Open Access Journal

ISSN : 2394 - 6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering
Call For Paper : Vol 11, Issue 08, August 2024

ISSN : 2394-6849 (Online)

Call for Paper

Vol 11, Issue 08, August 2024

Indexing

Synthetic Aperture Radar Feature extraction and Emerging Trends

Author : SK Wagle 1 Dr A Bazil Raj 2 Dr KP Ray 3

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Date of Publication :20th May 2021

Abstract: Synthetic Aperture Radar (SAR) image analysis and classification is one of the challenging as well as promising field in Modern Military warfare in reducing the reaction time between the Sensor and the shooter grid. Towards this, many attempts have been made for Automatic Target Recognition using various Machine learning and Deep learning Techniques. In this Paper,an attempt is made to study the existing techniques used to classify various SAR images without human intervention. The complexity involved in SAR images is more, mainly due to lack of sufficient training images to train the Deep Learning Neural Network Model. This may lead to Overfitting, due to which the Model may work with the Training images only but may not workwith the testing images. To mitigate this issue of overfitting, we have suggested Data Augmentation. Certain Data Augmentationtechniques have been compared and a simplistic model is suggested by which, we can achieve a high degree of accuracy in MilitaryTarget prediction with the limited amount of Training images.

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