Title :
Vessel identification study for non-coherent high-resolution radar
Author :
Carmona-Duarte, Cristina ; Ferrer-Ballester, Miguel Angel ; Calvo-Gallego, Jaime ; Dorta-Naranjo, B. Pablo
Author_Institution :
Inst. Univ. para el Desarrollo Tecnol. y la Innovacion en Comun., Univ. of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
Abstract :
This paper presents a vessel identification study based on vessel profile. The study was developed with real data obtained with high-resolution Continuous Wave Lineal Frequency Modulated (CW-LFM) radar. Cases studied in this work are vessels entering and leaving the harbor. Also, in this paper, a comparison between different classification techniques such as Neural Networks, Support Vector Machine and k-Nearest Neighbor is introduced. The differences between normalization methods are evaluated for each classification technique.
Keywords :
CW radar; FM radar; neural nets; radar computing; radar signal processing; signal classification; support vector machines; CW-LFM radar; classification technique; high-resolution continuous wave lineal frequency modulated radar; k-nearest neighbor; neural networks; noncoherent high-resolution radar; normalization methods; support vector machine; vessel identification study; vessel profile; Doppler radar; Error analysis; Frequency modulation; Radar imaging; Support vector machines; Training; high-resolution radar; target identification;
Conference_Titel :
Security Technology (ICCST), 2013 47th International Carnahan Conference on
Conference_Location :
Medellin
DOI :
10.1109/CCST.2013.6922052
