Open AccessMoving target detection with polarimetric distributed MIMO radar in heterogeneous clutter
Author(s) -
Xiang Yan,
Liu Zhiwen,
Huang Yulin,
Xu Yougen
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0705
Subject(s) - clutter , wishart distribution , covariance matrix , inverse wishart distribution , polarimetry , computer science , covariance , detector , likelihood ratio test , radar , algorithm , constant false alarm rate , remote sensing , mathematics , statistics , physics , telecommunications , optics , geography , machine learning , multivariate statistics , scattering
In this study, the authors consider the problem of moving target detection in the presence of heterogeneous clutter. The knowledge‐aided method has been extended to derive the polarimetric multiple‐input multiple‐output (MIMO) radar detector. And the polarimetric clutter covariance matrix was modelled as a complex inverse Wishart distribution. More precisely, the clutter covariance matrices between different transmitter–receiver (Tx–Rx) pairs are assumed to follow the distribution which shares a prior clutter covariance matrix structure while with different values of the power levels. Under this assumption, the generalised likelihood ratio test (GLRT) approach has been adopted to develop the polarimetric knowledge‐aided detector without secondary data. Numerical results are shown to illustrate the effectiveness of the polarimetric knowledge‐aided GLRT detector in heterogeneous clutter.