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Module

CEG2703 : Observation Processing and Analysis

  • Offered for Year: 2020/21
  • Module Leader(s): Dr Ciprian Spatar
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0

Aims

The module aims to develop the essential mathematical skills for understanding and undertaking observation processing and analysis. Students will be provided with an in-depth understanding of the reasons for inaccuracy in survey measurements and shown how to achieve and guarantee survey results adequate for their purpose by processes of pre-analysis, estimation and post-analysis. Knowledge of the basic concepts will be related to the computation of 1D, 2D and 3D survey control schemes but the universality of methods for the handling of measurement data will be emphasised with several case studies.

Outline Of Syllabus

Maths for observation processing (linearisation using Taylor series, partial differentiation, matrix algebra); measurement errors and their propagation; least squares using observation equations; network analysis; covariance analysis; pre- and post-adjustment analysis.

Teaching Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture180:206:00Synchronous online lectures.
Structured Guided LearningLecture materials180:309:00Reading and understanding of lecture notes.
Guided Independent StudyAssessment preparation and completion35:0015:00Report writing and submission
Scheduled Learning And Teaching ActivitiesPractical33:009:00Computer-based practical sessions delivered in person (6 hours) and online (3 hours)
Guided Independent StudyIndependent study156:3056:30Includes background reading and revision of lecture materials
Scheduled Learning And Teaching ActivitiesScheduled on-line contact time90:304:30Weekly online drop-in Q&A sessions.
Total100:00
Teaching Rationale And Relationship

Early lectures introduce essential mathematical concepts for the statistical analysis of measurement data. Later lectures discuss least squares estimation and post-analysis. The theoretical concepts presented in lectures are demonstrated through case studies. Practical sessions allow students to apply the underlying theory with the aid of both a spreadsheet application and a specialised software package. Extensive time is allocated to independent study, which includes background reading and exam preparation.
Alternatives will be offered to students unable to be present-in-person due to the prevailing C-19 circumstances.
Student’s should consult their individual timetable for up-to-date delivery information.

Assessment Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Practical/lab report1M100Least Squares Computations
Assessment Rationale And Relationship

Assessment exercises assesses students' computational accuracy and presentation of detailed computations.

Reading Lists

Timetable