Point mass filter based matching algorithm in gravity aided underwater navigation

doi:10.21629/JSEE.2018.01.15

Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (1): 152-159.doi: 10.21629/JSEE.2018.01.15

• Control Theory and Application • Previous Articles Next Articles

Point mass filter based matching algorithm in gravity aided underwater navigation

Yurong HAN¹(), Bo WANG^1,*(), Zhihong DENG¹(), Mengyin FU²()

¹ School of Automation, Beijing Institute of Technology, Beijing 100081, China
² Nanjing University of Science and Technology, Nanjing 210094, China

Received:2016-09-30 Online:2018-02-26 Published:2018-02-23
Contact: Bo WANG E-mail:761906893@qq.com;wb1020@bit.edu.cn;dzh_deng@bit.edu.cn;fumy@bit.edu.cn
About author:HAN Yurong received her B.S. degree in computer science and technology from the Department of Computer Science, Beijing Institute of Technology, Beijing, China, in 2011, where she is currently pursuing her Ph.D. degree with the Integrated Navigation and Intelligent Navigation Laboratory. Her current research interests is gravityaided inertial navigation. E-mail: 761906893@qq.com|WANG Bo received his B.S. and Ph.D. degrees from the School of Automation, Beijing Institute of Technology, Beijing, China, in 2004 and 2009, respectively. He was with the Universidad Polit′ ecnica de Madrid, Spain, from 2005 to 2006, as an exchange student. From 2009 to 2011, he was a post-doctoral research associate with Beihang University, Beijing, and was involved in navigation, guidance and control. Since 2011, he has been with the School of Automation, Beijing Institute of Technology, first as a lecturer, and currently an associate professor. His research interests include inertial navigation, integrated navigation, and signal processing. E-mail: wb1020@bit.edu.cn|DENG Zhihong received her B.S. and Ph.D. degrees in control theory and engineering from the Department of Automation, Harbin Engineering University, Harbin, China, in 1997 and 2001, respectively. She held a post-doctoral position with the Beijing Institute of Technology from 2001 to 2003. Since 2004, she has been with the Department of Automatic Control, Beijing Institute of Technology, first as an associate professor and then, since 2010, as a professor. Her research interests are strapdown inertial navigation system, information fusion and filter, and intelligent navigation technology. E-mail: dzh_deng@bit.edu.cn|FU Mengyin received his B.S. degree in radioelectronics from Liaoning University, Shenyang, China, in 1987, M.S. degree in control theory from the Beijing Institute of Technology, Beijing, China, in 1992, and Ph.D. degree in geodetic engineering from the Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China, in 2000. He was a professor with the Department of Automatic Control, Beijing Institute of Technology, from 1992 to 2012. Since 2012, he has been with the Nanjing University of Science and Technology. His current research interests include inertial navigation and intelligent navigation, navigation, guidance, and control. E-mail: fumy@bit.edu.cn
Supported by:
the National Natural Science Foundation of China(61673060);the National Key R & D Plan(2016YFB0501700);This work was supported by the National Natural Science Foundation of China (61673060) and the National Key R & D Plan (2016YFB0501700)

Abstract

Abstract:

Gravity-aided inertial navigation is a hot issue in the applications of underwater autonomous vehicle (UAV). Since the matching process is conducted with a gravity anomaly database tabulated in the form of a digital model and the resolution is 2'×2', a filter model based on vehicle position is derived and the particularity of inertial navigation system (INS) output is employed to estimate a parameter in the system model. Meanwhile, the matching algorithm based on point mass filter (PMF) is applied and several optimal selection strategies are discussed. It is obtained that the point mass filter algorithm based on the deterministic resampling method has better practicability. The reliability and the accuracy of the algorithm are verified via simulation tests.

Key words: gravity-aided inertial navigation system (INS) navigation, point mass filter (PMF), deterministic resampling

Yurong HAN, Bo WANG, Zhihong DENG, Mengyin FU. Point mass filter based matching algorithm in gravity aided underwater navigation[J]. Journal of Systems Engineering and Electronics, 2018, 29(1): 152-159.

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References 20

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Symbol	Quantity
Initial angle error/($''$)	0.16
Initial position erro/($'$)	0.1
Gyro constant drift/(($^\circ$)/h)	0.01
Gyro random drift/(($^\circ$)/h)	0.001
Accelerometor constant bias/$\mu$g	100
Accelerometor random bias/$\mu $g	10
Velocity/(m/s)	5.144
Acceleration/(m/s$^2$)	0

Nonlinear filter	Latitude/$(')$		Longitude/$(')$
Nonlinear filter	Mean	Standard	Mean	Standard
EKF	–1.877 2	3.509 1	–8.891 7	6.664 6
UKF	2.793 8	2.056 5	1.731 4	3.369 9
PF	2.433 3	2.578 2	0.539 1	3.011 2
PMF	–0.459 0	1.886 0	–1.226 0	2.205 0

Optimal selection method	Latitude/$(')$		Longitude/$(')$
Optimal selection method	Mean	Standard	Mean	Standard
INS	0.016	1.524	–5.867	2.715
MAP	-0.459	1.886	-1.226	2.205
Residual R	-0.248	1.513	–1.822	2.403
Deterministic R	–0.249	1.495	–1.826	2.389
Multiomial R	–0.264	1.528	–1.810	2.439

Point mass filter based matching algorithm in gravity aided underwater navigation

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