An Improved Scheme for Target Discrimination in High-Resolution SAR Images

Abstract

To design a highly automatic and practical method for target discrimination in synthetic aperture radar images, we propose in this paper an improved scheme consisting of the framework and algorithms for target discrimination. Our main contribution in this scheme comprises four aspects. First, an integrative frame sequentially combining the algorithm based on feature extraction and the knowledge of target group has been presented. Second, three new features for target discrimination have been introduced. Third, a genetic algorithm-based featureselection algorithm has been presented. The results show that this algorithm can evaluate the goodness-of-feature better. Finally, to improve the accuracy of the discriminator, we have designed a weighted quadratic distance discriminator, which has been observed to improve the performance of target discrimination. We have analyzed the performance of the proposed scheme comprehensively and specifically using some measured data, and carried out comparisons of the existing algorithms. The results show that the proposed scheme could improve the application ability in target discrimination.

A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

“…Sys2 is implemented from [75] (recognizing target 6, 7, and 9, and is referred to as recognizing T6, T7, and T9 throughout this work). Sys3A is accomplished in conformity to [76] (recognizing P Pulse and T Pulse in this work).…”

Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory

“…Generally, Rayleigh PDF and Gamma PDF are widely used in the clutter model. However, for the ground clutter with a long tail, a better model is demanded [25]. Here, a Weibull PDF is applied, with the density function as follows: $\begin{array}{c}truerightf(x)=\frac{c}{b}{\left(\frac{x}{b}\right)}^2{e}^{-{\left(\frac{x}{b}\right)}^c},\end{array}$ where x is the data amplitude, b and c , respectively, represent the scale and shape parameter which can be estimated from the data mean $<x>$ and standard deviation ${\sigma }_x$, $c=0.0791{\left(\frac{<x>}{{\sigma }_x}\right)}^2+0.8481\left(\frac{<x>}{{\sigma }_x}\right)+0.0817$ and $b=\frac{<x>}{\Gamma (1+\frac{1}{c})}$ [26].…”

High Range Resolution Profile Construction Exploiting Modified Fractional Fourier Transformation

“…The HRRP achieved by a wide band radar can be recognized as the transfer function of the group target. The transfer function of the target echoes with different time delays can be expressed as [1,2] h ( ) = [ 0 ( − 0 ) , 1 ( − 1 ) , . .…”

“…The task of detecting unresolvable group targets raises new challenges for both target detection and discrimination. A group target refers to a group of subtargets in a formation flying in the same direction with the same speed, such as aircrafts in a close formation, missiles with multiple warheads, or space debris in outer space orbit [1][2][3][4]. High range resolution profile (HRRP) of a wide band radar is an effective technique for the discrimination of a group target, and it has been intensively investigated in the field of automatic target recognition (ATR) [5][6][7].…”