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An Anti-FOD Method Based on CA-CM-CFAR for MMW Radar in Complex Clutter Background.
Yang, Xiaoqi; Huo, Kai; Su, Jianwei; Zhang, Xinyu; Jiang, Weidong.
Afiliação
  • Yang X; Graduate School, National University of Defense Technology, Changsha 410073, China.
  • Huo K; College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.
  • Su J; College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.
  • Zhang X; College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.
  • Jiang W; College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.
Sensors (Basel) ; 20(6)2020 Mar 14.
Article em En | MEDLINE | ID: mdl-32183386
ABSTRACT
Traditional constant false alarm rate (CFAR) methods have shown their potential for foreign object debris (FOD) indication. However, the performance of these methods would deteriorate under the complex clutter background in airport scenes. This paper presents a threshold-improved approach based on the cell-averaging clutter-map (CA-CM-) CFAR and tests it on a millimeter-wave (MMW) radar system. Clutter cases are first classified with variability indexes (VIs). In homogeneous background, the threshold is calculated by the student-t-distributed test statistic; under the discontinuous clutter conditions, the threshold is modified according to current VI conditions, in order to address the performance decrease caused by extended clutter edges. Experimental results verify that the chosen targets can be indicated by the t-distributed threshold in homogeneous background. Moreover, effective detection of the obscured targets could also be achieved with significant detectability improvement at extended clutter edges.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China