Clutter and Detection in Clutter (2015)

EEE 5110Z (2015) Clutter and Detection in Clutter - Class photo
EEE 5110Z (2015) Clutter and Detection in Clutter – Class photo



Course Information

Dates: 29 June to 3 July 2015

Course code: EEE5110Z

Venue: John Martin Room, 6th Floor, Menzies Building (Upper Campus), University of Cape Town


Course Description

Course Handout: High Frequency Radar 2015
Download Course Handout: Clutter & Detection in Clutter 2015

The course is organized in three parts:

  1. Radar clutter modelling and analysis
  2. Optimum and adaptive radar detection of targets in Gaussian clutter
  3. Optimum and adaptive radar detection of targets in heavy-tailed non-Gaussian clutter

Having successfully completed this course, students should:

  • understand the coherent radar array data model and its statistical analysis;
  • understand the optimal and adaptive coherent detection of radar targets problem;
  • know the techniques and algorithms that are currently used and choose which ones are the most suitable for a given scenario;
  • understand the significance of disturbance modelling and analysis in a radar system;
  • be able to analyze real clutter data;
  • be able to generate synthetic data for radar system performance simulation
  • be able to implement algorithms for radar target detection
  • be able to analyze radar detection algorithm performance by the Monte Carlo method;
  • be able to understand how the target signal model affects the structure of the detectors and its performance.


Course Overview

The following topics are covered:

  • HF radar history and capabilities, Theory, history and planned expansion, future directions (4 hours)
  • HF radar hardware, Transmitter, receiver, antenna (4 hours)
  • HF Radar case studies (6 hours)
  • HF radar installation checklists and procedures (2 hours)
  • Site selection and identifying man-made objects that would impact system performance (4 hours)
  • HF radar software (4 hours)
  • Data telemetry (4 hours)
  • Introduction to National and Global HF radar Network and (4 hours)
  • Data visualization (8 hours)



Maria GrecoProf Maria Greco has been an Associate Professor in the Department of Ingegneria dell’Informazione at the University of Pisa, Italy, since 2011.

Her general interests are in the areas of statistical signal processing, estimation and detection theory. In particular, her research interests include clutter models, spectral analysis, coherent and incoherent detection in non-Gaussian clutter, CFAR techniques, radar waveform diversity and bistatic/multistatic radars.



Prof Fulvio GiniProf Fulvio Gini has been a Full Professor in the Department of Ingegneria dell’Informazione of the University of Pisa since 2006.

His research interests include modeling and statistical analysis of radar clutter data, non-Gaussian signal detection and estimation, parameter estimation and data extraction from multichannel interferometric SAR data.