TOA positioning algorithm of LBL system for underwater target based on PSO

doi:10.23919/JSEE.2023.000107

Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (5): 1319-1332.doi: 10.23919/JSEE.2023.000107

• Control Theory and Application • Previous Articles Next Articles

TOA positioning algorithm of LBL system for underwater target based on PSO

Yao XING¹(), Jiongqi WANG¹(), Zhangming HE¹(), Xuanying ZHOU¹(), Yuyun CHEN¹^,²(), Xiaogang PAN³^,*()

¹ College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China
² School of Mathematics and Big Data, Foshan University, Foshan 528000, China
³ College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Received:2022-03-07 Online:2023-10-18 Published:2023-10-30
Contact: Xiaogang PAN E-mail:y__1326@163.com;wjq_gfkd@163.com;hzmnudt@sina.com;Julia_chow07@163.com;kasineya@sina.com;panxiaogang_nudt@163.com
About author:
XING Yao was born in 1997. He received his B.S. degree in applied mathematics from National University of Defense Technology, Changsha, China, in 2020. Currently, he is working toward his M.S. degree at the College of Liberal Arts and Sciences, National University of Defense Technology. His current research interests are data fusion, velocity measuring and positioning, systematic error identification, and target localization using underwater sound. E-mail: y__1326@163.com

WANG Jiongqi was born in 1979. He received his B.S. degree in applied mathematics from Zhejiang University, Hangzhou, China, in 2002, and his M.S. and Ph.D. degrees in system science from National University of Defense Technology, in 2004 and 2008, respectively. He is a professor in the College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, China. His research interests include measurement data analysis, parameter estimation, system identification, and space target state filter and its applications. E-mail: wjq_gfkd@163.com

HE Zhangming was born in 1985. He obtained his B.S. and M.S. degrees in applied mathematics from National University of Defense Technology, Changsha, China, in 2008 and 2010, respectively. From 2013 to 2014, he was a visiting scholar in Institute for Automatic Control and Complex Systems, University of Duisburg-Essen, Duisburg, Germany. He obtained his Ph.D. degree in system science from National University of Defense Technology, in 2015. He is a lecturer since 2015 and an associate professor since 2019 in the College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, China. His research interests include fault diagnosis and prognosis, signal processing, and system identification. E-mail: hzmnudt@sina.com

ZHOU Xuanying was born in 1991. She received her B.S., M.S., and Ph.D. degrees in applied mathematics from National University of Defense Technology, Hunan, in 2013, 2016, and 2019, respectively. She is a lecturer at the College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, China. Her research interests include system modelling, data processing, missiles, and signal process and its applications. E-mail: Julia_chow07@163.com

CHEN Yuyun was born in 1979. She received her B.S., M.S., and Ph.D. degrees in applied mathematics from National University of Defense Technology, Changsha, Hunan, in 2002, 2004 and 2017, respectively. She is a professor in the School of Mathematics and Big Data, Foshan University. Her main research interests include data analysis, nonlinear filter, and parameter estimation. E-mail: kasineya@sina.com

PAN Xiaogang was born in 1979. He received his Ph.D. degree in applied mathematics from National University of Defense Technology in 2009. He is a professor and master ’s supervisor. His main research interests are mission planning and operational research analysis. E-mail: panxiaogang_nudt@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (61903086; 61903366; 62001115), the Natural Science Foundation of Hunan Province (2019JJ50745; 2020JJ4280; 2021JJ40133), and the Fundamentals and Basic of Applications Research Foundation of Guangdong Province (2019A1515110136)

Abstract

Abstract:

For the underwater long baseline (LBL) positioning systems, the traditional distance intersection algorithm simplifies the sound speed to a constant, and calculates the underwater target position parameters with a nonlinear iteration. However, due to the complex underwater environment, the sound speed changes with time and space, and then the acoustic propagation path is actually a curve, which inevitably causes some errors to the traditional distance intersection positioning algorithm. To reduce the position error caused by the uncertain underwater sound speed, a new time of arrival (TOA) intersection underwater positioning algorithm of LBL system is proposed. Firstly, combined with the vertical layered model of the underwater sound speed, an implicit positioning model of TOA intersection is constructed through the constant gradient acoustic ray tracing. And then an optimization function based on the overall TOA residual square sum is advanced to solve the position parameters for the underwater target. Moreover, the particle swarm optimization (PSO) algorithm is replaced with the traditional nonlinear least square method to optimize the implicit positioning model of TOA intersection. Compared with the traditional distance intersection positioning model, the TOA intersection positioning model is more suitable for the engineering practice and the optimization algorithm is more effective. Simulation results show that the proposed methods in this paper can effectively improve the positioning accuracy for the underwater target.

Key words: long baseline (LBL) positioning system, sound speed profile, constant gradient acoustic ray tracing, time of arrival (TOA) intersection model, particle swarm optimization (PSO)

Yao XING, Jiongqi WANG, Zhangming HE, Xuanying ZHOU, Yuyun CHEN, Xiaogang PAN. TOA positioning algorithm of LBL system for underwater target based on PSO[J]. Journal of Systems Engineering and Electronics, 2023, 34(5): 1319-1332.

Figures/Tables 17

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Buoy	x/m	y/m	z/m
1	100	100	−1
2	100	−100	−1
3	−100	100	−1
4	−100	−100	−1
5	50	0	−1
6	0	50	−1
7	−50	0	−1
8	0	−50	−1

Algorithm	$\overline{\left\| \Delta { {x} } \right\|}/{\rm{m} }$	$\overline{\left\| \Delta { {y}} \right\|}/{\rm{m} }$	$\overline{\left\| \Delta { {z}} \right\|}/{\rm{m} }$	$\overline{\left\\| \Delta { { {\boldsymbol{X} } } } \right\\|}/{\rm{m} }$
M1	0.5778	0.1869	2.6452	2.7210
M2	0.1757	0.0858	1.0234	1.0506
M3	0.0944	0.0211	0.0593	0.1233

Algorithm	$\overline{\left\| \Delta { {x} } \right\|}/{\rm{m} }$	$\overline{\left\| \Delta { {y} } \right\|}/{\rm{m} }$	$\overline{\left\| \Delta { {z}} \right\|}/{\rm{m} }$	$\overline{\left\\| \Delta { {{\boldsymbol{X}}}} \right\\|}/{\rm{m} }$
M1	0.5384	0.5377	0.5146	0.9186
M2	0.2166	0.2169	0.3720	0.4820
M3	0.0288	0.0288	0.0507	0.0650

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TOA positioning algorithm of LBL system for underwater target based on PSO

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