Hydrographic Data Processing Past Paper, Winter Semester 24/25

Hydrographic Data Processing Winter Semester 24/25 Ellen Heffner, M.Sc. & Annika L. Walter, M.Sc. Semester schedule Week HDP Topic Date/Time Room DoPaWD Topic 1 / 17...

Hydrographic Data Processing Winter Semester 24/25 Ellen Heffner, M.Sc. & Annika L. Walter, M.Sc. Semester schedule Week HDP Topic Date/Time Room DoPaWD Topic 1 / 17.10. @ 14:15 Introduction, history, basics 2 General & SBES & Sound Velocity 24.10. @ 14:15 3.103 SBES: principles 3 / (holiday) 31.10. MBES: principles 4 Individual Computer Time with Tutor 07.11. @ 12:15 / 5 MBES Processing I & Calibration 14.11. @ 12:15 3.103 / 6 Scientific Writing Seminar 21.11. @ 12:15 3.103 MBES: system configuration 7 / 28.11. / 8 MBES Processing II & Quality Control 05.12. @ 12:15 3.103 Error budget and IHO standards 9 Individual Computer Time 12.12. @ 12:15 Tides and chart datum 10 Product creation 19.12. @ 12:15 3.103 Reference Systems: horizontal / vertical 11 Backscatter Processing 09.01. @ 12:15 3.103 Introduction to other sonars 12 Guest lecture Philippe Wischow from BSH 16.01. @ 12:15 3.103 Survey operation / Navigation / Positioning 13 Individual Computer Time 23.01. @ 12:15 System configuration 14 Guest lecture: Thomas Thies and Frank 30.01. @ 12:15 online Numerical exercise Köster from Hamburg Port Authoriy Hydrographic Data Processing WiSe 24/25 2 Agenda Lecture 2 Multibeam Processing Part I Theory Error budget and TPU MBES calibration Refraction correction Examples of systematic errors Practical Exercise QPS Qimera MBES calibration – Patchtest Refraction correction Hydrographic Data Processing WiSe 24/25 3 Agenda Lecture 2 Multibeam Processing Part I Theory Error budget and TPU MBES calibration Refraction correction Examples of systematic errors Practical Exercise QPS Qimera MBES calibration – Patchtest Refraction correction Hydrographic Data Processing WiSe 24/25 4 Types of Error Influences Gross errors Systematic errors Random errors Large deviation from usual Errors are caused by the Occur randomly and are present measured values measuring system in all observations Deviation from true value in only Detectable during repeated Form an exception one direction, since the causes of measurements Are avoidable in principle the amount / direction act in an Can be partially estimated almost constant way Can be eliminated Cannot be detected during repeated measurements Can be partially corrected Hydrographic Data Processing WiSe 24/25 5 Gross Errors: Examples Wrong decisions of the engineer Instruments Defective devices Faulty GNSS position (e.g. loss of RTK solution) External Noise Propeller noises Interferences with other acoustic systems Reflections in the water column Fish Bubbles Ice Hydrothermal springs Suspended solids Hydrographic Data Processing WiSe 24/25 6 Systematic Errors: Examples Wrong spatial or temporal reference of the individual components / sensors (GNSS, IMU, MBES,..) Offset errors (wrong determination during ship alignment survey) GNSS-Antenna Error in calibration (wrong correction angles MBES for roll, pitch and heading) Latency error Pitch / (Roll) Roll, Pitch, Heave Error due to ship movement Wave motion IMU Refraction error Wrong sound velocity profile Transducer depth Environmental conditions wind, waves, current Footprint Bottom surface [Hypack] Hydrographic Data Processing WiSe 24/25 7 Random Errors: Examples Echoes from side lobes Omega Effect Tunnel Effect Interferences Slope inclination error Reflections On quay walls and sheet pile walls Multiple reflected signals... [IHO, 2005] Hydrographic Data Processing WiSe 24/25 8 Error Influences and Estimation Total Propagated Uncertainty (TPU) Error Influences TPU Gross errors Measure for the accuracy to be Instruments expected of a measured point including all systematic and random Wrong decisions of the engineer errors External noise