Similar articles

Abstract: underwater mobile sensor networks (UMSNs) with free-floating sensors are more suitable for understanding the immense underwater environment. target tracking, whose performance depends on sensor localization accuracy, is one of the broad applications of UMSNs. However, in UMSNs, sensors move with environmental forces, so their positions change continuously, which poses a challenge on the accuracy of sensor localization and target tracking. We propose a high-accuracy localization with mobility prediction (HLMP) algorithm to acquire relatively accurate sensor location estimates. The HLMP algorithm exploits sensor mobility characteristics and the multi-step Levinson-Durbin algorithm to predict future positions. Furthermore, we present a simultaneous localization and target tracking (SLAT) algorithm to update sensor locations based on measurements during the process of target tracking. Simulation results demonstrate that the HLMP algorithm can improve localization accuracy significantly with low energy consumption and that the SLAT algorithm can further decrease the sensor localization error. In addition, results prove that a better localization accuracy will synchronously improve the target tracking performance.

水下移动传感器网络高能效节点定位和目标跟踪

[1]Aggarwal P, Wang X, 2011. Joint sensor localisation and target tracking in sensor networks. IET Radar Sonar Navig, 5(3):225-233.

[2]Arasaratnam I, Haykin S, 2009. Cubature Kalman filters. IEEE Trans Autom Contr, 54(6):1254-1269.

[3]Austin TC, Stokey RP, Sharp KM, 2000. Paradigm: a buoy-based system for AUV navigation and tracking. OCEANS MTS/IEEE Conf and Exhibition, p.935-938.

[4]Beerens SP, Ridderinkhof H, Zimmerman JTF, 1994. An analytical study of chaotic stirring in tidal areas. Chaos Sol Fract, 4(6):1011-1029.

[5]Bhardwaj M, Chandrakasan AP, 2002. Bounding the lifetime of sensor networks via optimal role assignments. 21 ^st Annual Joint Conf of the IEEE Computer and Communications Societies, p.1587-1596.

[6]Brockwell PJ, Dahlhaus R, 2004. Generalized Levinson-Durbin and Burg algorithms. J Econom, 118(1-2):129-149.

[7]Calafate CT, Lino C, Diaz-Ramirez A, et al., 2013. An integral model for target tracking based on the use of a WSN. Sensors, 13(6):7250-7278.

[8]Chen HY, Zhang SL, Liu MQ, et al., 2017. An artificial measurements-based adaptive filter for energy-efficient target tracking via underwater wireless sensor networks. Sensors, 17(5):971.

[9]Cui JH, Kong JJ, Gerla M, et al., 2006. The challenges of building mobile underwater wireless networks for aquatic applications. IEEE Netw, 20(3):12-18.

[10]Del Moral P, 1997. Nonlinear filering: interacting particle resolution. Compt Rend Acad Sci Ser I-Math, 325(6):653-658.

[11]Guo Y, Liu YT, 2013. Localization for anchor-free underwater sensor networks. Comput Electr Eng, 39(6):1812-1821.

[12]Isbitiren G, Akan OB, 2011. Three-dimensional underwater target tracking with acoustic sensor networks. IEEE Trans Veh Technol, 60(8):3897-3906.

[13]Kantas N, Singh SS, Doucet A, 2012. Distributed maximum likelihood for simultaneous self-localization and tracking in sensor networks. IEEE Trans Signal Process, 60(10):5038-5047.

[14]Kim S, Yoo Y, 2013. High-precision and practical localization using seawater movement pattern and filters in underwater wireless networks. IEEE 16^th Int Conf on Computational Science and Engineering, p.374-381.

[15]Kussat NH, Chadwell CD, Zimmerman R, 2005. Absolute positioning of an autonomous underwater vehicle using GPS and acoustic measurements. IEEE J Ocean Eng, 30(1):153-164.

[16]Li WL, Jia YM, Du JP, et al., 2013. Distributed multiple-model estimation for simultaneous localization and tracking with NOLS mitigation. IEEE Trans Veh Technol, 62(6):2824-2830.

[17]Lloret J, 2013. Underwater sensor nodes and networks. Sensors, 13(9):11782-11796.

[18]Mandal AK, Misra S, Ojha T, et al., 2017. Oceanic forces and their impact on the performance of mobile underwater acoustic sensor networks. Int J Commun Syst, 30(1):e2882.

[19]Pardey J, Roberts S, Tarassenko L, 1996. A review of parametric modelling techniques for EEG analysis. Med Eng Phys, 18(1):2-11.

[20]Sozer EM, Stojanovic M, Proakis JG, 2000. Underwater acoustic networks. IEEE J Ocean Eng, 25(1):72-83.

[21]Teng J, Snoussi H, Richard C, et al., 2012. Distributed variational filtering for simultaneous sensor localization and target tracking in wireless sensor networks. IEEE Trans Veh Technol, 61(5):2305-2318.

[22]Wang X, Xu MX, Wang HB, et al., 2012. Combination of interacting multiple models with the particle filter for three-dimensional target tracking in underwater wireless sensor networks. Math Probl Eng, 2012:829451.

[23]Yu CH, Choi JW, 2014. Interacting multiple model filter-based distributed target tracking algorithm in underwater wireless sensor networks. Int J Contr Autom Syst, 12(3):618-627.

[24]Zhang Q, Liu MQ, Zhang SL, 2015. Node topology effect on target tracking based on UWSNs using quantized measurements. IEEE Trans Cybern, 45(10):2323-2335.

[25]Zhou XC, Shen HB, Ye JP, 2011. Integrating outlier filtering in large margin training. J Zhejiang Univ-Sci C (Comput & Electron), 12(5):362-370.

[26]Zhu YM, You ZS, Zhao J, et al., 2001. The optimality for the distributed Kalman filtering fusion with feedback. Automatica, 37(9):1489-1493.