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Ph.D. Level Courses

Advanced Topics in Detection and Estimation Theory


This course will treat selected advanced topics in estimation and detection theory. For an outline of specific topics that we plan to cover, see below.


Prof. Prof. Erik G. Larsson, ISY/Communication Systems, and Dr. <Unknown username: saif>, ISY/Communication Systems


The course is open to students enrolled in a Ph.D. program at Linkoping University/ISY. External participants upon request. If you have interest to participate, please register by sending an email to erik.larsson@isy.liu.se, by March 1, 2011.


Good knowledge of linear algebra and probability theory. General mathematical maturity. Knowledge of basic discrete-time detection/estimation theory (Chapter 2 in van Trees book, or equivalent) taught for example in our first detection/estimation course.

Tentative course outline

  • Nonlinear estimation:
    • Array signal processing
    • Cramer-Rao bounds under constraints
    • Other performance bounds
    • Conditional and unconditional Maximum-Likelihood (a.k.a. deterministic and stochastic ML) techniques, concentrated ML
    • Techniques for asymptotic analysis of estimators
  • Detection
    • Model order selection, detection of number of sources
    • Asymptotic analysis of detection algorithms
  • Basic spectral estimation
    • Periodograms and weighted periodograms
    • Basic parametric models and methods
  • Direction-of-arrival and time-of-arrival estimation algorithms
  • Source localization/positioning systems
  • Detection of weak signals and signals with structure

Schedule and reading

Useful reference books

  • H. van Trees, "Detection, estimation and modulation theory: volume I", Wiley.
  • H. van Trees, "Detection, estimation and modulation theory: volume IV (optimum array processing)", Wiley.
  • S. Kay, "Fundamentals of statistical signal processing: parts I and II", Prentice-Hall.
  • P. Stoica and R. Moses, "Spectral analysis of signals," Prentice-Hall.

Credits and Examination

The course can give 5 ECTS.

  • The focus is on depth reading, presentation and discussion of research papers.
  • Participants taking the course for credit are expected to participate actively in all seminars and discussions.

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Last updated: 2019 07 29   15:48