Filtering Analysis of Navigation Data Processing for Personnel Positioning System

Lianhong Ding; Hongqing Sang; Juntao Li

doi:doi:10.11648/j.sjams.20160403.12

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Filtering Analysis of Navigation Data Processing for Personnel Positioning System

Lianhong Ding, Hongqing Sang, Juntao Li

Published in Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 3)

Received: 18 April 2016 Accepted: 28 April 2016 Published: 13 May 2016

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Abstract

Ultra wideband technology is a more precise indoor positioning technology. But the UWB positioning output would be unstable if the signal from base station were blocked. The low cost inertial positioning is a method to make up a method for indoor navigation. However, the positioning error will accumulate quickly due to the low cost inertial measurement error. To solve this problem, we selected the MPU6050 module as a chip and Simulated test with Extended Kalman Filter and Unscented Kalman Filter algorithms, and carried out the error analysis on both of them. Finally, come to sampling Kalman filter estimation accuracy estimation is more accurate, more suitable for MPU6050 positioning algorithm.

Published in	Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 3)
DOI	10.11648/j.sjams.20160403.12
Page(s)	97-100
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Indoor Positioning, Location Algorithm, Combined Positioning, Extended Calman Filter

References

[1]	Wang Jianping, Xu Heng, Li Qiyue. The mobile node localization Calman filtering algorithm on [J]. Journal of electronic measurement and instrument based on the 2013, 02: 120-126.
[2]	Xia Nan, Qiu Tianshuang, Li Jingchun, Li Shufang. A nonlinear filtering algorithm based on Calman filter and particle filter [J]. Journal of electronics, 2013, 01: 148-152.
[3]	Gao Mingyu. He Zhiwei, Xu Jie. Based on sampling points Kalman filtering power battery SOC estimation [J]. Electrotechnical Journal of, 2011, 11: 161-167.
[4]	Zhang Qiuzhao, Zhang Shubi, Zheng Nanshan, Wang Jian. The multiple fading robust volume of the combined system of Calman GPS/INS filter [J]. Journal of China University of Mining and Technology, 2014, 01: 162-168.
[5]	Repair spring wave, Ren Xiao, Li Yanqing, Liu Mingfeng. Short term prediction method of wind speed series based on Calman filter [J]. Journal of electrical engineering, 2014, 02: 253-259.
[6]	Liu Qi, Yan Li, Zhou. The technical characteristics and development direction of modern telecommunication technology [J]. UWB, 2009, 10: 6-10+18.
[7]	Wang Hongjian, Jing Wong, Bian Xinqian, Fu Guixia. SLAM [J]. EKF under water robot combined navigation based on 2012, 01: 56-64.
[8]	Wang Lu, Li Guangchun, Qiao Xiangwei, Wang Zhaolong, Ma Tao. Adaptive UKF algorithm [J]. automation of the maximum likelihood criterion and expectation maximization algorithm based on 2012, 07: 1200-1210.
[9]	Lin Zhao, Wang Xiaoxu, Sun Ming, Ding Jicheng, Yan Chao. [J]. automation of adaptive UKF filtering algorithm for maximum a posteriori estimation and weighted index based on 2010, 07: 1007-1019.
[10]	Ge Quanbo, Li Wenbin, Sun Ruoyu, Xu Zi. Estimation of [J]. automation of EKF centralized fusion based on 2013,06:816-825.

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APA Style

Lianhong Ding, Hongqing Sang, Juntao Li. (2016). Filtering Analysis of Navigation Data Processing for Personnel Positioning System. Science Journal of Applied Mathematics and Statistics, 4(3), 97-100. https://doi.org/10.11648/j.sjams.20160403.12

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ACS Style

Lianhong Ding; Hongqing Sang; Juntao Li. Filtering Analysis of Navigation Data Processing for Personnel Positioning System. Sci. J. Appl. Math. Stat. 2016, 4(3), 97-100. doi: 10.11648/j.sjams.20160403.12

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AMA Style

Lianhong Ding, Hongqing Sang, Juntao Li. Filtering Analysis of Navigation Data Processing for Personnel Positioning System. Sci J Appl Math Stat. 2016;4(3):97-100. doi: 10.11648/j.sjams.20160403.12

