Automatic target recognition (ATR) for military applications is one of the core processes toward enhancing intelligence and autonomously operating military platforms. Spurred by this and given that Synthetic Aperture Radar (SAR) presents several advantages over its counterpart data domains, this article surveys and assesses current SAR ATR algorithms that employ the most popular dataset for the SAR domain, namely the moving and stationary target acquisition and recognition (MSTAR) dataset. Specifically, we perform a direct comparison between current SAR ATR methods and highlight the strengths and weaknesses of each technique under both standard and extended operational conditions. Additionally, despite MSTAR being the standard SAR ATR benchmarking dataset, we also highlight its weaknesses and suggest future research directions.
Automatic Target Recognition on Synthetic Aperture Radar Imagery: A Survey
IEEE Aerospace and Electronic Systems Magazine ; 36 , 3 ; 56-81
2021-03-01
3239780 byte
Article (Journal)
Electronic Resource
English
(Automatic) target detection in synthetic aperture radar imagery via terrain recognition
Tema Archive | 2001
|Automatic Target Recognition using Multipolar Bistatic Synthetic Aperture Radar Images
Online Contents | 2010
|Analysis of synthetic aperture radar imagery
NTRS | 1977
|Processing for spaceborne synthetic aperture radar imagery
TIBKAT | 1973
|