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 …

An Automatic Target Recognition (ATR) system is a sensor which is usually able to
recognize targets or objects based on gathered data. The application of automatic target …

Discriminant analysis is a technique used in statistics and machine learning to separate two
or more classes of objects or events. We introduce linear, quadratic, and mixture …

The Gaussian form of the Bhattacharyya distance measure is being used by some in the
automatic target recognition (ATR) community to select features and to estimate an upper …

A novel subspace analysis method called diagonal clustering-based discriminant analysis
(DiaCDA) is proposed. Unlike principal component analysis (PCA), fisher linear discriminant …

This paper compares bootstrap techniques with prior probability synthetic data balancing to
determine which method is more effective for SAR target recognition. A bootstrap method …

Multi‐feature decision fusion is a robust way to enhance the performance of synthetic
aperture radar (SAR) automatic target recognition (ATR). This study fuses two physically …

For several years, different types of classifiers have been developed using several features
vector in the automatic target recognition (ATR) field. However, because of measurement …

In discriminating between objects from different classes, the more separable these classes
are the less computationally expensive and complex a classifier can be used. One thus …

The most popular separation criterion of establishing rules for discrimination and recognition
(classification) of patterns is the Fisher discriminant (separation) ratio. The approach …