1. Multibeam echosounders: error modeling evolution Multibeam sonar workshop, 3-4 April 2005 St. Andrews, NB Rob Hare, P. Eng., C.L.S. Canadian Hydrographic Service

2. 1994 - First USCHC multibeam course (Top Gun Hydro team) Professional Paper No. 25 – single-beam echosounder error budgets (1990) S-44 Edition 3 still in effect –Work on 4 th edition begun Multibeam error modelling in development (Hare, Godin, Mayer) –Pøhner model for Simrad MB (EM100, EM1000) - 1993 –Empirical models for Elac, Reson (RAN Hydro project) –EXCEL spreadsheets (pre-analysis) Random errors only

3. 1995 Hammerstad error model for all EM –Firmer theoretical footing for amplitude detection Canadian MB accuracy estimation report (Hare, Godin, Mayer) –Sweep and Swath Dinn et al. paper on effects of surface sound speed –Effect of transducer design, installation, roll

4. 1998 Fourth edition of S-44 released –95% confidence level chosen –Multiple orders of survey –Total bottom coverage requirement –Target detection requirement –Mandatory accuracy attribution of soundings

5. More refinements 1998 - Rijkswaterstaat (de Koning) develops MEET –Addition of systematic errors –Slick interface –Still just preanalysis spreadsheet 1999 - NAVO (Reed et al.) applies models to real data (post-mission) –Modified GSF to store accuracy attributes

6. Shallow-water Interferometric sidescan systems gaining prominence –Improved coverage, target detection –Ability to map geology and habitat up to shoreline 2000 - Lurton analyses phase detection measurement precision

7. 2001 NCOEH formed at USM –Assessment of NAVO hydrographic survey systems (Simrad, Reson) –Consideration of lidar (SHOALS) errors, but no model NAVO implementing error estimation in real-time –Part of RTQA software Lurton considers effects of S/N on four MB error models (English treatment, 2003 International Hydrographic Review)

8. Putting those error estimates to good use NAVO depth and position error maps –Assessment of individual soundings –Colour coding attributes –Real-time assessment of sounding quality Using logged parameters Development of CUBE –Attributed soundings as a means to an end –Automated post-processing –Statistical analysis of incoming soundings –Rejection of ambiguous depth hypotheses –Identification and iterative rejection of systematic biases

9. Future prospects 2005 - 2015 Error model for lidar –USM/Guenther examining? Real-time data cleaning and QC –CUBE in SIS (CHS) –CUBE in QINSy? –NOAA/UNH developments? –Hypack?? More realistic sound speed error models? Application of Reliability Theory? Fine tuning error models on-the-fly?

10. More future prospects Implementation of 4 Lurton models –including S/N components for phase measurement Better removal of systematic errors, cyclical errors (Hughes Clarke) Error (or quality) visualization –For hydrographers –For end-users

11. Training 2005 - 2015 Understanding error modeling –TPE (HIPS 5.4) –CUBE For SIS (real-time) For HIPS 6.0 (post-mission) Uncertainty management –Identifying blunders, systematic errors, random error contributions –Preanalysis –Real-time QA –Post-mission assessment Metadata – S-57, FGDC, ISO 19115, BAG format?? Certification of data sets (uncertainty, reliability, completeness?) Standards?