Local node selection for target tracking based on underwater wireless sensor networks

Abstract

Traditional sonar-array-based target tracking algorithms may be unsuitable for on-demand tracking missions, since they assume that the sonar arrays should be towed or mounted by a submarine or a ship. Alternatively, underwater wireless sensor networks can offer a promising solution approach. First, each underwater node is battery-powered, so saving energy expenditure is a critical issue. Instead of keeping all sensor nodes active, this paper provides a local node selection (LNS) scheme which increases energy efficiency by waking up only a small part of nodes at each time. Second, considering node's limited computing ability and the real-time requirement for the tracking algorithm, instead of employing the centralised fusion structure, we utilise the distributed Kalman filtering fusion with feedback in this paper. Finally, instead of assuming one sensor node can uniquely determine target's location, a more practical range-only measurement model is proposed. Then the LNS scheme and distributed fusion with feedback are extended to our range-only measurement model. The simulation results demonstrate the efficiency of our scheme.

Keywords:

• local node selection
• distributed Kalman filtering fusion
• target tracking
• range-only measurement model
• underwater wireless sensor networks

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 61374021], [grant number 61071061], [grant number 61222310], [grant number 61174142]; the Specialized Research Fund for the Doctoral Program of Higher Education of China (SRFDP) [grant number 20100101110055], [grant number 20120101110115], [grant number 20130101110109]; the Zhejiang Provincial Science and Technology Planning Projects of China [grant number 2012C21044]; the Marine Interdisciplinary Research Guiding Funds for Zhejiang University [grant number 2012HY009B].

Notes on contributors

Qiang Zhang

Qiang Zhang received the BE degree in control theory and control engineering from Zhejiang University, Hangzhou, China, in 2011. He is currently a PhD student in the College of Electrical Engineering, Zhejiang University, Hangzhou, China. His research interests include localisation for underwater wireless sensor networks and target tracking in underwater wireless sensor networks.

Chaojie Zhang

Chaojie Zhang received the BE and ME degrees in geotechnical engineering exploration from Central South University, Changsha, China, in 1993 and 1999, respectively, and the PhD degree in geotechnical engineering from Zhejiang University, Hangzhou, China, in 2003. He is currently a senior engineer with Zhejiang Institute of Hydraulics & Estuary, Hangzhou, China. He has authored more than 15 papers in major journals and international conferences and holds two CN patents. His current research interests include constitutive model of soft soil, foundation treatment, and in situ monitoring.

Meiqin Liu

Meiqin Liu received the BE and PhD degrees in control theory and control engineering from Central South University, Changsha, China, in 1994 and 1999, respectively. She was a post-doctoral research fellow with the Huazhong University of Science and Technology, Wuhan, China, from 1999 to 2001. She was a visiting scholar with the University of New Orleans, New Orleans, LA, USA, from 2008 to 2009. She is currently a professor with the College of Electrical Engineering, Zhejiang University, Hangzhou, China. She has authored more than 60 peer reviewed papers, including 33 journal papers. Her current research interests include neural network, robust control, multi-sensor network, and information fusion.

Senlin Zhang

Senlin Zhang received the BE degree in control theory and control engineering from the Wuhan University of Technology, Wuhan, China, and the ME degree in control theory and control engineering from Zhejiang University, Hangzhou, China, in 1984 and 1991, respectively. He is currently a professor with the College of Electrical Engineering, Zhejiang University, Hangzhou. His current research interests include textile automation, intelligent systems, and multi-sensory network.