Ph.D. student at the University of Tromsø, Department of Physics and Technology, Electronic Engineering Group. Research interests include statistical signal processing, pattern recognition and image processing applied to remote sensing and earth observation data. My research project concerns information extraction from polarimetric synthetic aperture radar (POLSAR) images. I am also a member of the Computational Earth Observation and Machine Learning Laboratory.

The working title of my Ph.D. project is "Information extraction from polarimetric SAR data". The goal is to use advanced methods from statistical signal processing and pattern recognition to extract more accurate thematic and geophysical information from full-polarimetric SAR images. Problems under study include:

• Statistical modelling
• Automatic clustering, classification and segmentation
• Noise filtering
• Retrieval of geophysical and biological parameters

Supervisors are Professor Torbjørn Eltoft, University of Tromsø and Dr. Harald Johnsen, Norut IT. Parts of the Ph.D. program period will be spent at the University of Genova, Biophysical and Electronic Engineering Department, working as a guest researcher in collaboration with Professor Sebastiano Serpico and the Image Processing and Pattern Recognition for Remote Sensing research group.

Synthetic aperture radar (SAR) is a form of radar in which sophisticated post-processing of radar data is used to produce a very narrow effective beam. It is used by moving instruments over relatively immobile targets, and has seen wide applications in remote sensing and mapping.

In a typical SAR application, a single radar antenna is attached to the side of an air- or spacecraft. A single pulse from the antenna will be rather broad (several degrees) because diffraction requires a large antenna to produce a narrow beam. The pulse will also be broad in the vertical direction; often it will illuminate the terrain from directly beneath the aircraft out to the horizon. However, if the terrain is approximately flat, the time at which echoes return allows points at different distances from the flight track to be distinguished. Distinguishing points along the track of the aircraft is difficult with a small antenna. However, if the amplitude and phase of the signal returning from a given piece of ground are recorded, and if the aircraft emits a series of pulses as it travels, then the results from these pulses can be combined. Effectively, the series of observations can be combined just as if they had all been made simultaneously from a very large antenna; this process creates a synthetic aperture much larger than the length of the antenna (and in fact much longer than the aircraft itself).

Combining the series of observations requires significant computational resources. It is normally done at a ground station after the observation is complete, using Fourier transform techniques. The result is a map of radar reflectivity (including both amplitude and phase), which contains information about ground cover. (Source: Wikipedia)

Some good tutorials and text books on SAR:

• Radar Remote Sensing - A comprehensive and unique set of radar remote sensing training materials suitable for use at the undergraduate and graduate levels. Canadian Centre of Remote Sensing (Downloadable pdf files).
• Fundamentals of Remote Sensing - An interactive module intended as an overview to remote sensing at a senior high school or early university level and touches on physics, environmental sciences, mathematics, computer sciences and geography. Canadian Centre of Remote Sensing (Downloadable pdf files).
• Soumekh, M. (1999), "Synthetic Aperture Radar Signal Processing", John Wiley, 616 pp.
• Franceschetti, G. and R. Lanari (1999), "Synthetic Aperture Radar Processing", John Wiley, 307 pp.
• Oliver, C. and S. Quegan (2004), "Understanding Synthetic Aperture Radar Images", SciTech Publishing, 429 pp.

Polarization is a property of radio waves (or other electromagnetic waves) describing the alignment or spatial orientation of the oscillating electric field. Different materials reflect radar waves with different intensities, but for anisotropic materials such as natural ground covers, reflectivity also depends on polarization. Some materials will also convert one polarization into another. By emitting a mixture of polarizations and using receiving antennas that each capture a specific polarization, several different images can be collected from the same series of pulses. (Source: Wikipedia)

In radar polarimetry, measurements obtained with different combinations of polarizations at the transmitter and receiver are used to characterize the ground scenes illuminated by the radar. Applications include classification, object detection and retrieval of biological and physical parameters.

Some good tutorials and text books on radar polarimetry:

• Radar Polarimetry - An introduction to the principles, technology and practical applications of radar polarimetry. Canadian Centre of Remote Sensing. (Online tutorial)
• Polarimetry Tutorial - A wide-ranging tutorial, which aims to provide a grounding in polarimetry and polarimetric interferometry with a view to stimulating research and development of scientific applications that exploit polarimetric data and techniques. European Space Agency (Downloadable pdf files)
• Ulaby F.T. and Elachi C. (1990), "Radar polarimetry for geoscience applications", Artech House, 364 pp.

Some freely available software packages for processing of SAR data:

• PolSarPro - Polarimetric SAR Data Processing and Educational Tool. (European Space Agency).
• Radar Tools - An IDL-based collection of tools for processing SAR data, packed together in a nice graphical user interface. (Berlin University of Technology)
• Radarworks - Matlab and C Radar Toolbox for processing, simulation and analysis of signal and image data. Especially useful for polarimetric radar. (Glen Davidson)

• Anfinsen S.N. and Rasmussen G.L. (2002), "Cloud detection in AVHRR images using neuro-fuzzy data fusion", Proc. of Eumetsat Meteorologic Satellite Conference, Dublin, Ireland, September 2002, pp. 207-214.
• Sivertsen, A.H., Eltoft, T. and Anfinsen S.N. (2002), "Evaluation of textural features for automatic cloud detection in AVHRR images", Proc. of Eumetsat Meteorologic Satellite Conference, Dublin, Ireland, September 2002, pp. 346-353.
• Anfinsen, S.N. (2000), "A Detection Theoretical Approach to Digital Communications Using Autoregressive Process Shift Keying", M.Sc. thesis, Physics Department, University of Tromsø, March 2000.
• Anfinsen S.N. and Nandi A.K., "Recursive filter structure for blind equalisation", Proc. of ICCCD-2000, Eds. Maskara S.L. and Lamba T.S., Allied Publishing Ltd, New Delhi, India, Vol. II, 2000, pp. 595-598.
• Nandi A.K. and Anfinsen S.N. (2000), "Blind equalisation with recursive filter structures", Signal Processing, Vol. 80, No. 10, 2000, pp. 2151-2167.
• Anfinsen S.N., Herrmann F. and Nandi A.K. (1999), "Blind Channel Equalisation", in Blind Estimation Using Higher-Order Statistics, Nandi A.K. (ed.), Kluwer Academic Publishers.
• Anfinsen, S.N. (1998), "Blind Equalisation Using Recursive Filter Structures", M.Sc. thesis, Dept. of Electrical and Electronic Engineering, University of Strathclyde, September 1998.

Courses studied as Ph.D. student:

• Multivariable Statistical Analysis (Autumn 2005)
• Non-Parametric Inference (Autumn 2005)
• Computer-Intensive Statistics (Spring 2006)
• Research Seminar (Spring 2006)

Courses taught as research assistant:

• Basic Physics (Autumn 2005)
• Detection Theory (Spring 2006)