IBeacon/INS Data Fusion Location Algorithm Based on Unscented Kalman Filter

Shouhua WANG; Mingchi LU; Xiyan SUN; Yuanfa JI; Dingmei HU

doi:10.11999/JEIT180748

Volume 41 Issue 9

Sep. 2019

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(9): 2209-2216

Shouhua WANG, Mingchi LU, Xiyan SUN, Yuanfa JI, Dingmei HU. IBeacon/INS Data Fusion Location Algorithm Based on Unscented Kalman Filter[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2209-2216. doi: 10.11999/JEIT180748

Citation:

Shouhua WANG, Mingchi LU, Xiyan SUN, Yuanfa JI, Dingmei HU. IBeacon/INS Data Fusion Location Algorithm Based on Unscented Kalman Filter[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2209-2216. doi: 10.11999/JEIT180748

Citation:

PDF( 2601 KB)

IBeacon/INS Data Fusion Location Algorithm Based on Unscented Kalman Filter

doi: 10.11999/JEIT180748

Shouhua WANG^{1, 2
,
,},
Mingchi LU^{1, 2},
Xiyan SUN^{1, 2, 3},
Yuanfa JI^{1, 2, 3},
Dingmei HU^{1, 2}

1.
Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Technology, Guilin 541004, China
2.
Satellite Navigation and Location Service National & Local Joint Engineering Research Center, Guilin 541004, China
3.
Guangxi Experiment Center of Information Science, Guilin University of Electronic Technology, Guilin 541004, China

Funds: The National Key R&D Program of China (2018YFB0505103), The Foundation of Guangxi Natural Science Foundation (2018GXNSFAA050123), The Foundation of Guangxi Key Laboratory of Precision Navigation Technology and Application (DH201803), The Department of Science and Technology of Guangxi Zhuang Autonomous Region (AA17202033), The Innovation Project of Guet Graduate Education (2018YJCX28)

Received Date: 2018-07-23
Rev Recd Date: 2019-02-25

Available Online: 2019-04-18

Publish Date: 2019-09-10

Abstract

Abstract

In order to overcome the accumulation error in Micro-Electro-Mechanical System-Inertial Navigation System (MEMS-INS) and the jump error in iBeacon fingerprint positioning, an iBencon/MEMS-INS data fusion location algorithm based on Unscented Kalman Filter (UKF) is proposed. The new algorithm solves the distance between the iBeacon anchor and the locating target. The solution of attitude matrix and position are obtained respectively by using accelerometer and gyroscope data. Bluetooth anchor position vector, the carrier speed error and other information constitute state variables. Inertial navigation location and bluetooth system distance information constitute measure variables. Based on state variables and measure variables, the UKF is designed to realize iBencon/MEMS-INS data fusion indoor positioning. The experimental results show that the proposed algorithm can effectively solve the problem of the large accumulation error of INS and the jump error of iBeacon fingerprint positioning, and this algorithm can realize 1.5 m positioning accuracy.
- Inertial sensor,
- Bluetooth beacon,
- Unscented Kalman Filter (UKF),
- Information fusion,
- Pedestrian positioning

FullText(HTML)

References(15)

References

XU Yuan, CHEN Xiyuan, and LI Qinghua. Autonomous integrated navigation for indoor robots utilizing on-line iterated extended Rauch-Tung-striebel smoothing[J]. Sensors, 2013, 13(12): 15937–15953. doi: 10.3390/s131215937

WIN M Z, DARDARI D, MOLISCH A F, et al. History and applications of UWB[scanning the issue][J]. Proceedings of the IEEE, 2009, 97(2): 198–204. doi: 10.1109/JPROC.2008.2008762

CHAN E C L, BACIU G, and MAK S C. Using Wi-Fi signal strength to localize in wireless sensor networks[C]. Proceedings of 2009 WRI International Conference on Communications and Mobile Computing, Yunnan, China, 2009: 538–542.

