title: Modified Anderson-Darling test-based target detector in non-homogenous environments.
abstract: A constant false alarm rate (CFAR) target detector in non-homogenous backgrounds is proposed. Based on K-sample Anderson-Darling (AD) tests, the method re-arranges the reference cells by merging homogenous sub-blocks surrounding the cell under test (CUT) into a new reference window to estimate the background statistics. Double partition test, clutter edge refinement and outlier elimination are used as an anti-clutter processor in the proposed Modified AD (MAD) detector. Simulation results show that the proposed MAD test based detector outperforms cell-averaging (CA) CFAR, greatest of (GO) CFAR, smallest of (SO) CFAR, order-statistic (OS) CFAR, variability index (VI) CFAR, and CUT inclusive (CI) CFAR in most non-homogenous situations.
authors.affiliation: Department of Electronic Engineering, Harbin Institute of Technology, Harbin 150001, China. li.yang@hit.edu.cn.
authors.forename: Yang
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Electronic Engineering, Harbin Institute of Technology, Harbin 150001, China. weiys@hit.edu.cn.
authors.forename: Yinsheng
authors.initials: Y
authors.lastname: Wei
authors.affiliation: Department of Electronic Engineering, Harbin Institute of Technology, Harbin 150001, China. westerange@163.com.
authors.forename: Bingfei
authors.initials: B
authors.lastname: Li
authors.affiliation: Center for Biomedical Informatics, Harvard University, Boston, MA 02115, USA. gil_alterovitz@hms.harvard.edu.
authors.forename: Gil
authors.initials: G
authors.lastname: Alterovitz