Machine-learning for classification of naval targets

Sajjan, Sangeetha S and Bhumika, CS and Choudhury, Balamati and Nair, RU (2019) Machine-learning for classification of naval targets. In: 2019 IEEE MTT-S International Microwave and RF Conference (IMARC), 13-15 December 2019, Mumbai, India.

[img] Text
09118614.pdf
Restricted to Registered users only

Download (6MB)
Official URL: https://ieeexplore.ieee.org/document/9118614

Abstract

Naval target classification is one of the prominent area of research in defence to safeguard ships and to provide guidelines for shipping channels. This work mainly explains the machine learning approach for naval target classification by examining the radar kinematics. The Artificial Neural Network (ANN) model is developed to classify various ship models. The Radar Cross-Section (RCS) data has been used for identification and classification of the naval target. The RCS database for ships are generated by simulating the open domain CATIA models.

Item Type: Conference or Workshop Item (Paper)
Subjects: MATHEMATICAL AND COMPUTER SCIENCES > Mathematical and Computer Scienes(General)
MATHEMATICAL AND COMPUTER SCIENCES > Cybernetics, Artificial Intelligence and Robotics
Depositing User: Mrs SK Pratibha
Date Deposited: 23 Nov 2021 11:43
Last Modified: 23 Nov 2021 11:43
URI: http://nal-ir.nal.res.in/id/eprint/13326

Actions (login required)

View Item View Item