Title :
A comparison of 1D and 2D algorithms for radar target classification
Author :
Novak, Leslie M.
Author_Institution :
MIT Lincoln Lab., Lexington, MA, USA
Abstract :
The use of high-resolution radar measurement data (35 GHz) from four ground vehicles (bulldozer, Dodge Power Wagon, Dodge Van, and Camaro) to evaluate the performance of several 1D and 2D classifiers is discussed. The 1D classifiers use high-resolution range profiles to classify targets; the 2D classifier uses high-resolution inverse synthetic aperture radar (ISAR) images to classify targets. Classification performance results using the 1D and 2D algorithms are presented, and it is shown that the 2D algorithm performed best.<>
Keywords :
pattern recognition; picture processing; radar applications; 1D algorithm; 1D classifiers; 2D algorithm; 2D classifiers; 35 GHz; Camaro; Dodge Power Wagon; Dodge Van; EHF; ISAR images; bulldozer; classification performance; ground vehicles; high-resolution inverse synthetic aperture radar; high-resolution range profiles; image processing; radar measurement data; radar target classification; Image processing; Pattern recognition; Radar applications;
Conference_Titel :
Systems Engineering, 1991., IEEE International Conference on
Conference_Location :
Dayton, OH, USA
Print_ISBN :
0-7803-0173-0
DOI :
10.1109/ICSYSE.1991.161069