One of the central problems in exploiting the radar data is the analysis of a time series. The problem at hand is how to extract the information present in the data and use it to its full potential. Traditionally, radar signals have been analyzed in either the time or the frequency domain. The Fourier Transform is at the heart of a wide range of techniques that are generally used in radar data analysis and processing. However, the change of frequency content with time is one of the main features we generally observe in radar data. Because of this change of frequency content with time, radar signals belong to the class of non-stationary signals. The analysis of non-stationary signals requires technique that extends the notion of a global frequency spectrum to a local frequency description. Joint time-frequency analysis using time-frequency or wavelet transforms has improved the analysis of non-stationary signals by revealing time-varying information embedded in signals.

During the past ten years, time-frequency analysis has been a major area of research in radar signal and image processing. One of the main challenges in radar detection and imaging is the unknown nature of the target�??s motion. The commonly used technique for radar detection and imaging is a Fourier-based approach, which assumes time invariance of the Doppler frequency. However, in real-world radar detection and imaging scenarios, when a target exhibits complex motion such as rotation, acceleration, or maneuvering, standard Fourier-based methods fail to yield more revealing picture of the temporal localization of a signal's spectral components. Radar target signature in the joint time-frequency domain is especially useful for representing time-dependent frequency characteristics that may help for target identification. The ultimate goal of time-frequency approach is not merely to detect or form an image of the target, but also to target identification, especially are cases of non-cooperative targets. The purpose of this special issue is to bring forward recent developments on time-frequency radar signal and image processing methods for detection, focusing images, feature extraction, and demonstrate the usefulness of the time-frequency approach for radar target identification.

There is a close relationship between radar and sonar signal processing using time-frequency analysis and also with other fields such as geological and fault detection processing, among others. Topics of interest include, but are not limited to, the following:


Radar image formation
Radar back-scattering signature analysis
ISAR/SAR motion compensation
Air target detection and imaging
Ocean target detection and imaging
Ground moving target detection and imaging
Landmine detection
Multiple moving targets detection
Feature extraction techniques
Time-frequency based image formation
Parametric and non-parametric methods
Radar target classification methods
Radar micro-Doppler analysis
Radar human gait analysis
Clutter suppression
Radar detection of complex natural resonance frequencies
Comparisons of time domain analysis, frequency domain analysis and joint time- frequency analysis for a specific radar application
Sonar application
Geological and fault detection

Paper Submission �?? All papers must be submitted through the journal�??s Manuscript Central system: http://mc.manuscriptcentral.com/iet-spr . When uploading your paper, please ensure that your manuscript is marked as being for this special issue. Detailed information about IET Research Journals, including an author guide and detailed formatting information is available at: http://www.theiet.org/publications/journals/

Guest Editors
Dr. Thayananthan Thayaparan, Defence R & D Canada
(Thayananthan.Thayaparan@drdc-rddc.gc.ca)
Prof. Ljubisa Stankovic, University of Montenegro
Prof. Moeness Amin, Villanova University, USA
Dr. Victor Chen, Naval Research Laboratory, USA
Prof. Leon Cohen, Hunter College, City University of New York
Prof. Boualem Boashash, University of Sharjah , UAE

IMPORTANT DATES:

Manuscript Due: February 27, 2009
Acceptance Notification: June 26, 2009
Final Manuscript Due: September 25, 2009
Publication Date: 4th Quarter, 2009