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RATR of adaptive angular-sector segmentation based on grey incidence analysis model

RATR of adaptive angular-sector segmentation based on grey incidence analysis model PurposeThe purpose of this paper is to solve the azimuth sensitivity of a high-resolution range profile (HRRP), which is one of the biggest obstacles faced by a radar automatic target recognition (RATR) system.Design/methodology/approachAimed at addressing the shortcomings of the equal angular-sector segmentation based on the scatterer model, an adaptive angular-sector segmentation is proposed on the basis of grey incidence analysis (GIA).FindingsThe main conclusions reached are as follows. First, the adaptive angular-sector segmentation in terms of GIA is suitable for RATR based on the HRRP; and, second, the adaptive angular-sector segmentation based on the type-B degree of grey incidence model is better than the Deng-Si degree of grey incidence model and the degree of grey slope incidence model.Practical implicationsThe outcome obtained in this paper can be selected for the RATR application.Originality/valueThis paper has been built on the basis of previous research achievements, and a new RATR method of adaptive angular-sector segmentation is presented based on the GIA. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Grey Systems: Theory and Application Emerald Publishing

RATR of adaptive angular-sector segmentation based on grey incidence analysis model

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2043-9377
DOI
10.1108/GS-09-2016-0034
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this paper is to solve the azimuth sensitivity of a high-resolution range profile (HRRP), which is one of the biggest obstacles faced by a radar automatic target recognition (RATR) system.Design/methodology/approachAimed at addressing the shortcomings of the equal angular-sector segmentation based on the scatterer model, an adaptive angular-sector segmentation is proposed on the basis of grey incidence analysis (GIA).FindingsThe main conclusions reached are as follows. First, the adaptive angular-sector segmentation in terms of GIA is suitable for RATR based on the HRRP; and, second, the adaptive angular-sector segmentation based on the type-B degree of grey incidence model is better than the Deng-Si degree of grey incidence model and the degree of grey slope incidence model.Practical implicationsThe outcome obtained in this paper can be selected for the RATR application.Originality/valueThis paper has been built on the basis of previous research achievements, and a new RATR method of adaptive angular-sector segmentation is presented based on the GIA.

Journal

Grey Systems: Theory and ApplicationEmerald Publishing

Published: Feb 6, 2017

References