Reflections in the water column TPU value results from the Systematic errors combination of all contributing Total uncertainties Incorrect spatial / temporal reference of the individual components / sensors Propagated Error (TPE) Error due to ship movement TPU can be statistically computed Refraction error using the law of uncertainty propagation Environmental conditions Random errors Echoes from side lobes Reflections,... Hydrographic Data Processing WiSe 24/25 9 Total Propagated Uncertainty (TPU) GPS Antenna, x, y = ± 2 cm, z = ± 3 cm The TPU Constant Error Total Propagated Uncertainty MBE Transducer, x, y = ± 5 cm, z = ± 6 cm Depth Dependant Error Sounding Outer Beam, x, y = ± 9 cm, z = ± 13 cm Center Beam, x, y = ± 7 cm, z = ± 8 cm Outer Beam, x, y = ± 9 cm, z = ± 13 cm Hydrographic Data Processing WiSe 24/25 10 Total Propagated Uncertainty (TPU) in CARIS HIPS and SIPS Hydrographic Data Processing WiSe 24/25 11 IHO Standards International Hydrographic Organization (IHO) Sets international standards S-4: Regulations for International Charts.. ”to specify minimum standards for hydrographic S-44: Hydrographic Surveys surveys in order that hydrographic data collected S-57: Digital Hydrographic Data according to these standards is sufficiently accurate and that the spatial uncertainty of data is adequately quantified to be safely used by mariners as primary users of this information”. Hydrographic Data Processing WiSe 24/25 12 IHO Standards International Hydrographic Organization (IHO) Intergovernmental organization representing hydrography Comprises 99 member states Aim is to ensure that worlds waters are surveyed and charted Coordinates endeavours of the world’s hydrographic offices Sets international standards S-4: Regulations for International Charts.. S-44: Hydrographic Surveys S-57: Digital Hydrographic Data Green = Member States; Yellow = Other Coastal States; Gray = Other Landlocked States (2024) Hydrographic Data Processing WiSe 24/25 13 IHO Standard S-44 IHO Standards for Hydrographic Surveys (Edition 6.1.0, September 2022) Used to compile navigational charts Specifies minimum standards Definition of five different orders of survey Order 2 Order 1b Order 1a Special Order Exclusive Order General depiction General depiction Adequate Accurate Minimum of the bottom of the bottom depiction of the depiction of the underkeel Depth > 200 m Underkeel bottom bottom clearance and clearance not an Underkeel Underkeel bottom issue clearance not clearance is critical characteristics are critical Harbours, potentially Coastal waters, berthing areas, hazardous fairways, channels critical areas of Restricted to fairways and shallow waters shipping channels [IHO, 2022] Hydrographic Data Processing WiSe 24/25 14 IHO S-44 Minimum Bathymetry Standards TVUmax(d) = 𝑎𝑎2 + (𝑏𝑏 𝑥𝑥 𝑑𝑑)² Where: a: represents depth independent coefficient b: represents depth dependent coefficient d: is the depth [IHO, 2022] Hydrographic Data Processing WiSe 24/25 15 Accuracy of Hydrographic Measurements Example of a measurement with a single beam echosounder IHO S-44: Minimum depth accuracy requirements 1st order z: water depth related to chart datum zc: Water sound velocity zt: Time i: Distance of transducer to the waterline (immersion depth, settlement, squat) h: Heave r: Reading accuracy [IHO, 2005] tide: Tide Hydrographic Data Processing WiSe 24/25 16 Error Influences and Correction Error Influences Error Correction Gross errors Are eliminateable! Instruments Reduction through: training, cautious handling Wrong decisions of the engineer External noise Reflections in the water column Systematic errors Are eliminateable! Incorrect spatial/temporal reference of the individual Reduction through: filters & field calibration components/sensors Multibeam echo sounder installation: patch test Error due to ship movement Sound velocity: SVP and CTD profiles, Refraction Correction