Multi-Sonar Integration and the Advent of Senor Intelligence

The subsea environment represents the last major frontier of discovery on Earth. It is envisioned that exploration of the seabed, in both our deep-ocean and inshore waters, will present a multitude of potential economic opportunities. Recent interest in the everexpanding exploration for valuable economic resources, the growing importance of environmental strategies and the mounting pressure to stake territorial claims, has been the main motivation behind the increasing importance of detailed seabed mapping, and rapid advancements in sensor technology and marine survey techniques (McPhail, 2002; Nitsche et al., 2004; Desa et al., 2006; Niu et al., 2007). Over the past decade, there has been an increasing emphasis on the integration of multiple sonar sensors during marine survey operations (Wright et al., 1996; Laban, 1998; Pouliquen et al., 1999; Yoerger et al., 2000; Duxfield et al., 2004; Kirkwood et al., 2004). The synergies offered by fusing and concurrently operating multiple acoustic mapping devices in a single survey suite underpin the desire for such an operational configuration; facilitating detailed surveying of the ocean environment, while enabling the information encoded in one instrument’s dataset to be used to correct artefacts in the other. Innovative advancements in the intelligence of sensors have permitted time-critical decisions to be made based on the assessment of real-time environmental information. Inmission data evaluation and decision making allows for the optimisation of surveys, improving mission efficiency and productiveness. While low-frequency ( 200kHz) imaging sonar generates high-resolution datasets, providing greater detail and improving data analysis. High-frequency sonar systems are therefore the desired sensor systems used during seabed survey missions. However, seawater severely restricts acoustic wave propagation, reducing the range (field of view) of high-resolution sonar in particular. Consequently, high-resolution survey sensors must be deployed in close-proximity to the seabed. UUVs are ideal platforms for providing the nearseabed capability required, and often demanded, by marine survey operations (McPhail, 2002). Furthermore, recent technological advancements have allowed UUVs to provide highresolution survey capabilities for the largely unexplored deep-water environments, previously considered uneconomical or technically infeasible (Whitcomb, 2000). O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

[1]  Elliot R McVeigh,et al.  Emerging imaging techniques. , 2006, Circulation research.

[2]  D. Toal,et al.  Automated Optimisation of Simultaneous Multibeam and Sidescan Sonar Seabed Mapping , 2007, OCEANS 2007 - Europe.

[3]  W. Brown Synthetic Aperture Radar , 1967, IEEE Transactions on Aerospace and Electronic Systems.

[4]  V. O'Connell,et al.  Mapping marine habitats with high resolution sidescan sonar , 1999 .

[5]  R. L. Wernli AUVs-a technology whose time has come , 2002, Proceedings of the 2002 Interntional Symposium on Underwater Technology (Cat. No.02EX556).

[6]  A. Ishoy How to make survey instruments "AUV-friendly" , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[7]  Jim Bradford,et al.  Data handling methods and target detection results for multibeam and sidescan data collected as part of the search for SwissAir Flight 111 , 1999 .

[8]  Stephen D. McPhail Autonomous Underwater Vehicles: Are they the Ideal Sensor Platforms for Ocean Margin Science? , 2002 .

[9]  Louis L. Whitcomb,et al.  Underwater robotics: out of the research laboratory and into the field , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[10]  Belur V. Dasarathy Industrial applications of multi-sensor multi-source information fusion , 2000, Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482).

[11]  H. Thomas,et al.  Mapping payload development for MBARI's Dorado-class AUVs , 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

[12]  Daniel Toal,et al.  Approach to the Real-Time Adaptive Control of Multiple High-Frequency Sonar Survey Systems for Unmanned Underwater Vehicles , 2008 .

[13]  Tien-Hsin Chao,et al.  Multi-sensor data fusion for seafloor mapping and ordnance location , 1996, Proceedings of Symposium on Autonomous Underwater Vehicle Technology.

[14]  Rudy J Kloser,et al.  Optimal seabed habitat mapping using multibeam acoustics with associated physical and visual sampling devices - at sea trials , 2000 .

[15]  K. Shono,et al.  Integrated hydro-acoustic survey scheme for mapping of sea bottom ecology , 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

[16]  Per Espen Hagen,et al.  The HUGIN AUV "Plug and play" payload system , 2002, OCEANS '02 MTS/IEEE.

[17]  G. E. Fogg,et al.  Methods for the Study of Marine Benthos. , 1972 .

[18]  C. Heron,et al.  Imaging Techniques , 2003, NeuroImage.

[19]  W. J. Kirkwood,et al.  Development of the DORADO mapping vehicle for multibeam, subbottom, and sidescan science missions , 2007, J. Field Robotics.

[20]  John Shaw,et al.  Integration of multibeam bathymetry and sidescan sonar data for geological surveys , 1999, Oceans '99. MTS/IEEE. Riding the Crest into the 21st Century. Conference and Exhibition. Conference Proceedings (IEEE Cat. No.99CH37008).

[21]  Richard P. Signell,et al.  Surficial geology in central Narragansett Bay, Rhode Island: interpretations of sidescan sonar and multibeam bathymetry , 2006 .

[22]  Xavier Lurton,et al.  An Introduction to Underwater Acoustics: Principles and Applications , 2010 .

[23]  Neil Bose,et al.  Applications of Autonomous Underwater Vehicles in Offshore Petroleum Industry Environmental Effects Monitoring , 2007 .

[24]  Craig J. Brown,et al.  Mapping seabed biotopes at Hastings Shingle Bank, eastern English Channel. Part 1. Assessment using sidescan sonar , 2004, Journal of the Marine Biological Association of the United Kingdom.

[25]  Peter Lonsdale,et al.  Simultaneous operation of the Sea Beam multibeam echo-sounder and the SeaMARC II bathymetric sidescan sonar system , 1990 .

[26]  Synthetic Aperture Sonar : Frontiers in Underwater Imaging Revolutionary Sonar Imaging Technology for Undersea Warfare And the Commercial Marketplace , 2022 .

[27]  John C. Curlander,et al.  Synthetic Aperture Radar: Systems and Signal Processing , 1991 .

[28]  D. Yoerger,et al.  Multisensor mapping of the deep seafloor with the Autonomous Benthic Explorer , 2000, Proceedings of the 2000 International Symposium on Underwater Technology (Cat. No.00EX418).

[29]  B. Zerr,et al.  Seabed segmentation using a combination of high frequency sensors , 1999, Oceans '99. MTS/IEEE. Riding the Crest into the 21st Century. Conference and Exhibition. Conference Proceedings (IEEE Cat. No.99CH37008).

[30]  Elgar Desa,et al.  Potential of autonomous underwater vehicles as new generation ocean data platforms , 2006 .

[31]  Echosounder IDENTIFICATION OF SEAFLOOR HABITATS IN COASTAL SHELF WATERS USING A MULTIBEAM ECHOSOUNDER , 2004 .

[32]  J. Bennett,et al.  Field Testing Of A New Deep Water Multibeam Echo Sounder , 1991, OCEANS 91 Proceedings.

[33]  Frank O. Nitsche,et al.  Process-related classification of acoustic data from the Hudson River Estuary , 2004 .

[34]  Philippe Jeanjean,et al.  High-Resolution AUV Surveys of the Eastern Sigsbee Escarpment , 2002 .