Optimizing Multibeam Data Quality Across the Fleet

1. Optimizing Multibeam Data Quality Across the Fleet TIM GATES (Gates Acoustic Services) VICKI FERRINI (LDEO) JONATHAN BEAUDOIN (CCOM-UNH) PAUL JOHNSON (CCOM-UNH) JOHN HUGHES CLARKE (OMG-UNB)

2. Background • MB workshop at NSF June 2010 in response to fleet-wide issues with multibeam performance • Goals: • Discuss operation of the sonars • Identify common threads in documented problems • Get advice from domain experts and other MB users • Outcomes: • Identified several specific operational and technical issues, some poorly understood, impacting multibeam data quality • Identified a strong need to coordinate operational and technical efforts across the fleet

3. UNOLS FLEET • SCRIPPS • MELVILLE • ROGER REVELLE • WHOI • KNORR • ATLANTIS • UW – THOMAS THOMPSON • UH – KILO MOANA • LDEO – MARCUS LANGSETH

4. Multibeam Advisory Committee (MAC) • Fleet-wide Approach • Facilitate Communication • Community of Stakeholders • Technical Resources • Technical Teams • Shipboard Acceptance • Acoustic Noise • Quality Assurance • Best Practices • Transition into a UNOLS Committee

5. MAC: Committee Planning • In-person meeting once per year • Supplement with Telecon/Web Conferencing • Review Technical Team activities & products • Prioritize ship visits • Address practical implementation of best practices • Discuss concerns/issues from Operators • Ensure MAC is providing necessary resources

6. Overview of Technical Teams ANT and SAT: help optimize ship and system performance QAT: help optimize the way data is acquired

7. MAC: Acoustic Noise Team • Goal: Perform acoustic noise tests to assess and potentially improve sensor efficiency (coverage) and data quality • Establish baseline noise levels • Help populate an archive of historical data on noise properties of each vessel to aid in monitoring over sensor lifetime • Anticipate 2 ship visits per year

8. MAC: Shipboard Acceptance Team • Goal: Ensure all hull-mounted multibeam systems are installed, calibrated, and configured properly and consistently • Participate in Sea Acceptance Trials for new and/or poorly understood existing installations • Anticipate 2 ship visits per year

9. MAC: Quality Assurance Team • Goal: Ensure multibeam sonar systems are operated in a consistent manner that maximizes data accuracy, precision, and scientific utility • Develop and disseminate best practice documentation • Develop and deploy tools and procedures to optimize data quality during acquisition

10. Technical Teams in Action

11. Acoustic Noise Testing • It is planned to acquire baseline acoustic signatures from each UNOLS vessel • Signatures will be acquired from test hydrophones and internal sonar noise routines • Results of acoustic testing will determine: • Propeller cavitation • Hydrodynamic flow noise • Machinery contributions • Bubble sweepdown impacts • Data will be archived for future comparisons and trending of noise backgrounds

12. Acoustic Testing • R/V MELVILLE was tested in January • R/V KILO MOANA is scheduled for testing in June • Previous tests (prior to the MAC) have been accomplished on: • R/V REVELLE • R/V KILO MOANA • R/V MARCUS LANGSETH • R/V ATLANTIS

13. Benefits of Acoustic Testing • Identify acoustic deficiencies that limit full sonar performance • Provide corrective actions for problem areas • Develop “quiet” machinery line-ups for best performance • Develop operational guidance to mitigate acoustic noise issues

14. Recent Acoustic Findings • ATLANTIS – has a cavitating gondola • LANGSETH – quieter at 9 knots than 0 to 8 knots due to controllable pitch propellers • KILO MOANA – Above 9 knots data is controlled by diesel engines which limit sonar performance • MELVILLE – anti-roll system limits sonar performance during roll cycles • REVELLE – bubble sweepdown transients limit sonar performance in higher sea states

15. QAT: R/V Kilo MoanaShip Geometry Verification • Verification of current system geometry by establishing “chain of custody” by reviewing: • Ship drawings • Blom survey (2005): initial survey of mapping system offsets • Applanix site visit reports (2006 & 2008) • IMTEC survey (2012): survey of new EM710 installation • Independently established linear and angular offsets from above documentation and verbal reports of configuration changes • Found and corrected errors in current configuration: • Primary GPS location in POS/MV configuration • Pitch offset in EM710 configuration

16. QAT: R/V Kilo MoanaAssessment of Documentation • Found hardcopy and softcopy operators manuals for EM122 and EM710 • Found out-dated “cookbooks” for EM1002/EM120 on technician’s wiki • Newer “cookbooks” generated for EM710/EM122 and focused on SIS • How to backup all system settings • How to uninstall SIS and remove the database • How to re-install SIS and import system settings to get system back to last known good configuration

17. QAT: R/V Kilo MoanaSoftware Deployment: SVP Editor • Graphical display and editing of XBT data: can interact with data to remove outliers • Implements proposed best-practices: • Augment with database salinity profile (World Ocean Atlas 2009) • Embed measured surface sound speed in upper layer • Use database for vertical extension of cast • Streamlined processing allows for delivery of cast to SIS for immediate application SIS • Server mode: automatically delivers World Ocean Atlas sound speed profiles to SIS while in transit

18. QAT: R/V Kilo MoanaSoftware Deployment: BIST Logger • python script to log BIST output over network via UDP • Includes vessel position/speed and engine RPMs; reduces requirement to embed “metadata” in filenames, e.g. starboard_engine_200_rpm_5kts_045_heading_BIST.txt • Enables acquisition of rich acoustic noise data sets with minimal effort • Results from acquisition of 294 BIST noise spectrum measurements over 38 minute time span with gradual increases in ship speed. Achieved with one operator repeatedly launching the appropriate BIST test; all data and metadata were logged automatically. Plot generated with Matlab.

19. We value your input! • You can benefit: Reports and tools will be available publicly online • You can contribute also: • Best practice documentation • Ideas • Multibeam Horror/Success stories

20. http://mac.unols.org/