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@article{10.11648/j.sjams.20160403.12,
  author = {Lianhong Ding and Hongqing Sang and Juntao Li},
  title = {Filtering Analysis of Navigation Data Processing for Personnel Positioning System},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {3},
  pages = {97-100},
  doi = {10.11648/j.sjams.20160403.12},
  url = {https://doi.org/10.11648/j.sjams.20160403.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160403.12},
  abstract = {Ultra wideband technology is a more precise indoor positioning technology. But the UWB positioning output would be unstable if the signal from base station were blocked. The low cost inertial positioning is a method to make up a method for indoor navigation. However, the positioning error will accumulate quickly due to the low cost inertial measurement error. To solve this problem, we selected the MPU6050 module as a chip and Simulated test with Extended Kalman Filter and Unscented Kalman Filter algorithms, and carried out the error analysis on both of them. Finally, come to sampling Kalman filter estimation accuracy estimation is more accurate, more suitable for MPU6050 positioning algorithm.},
 year = {2016}
}

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TY  - JOUR
T1  - Filtering Analysis of Navigation Data Processing for Personnel Positioning System
AU  - Lianhong Ding
AU  - Hongqing Sang
AU  - Juntao Li
Y1  - 2016/05/13
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160403.12
DO  - 10.11648/j.sjams.20160403.12
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 97
EP  - 100
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160403.12
AB  - Ultra wideband technology is a more precise indoor positioning technology. But the UWB positioning output would be unstable if the signal from base station were blocked. The low cost inertial positioning is a method to make up a method for indoor navigation. However, the positioning error will accumulate quickly due to the low cost inertial measurement error. To solve this problem, we selected the MPU6050 module as a chip and Simulated test with Extended Kalman Filter and Unscented Kalman Filter algorithms, and carried out the error analysis on both of them. Finally, come to sampling Kalman filter estimation accuracy estimation is more accurate, more suitable for MPU6050 positioning algorithm.
VL  - 4
IS  - 3
ER  -

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Author Information

Lianhong Ding

School of Information, Beijing Wuzi University, Beijing, China
Hongqing Sang

School of Logistics Engineering, School of Information, Beijing Wuzi University, Beijing, China
Juntao Li

School of Information, Beijing Wuzi University, Beijing, China

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APA Style

Lianhong Ding, Hongqing Sang, Juntao Li. (2016). Filtering Analysis of Navigation Data Processing for Personnel Positioning System. Science Journal of Applied Mathematics and Statistics, 4(3), 97-100. https://doi.org/10.11648/j.sjams.20160403.12

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ACS Style

Lianhong Ding; Hongqing Sang; Juntao Li. Filtering Analysis of Navigation Data Processing for Personnel Positioning System. Sci. J. Appl. Math. Stat. 2016, 4(3), 97-100. doi: 10.11648/j.sjams.20160403.12

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AMA Style

Lianhong Ding, Hongqing Sang, Juntao Li. Filtering Analysis of Navigation Data Processing for Personnel Positioning System. Sci J Appl Math Stat. 2016;4(3):97-100. doi: 10.11648/j.sjams.20160403.12

Copy | Download

@article{10.11648/j.sjams.20160403.12,
  author = {Lianhong Ding and Hongqing Sang and Juntao Li},
  title = {Filtering Analysis of Navigation Data Processing for Personnel Positioning System},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {3},
  pages = {97-100},
  doi = {10.11648/j.sjams.20160403.12},
  url = {https://doi.org/10.11648/j.sjams.20160403.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160403.12},
  abstract = {Ultra wideband technology is a more precise indoor positioning technology. But the UWB positioning output would be unstable if the signal from base station were blocked. The low cost inertial positioning is a method to make up a method for indoor navigation. However, the positioning error will accumulate quickly due to the low cost inertial measurement error. To solve this problem, we selected the MPU6050 module as a chip and Simulated test with Extended Kalman Filter and Unscented Kalman Filter algorithms, and carried out the error analysis on both of them. Finally, come to sampling Kalman filter estimation accuracy estimation is more accurate, more suitable for MPU6050 positioning algorithm.},
 year = {2016}
}

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TY  - JOUR
T1  - Filtering Analysis of Navigation Data Processing for Personnel Positioning System
AU  - Lianhong Ding
AU  - Hongqing Sang
AU  - Juntao Li
Y1  - 2016/05/13
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160403.12
DO  - 10.11648/j.sjams.20160403.12
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 97
EP  - 100
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160403.12
AB  - Ultra wideband technology is a more precise indoor positioning technology. But the UWB positioning output would be unstable if the signal from base station were blocked. The low cost inertial positioning is a method to make up a method for indoor navigation. However, the positioning error will accumulate quickly due to the low cost inertial measurement error. To solve this problem, we selected the MPU6050 module as a chip and Simulated test with Extended Kalman Filter and Unscented Kalman Filter algorithms, and carried out the error analysis on both of them. Finally, come to sampling Kalman filter estimation accuracy estimation is more accurate, more suitable for MPU6050 positioning algorithm.
VL  - 4
IS  - 3
ER  -

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