Owing to the heavy spread of eigenspectrum of the population covariance matrix under finite training samples condition, it is a challenge to estimate the clutter Degrees of Freedom (DoF) in airborne forward-looking radar. In this work, a method for estimation the clutter’s DoF is proposed. In order to estimate the clutter’s DoF, an idea from sources detection by Minimum Description Length (MDL) criterion is borrowed, and the parametric probability model is formed based on the eigenvalue’s statistical distribution properties from Random Matrix Theory (RMT). The proposed method is effective to estimate the clutter’s DoF under finite training samples condition, and the simulation results verify the efficiency of the proposed method.
李海，刘新龙，蒋婷，吴仁彪. 基于随机矩阵理论和最小描述长度的机载前视阵雷达杂波自由度估计[J]. 电子与信息学报, 2016, 38(12): 3224-3229.
LI Hai, LIU Xinlong, JIANG Ting, WU Renbiao. Estimation of Clutter Degrees of Freedom in Airborne Forward-looking Radar via Random Matrix Theory and Minimum Description Length Criteria. JEIT, 2016, 38(12): 3224-3229.
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