Abstract
Pure inertial navigation system (INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network (WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter (KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system (FIS), and the fuzzy adaptive Kalman filter (FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
WU Yuan-xin, PAN Xian-fei. Velocity/position integration formula. Part II: Application to strapdown inertial navigation computation [J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(2): 1024–1034.
TENG Yun-long, SHI Yi-bing. A three-dimensional positioning method based on three satellites [J]. Journal of Central South University, 2012, 19(12): 3449–3453.
LUO Cheng-ming, LI Wei, YANG Hai, FAN Meng-bao, YANG Xue-feng. Mobile target positioning using refining distance measurements with inaccurate anchor nodes in chain-type wireless sensor networks [J]. Mobile Networks and Applications, 2014, 19(3): 363–381.
LAMBERTI F, SANNA A, PARAVATI G, MONTUSCHI P, GATTESCHI V, DEMARTINI C. Mixed Marker-based/Marker-less visual odometry system for mobile robots [J]. International Journal of Advanced Robotic Systems, 2013, 10(1): 1–11.
AGHILI F, SALERNO A. Driftless 3-D attitude determination and positioning of mobile robots by integration of IMU with two RTK GPSs [J]. IEEE/ASME Transactions on Mechatronics, 2013, 18(1): 21–31.
ZHANG Tao, XU Xiao-su. A new method of seamless land navigation for GPS/INS integrated system [J]. Measurement, 2012, 45(1): 691–701.
ADUSUMILLI S, BHATT D, WANG H, BHATTACHARYA P, DEVABHAKTUNI V. A low-cost INS/GPS integration methodology based on random forest regression [J]. Expert Systems with Applications, 2013, 40(11): 4653–4659.
HU Hai-dong, HUANG Xian-lin, LI Ming-ming, SONG Zhuo-yue. Federated unscented particle filtering algorithm for SINS/CNS/GPS system [J]. Journal of Central South University of Technology, 2010, 17(4): 778–785.
QIN Hong-lei, CONG Li, SUN Xing-li. Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation [J]. Journal of Systems Engineering and Electronics, 2012, 23(2): 256–264. (in Chinese)
CHANGI A Y, LIU T C. Performance evaluation of real-time indoor positioning with active RFID and ZigBee-based WSN systems [J]. Journal of Vibroengineering, 2013, 15(2): 736–745.
LU Y S, LAI C F, HU C C, HUANG Y M, GE X H. Path loss exponent estimation for indoor wireless sensor positioning [J]. KSII Transactions on Internet and Information Systems, 2010, 4(3): 243–257.
EVENNOU F, MARX F. Advanced integration of WiFi and inertial navigation systems for indoor mobile positioning [J]. EURASIP Journal on Applied Signal Processing, 2006, Article ID: 86706, 1–11.
RUIZ A R J, GRANJA F S, HONORATO PRIETO J C, ROSAS J I G. Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements [J]. IEEE Transactions on Instrumentation and Measurement, 2012, 1(61): 178–188.
XU Yuan, CHEN Xi-yuan, LI Qing-hua. Unbiased tightly-coupled INS/WSN integrated navigation based on extended Kalman filter [J]. Journal of Chinese Inertial Technology, 2012, 20(3): 292–299. (in Chinese)
LI Qing-hua, CHEN Xi-yuan, XU Yuan. Distributed H∞ fusion filter design for INS/WSN integrated positioning system [J]. Journal of Southeast University (English Edition), 2012, 28(2): 164–168.
WANG Tian-miao, WANG Chao-lei, LIANG Jian-hong, CHEN Yang, ZHANG Yi-cheng. Vision-aided inertial navigation for small unmanned aerial vehicles in GPS-denied environments [J]. International Journal of Advanced Robotic Systems, 2013, 10(1): 1–12.
JWO D J, YANG C F, CHUANG C H, LIN K C. A novel design for the ultra-tightly coupled GPS/INS navigation system [J]. Journal of Navigation, 2012, 65(4): 717–747.
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation item: Project(2013AA06A411) supported by the National High Technology Research and Development Program of China; Project(CXZZ14_1374) supported by the Graduate Education Innovation Program of Jiangsu Province, China; Project supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China
Rights and permissions
About this article
Cite this article
Yang, H., Li, W. & Luo, Cm. Fuzzy adaptive Kalman filter for indoor mobile target positioning with INS/WSN integrated method. J. Cent. South Univ. 22, 1324–1333 (2015). https://doi.org/10.1007/s11771-015-2649-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11771-015-2649-9