Multifeature decision fusion is an effective way to promote the performance of target
recognition of synthetic aperture radar (SAR) images. This paper proposes a joint …

We propose a synthetic aperture radar (SAR) automatic target recognition (ATR) method by
jointly classifying three complementary features based on multitask compressive sensing …

A novel multitask compressive sensing (MtCS)-based method for multi-view radar automatic
target recognition is presented in the paper. The sparse representation vectors recovered …

The emerging field of compressed sensing provides sparse reconstruction, which has
demonstrated promising results in the areas of signal processing and pattern recognition. In …

In order to improve synthetic aperture radar (SAR) target recognition performance, this paper
proposes a novel method using multi-level deep features. The multi-level deep features are …

ABSTRACT A multi-criteria sparse representation-based classification (SRC) is developed
for synthetic aperture radar (SAR) target recognition. The sparse representation is first …

The monogenic signal, which is defined as a linear combination of a signal and its Riesz-
transformed one, provides a great opportunity for synthetic aperture radar (SAR) image …

This letter proposes a synthetic aperture radar (SAR) target recognition method via joint
classification of deep features fused by multi-canonical correlation analysis (MCCA). A …

In this paper, we present a Synthetic Aperture Radar (SAR) image target recognition
algorithm based on multi-feature multiple representation learning classifier fusion. First, it …

This letter develops a synthetic aperture radar (SAR) target classification method based on
bidimensional variational mode decomposition (BVMD) and multitask compressive sensing …