Zhaosheng Shao, Ziqiang Wang, Yujie Gao. Ultra-wideband (UWB) precise location problem under signal interference based on Shark optimization algorithm. Journal of Artificial Intelligence Practice (2021) Vol. 4: 63-67. DOI: http://dx.doi.org/10.23977/jaip.2020.040108.

REFERENCES

[1] Zhang Deli, Niu Rui, Liao Chang-Rong. Design of indoor positioning system [J]. Science and Technology innovation,2021(28):7-9.
[2] Zhang Baojun, Chen Xi, LIAO Yanna, TIAN Qi. UWB/INS indoor Location Algorithm based on DL-LSTM [J]. Sensors and Microsystems,2021,40(10):147-150.
[3] Yuan Feng, JIAO Liang-bao, Chen Nan, GU Hui-dong. Optimization of DS-TWR Ranging Algorithm in indoor Positioning [J]. Computer and Modernization,2021(10):100-106.
[4] Long Rui. Fast Location method of abnormal Nodes in distributed fiber Optic Sensor Network [J]. Laser Journal,2021,42(09):85-89.
[5] Jia Wen. Research on downhole personnel positioning technology and system based on decision-prediction for UWB [J]. Energy technology and management,2021,46(05):166-168.
[6] Zhou Jun, WEI Guo-liang, TIAN Xin, Wang Gan-nan. A novel indoor Location Algorithm combining UWB and IMU data [J]. Microcomputer system,2021,42(08):1741-1746.
[7] Li Shi-yin, Zhu Yuan, LIU Jiang, Wang Xiao-ming, Yang Yuan. Research on THREE-DIMENSIONAL UWB indoor Positioning Method based on SAE-RF [J]. Sensors and Microsystems,2021,40(08):46-49.
[8] Wang Zhi,Zang Liguo,Tang Yiming,Shen Yehui,Wu Zhenxuan. An Intelligent Networked Car-Hailing System Based on the Multi Sensor Fusion and UWB Positioning Technology under Complex Scenes Condition[J]. World Electric Vehicle Journal,2021,12(3):
[9] Paszek Krzysztof,Grzechca Damian,Becker Andreas. Design of the UWB Positioning System Simulator for LOS/NLOS Environments.[J]. Sensors (Basel, Switzerland),2021,21(14)

Downloads: 5760
Visits: 177949

Sponsors, Associates, and Links


All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.