Refraction error Controls at known depths (e.g. floodgates) Environmental conditions Random errors Are not eliminateable! Echoes from side lobes Reduction through: Repetition reflections,... Hydrographic Data Processing WiSe 24/25 17 Agenda Lecture 2 Multibeam Processing Part I Theory Error budget and TPU MBES calibration Refraction correction Examples of systematic errors Practical Exercise QPS Qimera MBES calibration – Patchtest Refraction correction Hydrographic Data Processing WiSe 24/25 18 Multibeam Echosounder Installation Initial alignment / Static offsets As a base for the initial measurement the definition / the realization of the vessel coordinate system within the survey vessel has to be found The COG (Center of Gravity), a reference point in the vessel that is typically the center of gravity or the intersection of the pitch and roll axis should be the origin of the vessel coordinate system In most cases the COG of the vessel isn‘t known precisely, but the position of COG can be estimated for example to be in the centerline and in the middle of the vessel with a height close to the waterline height Hydrographic Data Processing WiSe 24/25 19 Multibeam Echosounder Installation Initial alignment / Static offsets Each geodetic / hydrographic sensor has its own center of measurement and an individual coordinate system with individual axis and rotation definitions The sensors center of measurement and the sensor coordinate definition can be found in the manufacturer’s schematic drawings of the sensor Acoustic reference point of the multibeam echosounder Teledyne Reson Seabat 7125 SV2 [RESON, 2012] Hydrographic Data Processing WiSe 24/25 20 Multibeam Echosounder Installation Initial alignment / Static offsets Each geodetic / hydrographic sensor has its own center of measurement and an individual coordinate system with individual axis and rotation definitions The sensors center of measurement and the sensor coordinate definition can be found in the manufacturer’s schematic drawings of the sensor Center of measurement (excentric / off center) of the INS IXBLUE PHINS [IXBLUE, 2010] Hydrographic Data Processing WiSe 24/25 21 Multibeam Echosounder Installation Initial alignment / Static offsets The initial measurement determines the offsets in x,y,z direction and the angular misalignments between the vessel coordinate system and the certain sensor coordinates systems with high accuracy In most cases where the initial measurement is carried out with the vessel on a slipway in a static configuration, a local geodetic network around and in the vessel is created to measure all sensors with high end total stations from different reference positions The sensor coordinates in the local reference system were transformed into the vessel coordinate system Hydrographic Data Processing WiSe 24/25 22 Multibeam Calibration: Patch Test To determine the: 1. Latency of the echo sounder and positioning system Today negligible because of PPS signal To determine the residual angular offsets (pitch, heading, roll) of transducer and motion sensor 2. Pitch: rotation around the ship's transverse axis 3. Heading / yaw: rotation around vertical axis 4. Roll: rotation around the longitudinal axis of the ship (Attention: same description as for ship movement!) To determine the: 5. transducer draught A patch test should be performed: After installation of the transducer After a longer standing time [calqlata.com] Changes in the installation Hydrographic Data Processing WiSe 24/25 23 Patch Test: Latency δt [IHO, 2005] Hydrographic Data Processing WiSe 24/25 24  Patch Test: Latency δt Time difference between depth measurement and position determination Is minimized nowadays by the use of PPS signals (pulse per second) Latency calibration hardly necessary anymore LED PPS USB RXD Output 1 Second TXD NEO-7M GND VCC power PPS Electrical signal that repeats precisely once per