Maritime target detection, estimation and classification in Bistatic ultra wideband forward scattering radar

Data mining algorithms are applied on the small volumes of available data from recorded signals of UWB Bistatic maritime FSR system for more precise target classification. The rough estimation (pre-classification) of the length, reflected energy of the target is received from signal records with an original structure of a CFAR processor, for target detection and estimation in the time domains. The scientific results presented in the paper are achieved based on processing real data collected with an FSR maritime system by the researchers from Birmingham University.

[1]  P. Jancovic,et al.  Automatic target classification in a low frequency FSR network , 2008, 2008 European Radar Conference.

[2]  Thomas Reinartz,et al.  CRISP-DM 1.0: Step-by-step data mining guide , 2000 .

[3]  Gaspare Galati,et al.  Advanced Radar Techniques and Systems , 1993 .

[4]  M. Gashinova,et al.  CFAR detection and parameter estimation of moving marine targets using forward scatter radar , 2011, 2011 12th International Radar Symposium (IRS).

[5]  Mikhail Cherniakov,et al.  CFAR BI detector for Mariner targets in time domain for bistatic forward scattering radar , 2011, Symposium on Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments (WILGA).