MSc thesis project proposal

Classification of targets using the polarimetric-Doppler PARSAX radar

In many practical applications it is of interest to classify observed objects of interest, also called targets, using features that are measured via a sensor. A typical example is the classification of ships using radar measurements. The measured features are compared to features of targets from a database and a decision is made about the class of the observed target.

The MS3 group has developed a reconfigurable radar, PARSAX, that can observe ships and aircrafts using different sensing modes dynamically. The group is interested in advancing the state of the art in automatic target classification by exploiting sensor management algorithms for selecting the best sensing parameters for observing and classifying targets. For more information on PARSAX radar visit the project's page

When classification of targets is of interest, it is possible to compare the measured features to features reported via automated systems such as the Automatic Identification System (AIS) for ships and the Automatic Dependent Surveillance-Broadcast (ADS-B) system for aircrafts. See for example the image taken from www.marinetraffic.com .

Assignment

Important aspects of this project are:

  • A literature survey on target classification that describes classification algorithms, target features that can be used and how these features are related to radar parameters that can be controlled;
  • An interface between MATLAB and a website with AIS data or an ADS-B receiver in order to automatically import relevant information about features of the observed targets to MATLAB;
  • Implementation of the most promising classification algorithm.
  • (optional) Experimental verification of the proposed algorithm.

Requirements

A good background in probability theory, statistics, microwaves, antennas, and MATLAB is important.

Contact

dr. Oleg Krasnov

Microwave Sensing, Signals and Systems Group

Department of Microelectronics

Last modified: 2020-09-23