Both principal component analysis (PCA) and linear discriminant analysis (LDA) have long
been recognized as tools for feature extraction and data analysis. There has been reports in …

The convolutional neural network (CNN) is widely used in synthetic aperture radar (SAR)
target recognition, but conventional CNN mainly adopts a single-scale convolutional kernel …

Multiview synthetic aperture radar (SAR) images contain much richer information for
automatic target recognition (ATR) than a single-view one. It is desirable to establish a …

Synthetic aperture radar (SAR) is an important microwave sensor that is capable of high-
resolution imaging. Extracting valuable features from the SAR target imagery is one of …

Due to weather-and illumination-independent characteristics, synthetic aperture radar (SAR)
has become an important tool for target recognition. Using analysis of existing methods, a …

Synthetic aperture radar (SAR) automatic target recognition is an important application in
SAR. How to extract features has restricted the application of SAR technology seriously. In …

With the present revival of interest in bistatic radar systems, research in that area has gained
momentum. Given some of the strategic advantages for a bistatic configuration, and …

This paper analyzes the potential for improvement in the performance of automatic target
recognition (ATR) for synthetic-aperture radar (SAR) with bistatic aspect diversity. Initial …

Background clutter is becoming one of the most important factors affecting the target
acquisition performance of electro-optical imaging systems. A novel clutter metric based on …

Validation of automatic target recognition (ATR) algorithm needs huge amount of real data,
which is mostly infeasible. Hence we need statistical separability indices (SI) to evaluate the …