second Output by GNSS receivers Used for precise timekeeping as it defines the start of the second (not time itself!) Hydrographic Data Processing WiSe 24/25 25 Patch Test: Pitch δθP [IHO, 2005] Hydrographic Data Processing WiSe 24/25 26 Patch Test: Pitch δθP [R2Sonic, 2009] Hydrographic Data Processing WiSe 24/25 27 Patch Test: Pitch δθP Before: After: vs. Hydrographic Data Processing WiSe 24/25 28 Patch Test: Heading (AzimuthalOffset) δα [IHO, 2005] Hydrographic Data Processing WiSe 24/25 29 Patch Test: Heading (AzimuthalOffset) δα [R2Sonic, 2009] Hydrographic Data Processing WiSe 24/25 30 Patch Test: Roll δϴR [IHO, 2005] Hydrographic Data Processing WiSe 24/25 31 Patch Test: Roll δϴR Hydrographic Data Processing WiSe 24/25 32 Patch Test: Roll δϴR Before: After: vs. Hydrographic Data Processing WiSe 24/25 33 Patch Test: Processing Pitch Roll Heading On a slope Flat Bathymetry Object or slope Hydrographie 2 34 [NOAA, 2010] = Section for viewing the data Hydrographic Data Processing WiSe 24/25 34 PatchTest: Boresight Calibration Boresight calibration (Data selection algorithm & adjustment) [Seube & Keyetieu, 2017] Hydrographic Data Processing WiSe 24/25 36 PatchTest: Boresight Calibration Boresight calibration (Data selection algorithm & adjustment) Advantages: Less profiles: 4 (single-head) or 5 (dual-head) All three position angle corrections are determined together Statistical analysis of the results [CARIS] Hydrographic Data Processing WiSe 24/25 37 PatchTest: Boresight Calibration Boresight calibration (Data selection algorithm & adjustment) Processing: 1. Raw data are georeferenced 2. Division of the area into small, differently sized areas (=patches) Depending on data density, uniformity, flatness 3. Evaluation of the patches according to pitch, roll, yaw 4. Calculation of correction angles for pitch, roll, yaw Based on least squares method [CARIS] Literature: Seube, N., Levilly, S., de Jong, K. (2016): Automatic Estimation of Boresigth Anlges Between IMU and Multi-beam Echo Sounder Systems. B. Zerr et al. (Hrsg.), Quantitative Monitoring of Underwater Environment, Ocean Engineering & Oceanography 6, DOI:10.1007/978-3-319-32107-3_1 Hydrographic Data Processing WiSe 24/25 38 PatchTest: MBES Transducer Draught A well known reference surface is needed to compare measured depths with reference depths a sill of a lock gate, a sill of a flood barrier, a floating dock etc. Before all previously determined offsets (Roll, Pitch, Yaw, Navigation Latency) need to be applied The 3D point clouds of the survey lines covering the reference surface can be geometrically and statistically compared against the reference surface With the aid of a 3D difference model the height / depth offset of the transducer can be computed and applied in the vessel configuration Hydrographic Data Processing WiSe 24/25 39 Agenda Lecture 2 Multibeam Processing Part I Theory Error budget and TPU MBES calibration Refraction correction Examples of systematic errors Practical Exercise QPS Qimera MBES calibration – Patchtest Refraction correction Hydrographic Data Processing WiSe 24/25 40 Refraction [R2Sonic] Hydrographic Data Processing WiSe 24/25 41  Refraction Snellius Law of refraction sin 𝜃𝜃𝜃 𝑐𝑐𝑐 = sin 𝜃𝜃𝜃 𝑐𝑐𝑐 [Physics Stack Exchange] Hydrographic Data Processing WiSe 24/25 42 Refraction Correction Methods during data acquisition for determining sound velocity profiles SVP CTD Methods during data processing for correcting refraction errors Refraction Editor Manual Implemented in Teledyne Caris HIPS & SIPS Sound Speed Profile inversion algorithm (TU Delft) Automatic Implemented in QPS Qimera [QPS, 2016] Hydrographic Data Processing WiSe 24/25 43 Refraction Correction Refraction Editor in Teledyne Caris HIPS & SIPS Through altering the SVP a better refraction solution will be derived Sound velocity corrections at user defined depths Hydrographic Data Processing WiSe 24/25 