CASTILLO-CARA M, LOVON-MELGAREJO J, BRAVO-ROCCA G, et al. An empirical study of the transmission power setting for Bluetooth-based indoor localization mechanisms[J]. Sensors (Basel) , 2017, 17(6): 1318–1340. doi: 10.3390/s17061318

CHENG Jiantong, YANG Ling, LI Yong, et al. Seamless outdoor/indoor navigation with WIFI/GPS aided low cost Inertial Navigation System[J]. Physical Communication, 2014, 13: 31–43. doi: 10.1016/j.phycom.2013.12.003

ZHUANG Yuan and EL-SHEIMY N. Tightly-coupled integration of WiFi and MEMS sensors on handheld devices for indoor pedestrian navigation[J]. IEEE Sensors Journal, 2016, 16(1): 224–234. doi: 10.1109/JSEN.2015.2477444

LIAO J K, CHIANG K W, and ZHOU Zhiming. The performance analysis of smartphone-based pedestrian dead reckoning and wireless locating technology for indoor navigation application[J]. Inventions, 2016, 1(4): 25–44. doi: 10.3390/inventions1040025

WALTER C S, SEIFFERT S, VINCENT F, et al. Indoor navigation assistant for visually impaired by pedestrian dead reckoning and position estimative of correction for patterns pecognition[J]. IFAC PapersOnLine, 2016, 49(30): 167–170. doi: 10.1016/j.ifacol.2016.11.149

宋丽君, 秦永元. MEMS加速度计的六位置测试法[J]. 测控技术, 2009, 28(7): 11–13. doi: 10.3969/j.issn.1000-8829.2009.07.004

SONG Lijun and QIN Yongyuan. Six-position testing of MEMS accelerometer[J]. Measurement &Control Technology, 2009, 28(7): 11–13. doi: 10.3969/j.issn.1000-8829.2009.07.004

CORREA A, DIAZ E M, AHMED D B, et al. Advanced pedestrian positioning system to smartphones and smartwatches[J]. Sensors, 2016, 16(11): 1903–1921. doi: 10.3390/s16111903

NETO P, MENDES N, and MOREIRA A P. Kalman filter-based yaw angle estimation by fusing inertial and magnetic sensing: A case study using low cost sensors[J]. Sensor Review, 2015, 35(3): 244–250. doi: 10.1108/SR-10-2014-0723

杨东勇, 顾东袁, 傅晓婕. 一种基于RSSI相似度的室内定位算法[J]. 传感技术学报, 2009, 22(2): 264–268. doi: 10.3969/j.issn.1004-1699.2009.02.025

YANG Dongyong, GU Dongyuan, and FU Xiaojie. An indoor location algorithm base on RSSI-similarity degree[J]. Chinese Journal of Sensors and Actuators, 2009, 22(2): 264–268. doi: 10.3969/j.issn.1004-1699.2009.02.025

PEI Ling, CHEN Ruizhi, LIU Jingbin, et al. Using inquiry-based Bluetooth RSSI probability distributions for indoor positioning[J]. Journal of Global Positioning Systems, 2010, 9(2): 122–130.

李荣冰, 刘建业, 孙永荣. MEMS-IMU构型设计及惯性器件安装误差标定方法[J]. 中国惯性技术学报, 2007, 15(5): 526–529, 563. doi: 10.3969/j.issn.1005-6734.2007.05.005

LI Rongbing, LIU Jianye, and SUN Yongrong. MEMS-IMU configuration and its inertial sensors’ calibration for installation errors[J]. Journal of Chinese Inertial Technology, 2007, 15(5): 526–529, 563. doi: 10.3969/j.issn.1005-6734.2007.05.005

周牧, 王斌, 田增山, 等. 室内BLE/MEMS跨楼层融合定位算法[J]. 通信学报, 2017, 38(5): 1–10. doi: 10.3969/j.issn.1001-2400.2017.05.001

ZHOU Mu, WANG Bin, TIAN Zengshan, et al. Indoor BLE and MEMS based multi-floor fusion positioning algorithm[J]. Journal on Communications, 2017, 38(5): 1–10. doi: 10.3969/j.issn.1001-2400.2017.05.001

Relative Articles

Supplements(0)

Cited By

Proportional views