New solutions to collect hydrographic data with autonomous surface vehicles - QC-203

Preferred Disciplines: Geomatics sciences, geomatic engineering; electrical engineering; hydrography; mathematics (Master's level)
Project length: 8-18 months (2-3 units)
Approx. start date: May 6, 2019
Location: Quebec City, QC
No. of Positions: 1
Preferences: None
Company: CIDCO (Interdisciplinary Centre for the Development of Ocean Mapping)

About Company:

CIDCO is a research centre. Its mission is to modernize hydrography through research, development, training and technology transfer and to enhance its outcomes in a sustainable way thanks to its partnerships and its leading-edge expertise.

Summary of Project:

Even if 71% of the Earth’s surface is water-covered, there are still a lot of unmapped areas (ex. lakes in Canada, arctic regions). A solution to intensify hydrographic data collection consist in using autonomous surface vehicles. However, expertise to conduct hydrographic survey has not yet been transferred to automatic algorithms capable to work in a robust and unsupervised manner. There are many sources of errors when collecting hydrographic data, either systematic or random. Such errors need to be automatically detected onboard the vehicle to make sure the data are compliant with the survey specifications. This is the goal of the research project. 

Research Objectives/Sub-Objectives:

The main objective of this research is to design and develop new methods dedicated to hydrographic errors estimation, automatic calibration of the autonomous surface vehicle, sea-bottom morphology analysis and sedimentology monitoring. This main objective will be structured according to the following specific objectives :

  • Design and development of algorithms to detect systematic errors: build error estimators allowing the detection and assessment of systematic error among multibeam datasets.
  • Design and development of algorithms to detect environmental errors: build error estimators allowing the detection and assessment of positioning errors and sound velocity errors among multibeam datasets.

Methodology:

    The research will consist in studying the impact of sound velocity profils on the bathymetric soundings recorded by the multibeam sonar, and in specifying observability criteria in order to be able to detect sound celerity errors independently of systematic errors.

    • In addition, the research will consist in analysing the impact of the various systematic errors on the hydrographic survey, and in specifying acquisition line patterns dedicated to the survey quality assessment. These line patterns should enhance the observability of each error type independently. Their specification will rely on the overlap geometry of the lines and on the sea-bottom morphology (flat seabed, slope, ….).
    • The student will have the opportunity to do some surveys onboard a hydrographic vessel or using an autonomous survey vehicle. 

    Expertise and Skills Needed:

    • Very good mathematical skills
    • Knowledge and skills in geospatial data and spatial reference systems
    • Good knowledge and skills in programming (ex. C++, Python, Scilab, Matlab)
    • Experience with bathymetric data acquisition and processing is an asset
    • Motivation for metrology or sensor calibration projects
    • Creativity, self-motivation and the ability to solve technical problem
    • Ability to adapt and very good skills toward priority management
    • Good communication skills to technical and non-technical communities, both verbal and writing
    • Ability to work both individually and as a team member

    For more info or to apply to this applied research position, please

    1. Check your eligibility and find more information about open projects.
    2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Benoit Roberge-Vallières

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