Cooperative Positioning in Underwater Sensor Networks

We consider cooperative positioning using acoustic range measurements for underwater sensor networks, including networks formed by autonomous unmanned underwater vehicles (UUVs). Severe multipath scattering from the seabed and ocean surface can result in inaccurate range measurements. In an inhomogeneous medium, such as sea water, the direct path is not necessarily the strongest path or the first arrival. Then, the range measurements based on the first or strongest arrival could be significantly biased. We introduce herein a new centralized cooperative positioning algorithm, referred to as the weighted Gerchberg-Saxton algorithm (WGSA), for underwater sensor networks. We assume that for each acoustic ranging channel, multiple range measurements corresponding to several propagation paths, one of which is the direct path, are available for cooperative positioning. Since it is unknown a priori which path is the direct path, we must identify it first. We show that WGSA can be used to automatically identify the direct path. We also show using numerical examples that WGSA is an effective and efficient approach to cooperative positioning in underwater sensor networks.

[1]  Hao He,et al.  Enhanced Channel Estimation and Symbol Detection for High Speed MIMO Underwater Acoustic Communications , 2009, 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop.

[2]  M. Stojanovic,et al.  Underwater acoustic networks , 2000, IEEE Journal of Oceanic Engineering.

[3]  Dario Pompili,et al.  Challenges for efficient communication in underwater acoustic sensor networks , 2004, SIGBED.

[4]  Hoon Kim,et al.  Monte Carlo Statistical Methods , 2000, Technometrics.

[5]  A.B. Baggeroer,et al.  The state of the art in underwater acoustic telemetry , 2000, IEEE Journal of Oceanic Engineering.

[6]  Joseph Shmuel Picard,et al.  Network Localization with Biased Range Measurements , 2008, IEEE Transactions on Wireless Communications.

[7]  Curt Schurgers,et al.  Motion-aware self-localization for underwater networks , 2008, Underwater Networks.

[8]  John J. Leonard,et al.  Cooperative Localization for Autonomous Underwater Vehicles , 2009, Int. J. Robotics Res..

[9]  John J. Leonard,et al.  Cooperative Localization for Autonomous Underwater Vehicles , 2009, Int. J. Robotics Res..

[10]  Zhou Shengli,et al.  Prospects and problems of wireless communication for underwater sensor networks , 2008 .

[11]  Winston Khoon Guan Seah,et al.  Localization in underwater sensor networks: survey and challenges , 2006, Underwater Networks.

[12]  G. Deane,et al.  Surface wave focusing and acoustic communications in the surf zone , 2004 .

[13]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[14]  J. Preisig,et al.  Estimation of Rapidly Time-Varying Sparse Channels , 2007, IEEE Journal of Oceanic Engineering.

[15]  Shengli Zhou,et al.  IEEE TRANSACTIONS ON SIGNAL PROCESSING (TO APPEAR) 1 Stratification Effect Compensation for Improved Underwater Acoustic Ranging , 2022 .

[16]  M. Gerla,et al.  AUV-Aided Localization for Underwater Sensor Networks , 2007, International Conference on Wireless Algorithms, Systems and Applications (WASA 2007).

[17]  P. Stoica,et al.  Cyclic minimizers, majorization techniques, and the expectation-maximization algorithm: a refresher , 2004, IEEE Signal Process. Mag..

[18]  Dario Pompili,et al.  Underwater acoustic sensor networks: research challenges , 2005, Ad Hoc Networks.

[19]  Hao He,et al.  Enhanced channel estimation and symbol detection for high speed multi-input multi-output underwater acoustic communications. , 2009, The Journal of the Acoustical Society of America.

[20]  Weichang Li,et al.  Estimation and tracking of rapidly time-varying broadband acoustic communication channels , 2006 .

[21]  Christian P. Robert,et al.  Monte Carlo Statistical Methods (Springer Texts in Statistics) , 2005 .

[22]  Moe Z. Win,et al.  Cooperative Localization in Wireless Networks , 2009, Proceedings of the IEEE.

[23]  A. J. Weiss,et al.  Maximum-likelihood position estimation of network nodes using range measurements , 2008 .

[24]  Joseph Shmuel Picard,et al.  Localization of networks using various ranging bias models , 2008, Wirel. Commun. Mob. Comput..

[25]  S. Singh,et al.  The WHOI micro-modem: an acoustic communications and navigation system for multiple platforms , 2005, Proceedings of OCEANS 2005 MTS/IEEE.

[26]  Jiang Li,et al.  On the Performance of Location-Centric Storage in Sensor Networks , 2007, International Conference on Wireless Algorithms, Systems and Applications (WASA 2007).

[27]  Yuan Li,et al.  Research challenges and applications for underwater sensor networking , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..

[28]  R. Gerchberg.  A practical algorithm for the determination of phase from image and diffraction plane pictures , 1972 .

[29]  J. Heidemann,et al.  Underwater Sensor Networking : Research Challenges and Potential Applications , 2006 .

[30]  James Preisig,et al.  Acoustic propagation considerations for underwater acoustic communications network development , 2006, Underwater Networks.

[31]  Jian Li,et al.  Enhanced channel estimation and efficient symbol detection in MIMO underwater acoustic communications , 2009, 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers.

[32]  Patrick McDowell,et al.  UUV Teams For Deep Water Operations , 2001 .

[33]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.