Target recognition for synthetic aperture radar imagery based on convolutional neural network feature fusion

Odysseas Kechagias-Stamatis

doi:10.1117/1.JRS.12.046025

4 December 2018 Target recognition for synthetic aperture radar imagery based on convolutional neural network feature fusion

Odysseas Kechagias-Stamatis

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 4, 046025 (December 2018). https://doi.org/10.1117/1.JRS.12.046025

Abstract

Driven by the great success of deep convolutional neural networks (CNNs) that are currently used by quite a few computer vision applications, we extend the usability of visual-based CNNs into the synthetic aperture radar (SAR) data domain without employing transfer learning. Our SAR automatic target recognition (ATR) architecture efficiently extends the pretrained Visual Geometry Group CNN from the visual domain into the X-band SAR data domain by clustering its neuron layers, bridging the visual—SAR modality gap by fusing the features extracted from the hidden layers, and by employing a local feature matching scheme. Trials on the moving and stationary target acquisition dataset under various setups and nuisances demonstrate a highly appealing ATR performance gaining 100% and 99.79% in the 3-class and 10-class ATR problem, respectively. We also confirm the validity, robustness, and conceptual coherence of the proposed method by extending it to several state-of-the-art CNNs and commonly used local feature similarity/match metrics.

Citation Download Citation

Odysseas Kechagias-Stamatis "Target recognition for synthetic aperture radar imagery based on convolutional neural network feature fusion," Journal of Applied Remote Sensing 12(4), 046025 (4 December 2018). https://doi.org/10.1117/1.JRS.12.046025

Received: 4 August 2018; Accepted: 6 November 2018; Published: 4 December 2018

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available