44 Refraction Correction Sound Speed Profile inversion algorithm (TU Delft) takes advantage of the overlap between survey lines Algorithm estimates sound speed corrections for chosen pings and their neighbours by computing best-fit solution that minimizes the mismatch in the areas of overlap between lines Process completely automated E: Energy function C: number of grid cells in the segment considered Bc,n: number of soundings in a cell (c), for the given track (n). zc,n,b: depth of a sounding for the given cell, track and beam (b) zc: weighted mean of zc,n,b with the weight function being the inverse cubed horizontal distance between the sounding and cell center. x contains N unknown sound speeds for the segment under consideration [Beaudoin et al. 2018] Hydrographic Data Processing WiSe 24/25 45 Refraction Correction Sound Speed Profile inversion algorithm (TU Delft) [Beaudoin et al. 2018] Hydrographic Data Processing WiSe 24/25 46 Agenda Lecture 2 Multibeam Processing Part I Theory Error budget and TPU MBES calibration Refraction correction Examples of systematic errors Practical Exercise QPS Qimera MBES calibration – Patchtest Refraction correction Hydrographic Data Processing WiSe 24/25 47 Example of Systematic Error Frownies [QPS] Hydrographic Data Processing WiSe 24/25 48 Example of Systematic Error Smilies [QPS] Hydrographic Data Processing WiSe 24/25 49 Example of Systematic Error Example: Incorrect synchronization/calibration of depth measurements and motion sensor data  Roll artefacts  Pitch artefacts Hydrographic Data Processing WiSe 24/25 50 Example of Systematic Error Example: Incorrect synchronization/calibration of depth measurements and motion sensor data  Roll artefacts [QPS] [pubs.usgs.gov] Hydrographic Data Processing WiSe 24/25 51 Example of Systematic Error Example: Incorrect synchronisation/ After Patch test Measurement of depth measurements and motion sensor data  Heading artefact  Pitch artefact Hydrographic Data Processing WiSe 24/25 52 Agenda Lecture 2 Multibeam Processing Part I Theory Error budget and TPU MBES calibration Refraction correction Examples of systematic errors Practical Exercise QPS Qimera MBES calibration – Patchtest Refraction correction Hydrographic Data Processing WiSe 24/25 53 References Beaudoin, J., Renoud, W., Haji Mohammadloo, T., & Snellen, M. (2018): Automated Correction of Refraction Residuals. Retrieved from http://pure.tudelft.nl/ws/portalfiles/portal/47701861/Beaudoin_et_al._Automated_Correction_of_Refraction_Resid uals.pdf, last accessed 10.11.2024. International Hydrographic Organization. (2005): Manual on Hydrography. Monaco: International Hydrographic Bureau. Retrieved from https://iho.int/uploads/user/pubs/cb/c-13/english/C-13_Chapter_1_and_contents.pdf, last accessed 10.11.2024. International Hydrographic Organization. (2022): S-44 Edition 6.1.0. Monaco: International Hydrographic Bureau. Retrieved from https://iho.int/uploads/user/Services%20and%20Standards/HSSC/HSSC14/S- 44_Edition_6.1.0_Proposed_20220328.pdf, last accessed 10.11.2024. R2Sonic. (n.d.): Training. Retrieved from https://www.r2sonic.com/resources/training/, last accessed 01.04.2020. Seube, N., & Keyetieu, R. (2017). Multibeam Echo Sounders-IMU Automatic Boresight Calibration on Natural Surfaces. Marine Geodesy, 40(2–3), 172–186. https://doi.org/10.1080/01490419.2017.1310156 Seube, N., Levilly, S., de Jong, K. (2016): Automatic Estimation of Boresigth Anlges Between IMU and Multi-beam Echo Sounder Systems. B. Zerr et al. (Hrsg.), Quantitative Monitoring of Underwater Environment, Ocean Engineering & Oceanography 6, DOI:10.1007/978-3-319-32107-3_1 Teledyne CARIS. (n.d.): Retrieved from https://www.teledynecaris.com/en/products/abc/, last accessed 13.10.2024. Hydrographic Data Processing WiSe 24/25 54  Thank you Ellen Heffner [email protected] HafenCity Universität Hamburg Henning-Voscherau-Platz 1 20457 Hamburg