Course Catalogue

Signal Detection and Estimation (UESTC) UESTC5023

  • Academic Session: 2026-27
  • School: School of Engineering
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

This course introduces fundamental concepts and techniques of detection and estimation and their applications in communications and radar systems. Topics include signal detection in white/coloured Gaussian noise, nonparametric detection, and parameter estimation.

Timetable

40 hours of lectures

Requirements of Entry

None

Excluded Courses

None

Co-requisites

None

Assessment

Final exam 80%

Homework assignments and in-class participation 20%

Main Assessment In: December

Course Aims

This course aims to develop in students a good understanding of both the theory and methods of signal detection and estimation and be able to apply these methods to solve related theoretical and practical problems.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. Explain fundamental concepts of stochastic processes, and representations of narrow band signals and noise sources;

2. Compare criteria for signal detection (including Bayes, Minimax, Neyman-Pearson, etc.) for practical applications, including in the presence of Gaussian noise and for signals with random parameters;

3. Perform parameter estimation on realistic datasets, for amplitude, phae, time and frequency, including in the presence of additive Gaussian noise; 

4. Evaluate optimal signal detection and estimation techniques for a variety of real world examples, and apply those technique in practice.

Minimum Requirement for Award of Credits

No exceptions