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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

李海 刘新龙 蒋婷 吴仁彪

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. doi: 10.11999/JEIT160132
引用本文: 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. doi: 10.11999/JEIT160132
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[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3224-3229. doi: 10.11999/JEIT160132
Citation: 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[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3224-3229. doi: 10.11999/JEIT160132

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

doi: 10.11999/JEIT160132
基金项目: 

国家自然科学基金(61471365, 61571442, 61231017)

中央高校基本科研业务费项目(3122015B002),中国民航大学蓝天青年学者培养经费

Estimation of Clutter Degrees of Freedom in Airborne Forward-looking Radar via Random Matrix Theory and Minimum Description Length Criteria

Funds: 

The National Natural Science Foundation of China (61471365, 61571442, 61231017), The National Universitys Basic Research Foundation of China (3122015B002), The Foundation for Sky Young Scholars of Civil Aviation University of China

  • 摘要: 有限训练样本时,总体协方差矩阵特征谱的严重扩展使得机载前视阵雷达杂波自由度估计困难。该文提出一种前视阵杂波自由度估计方法,该方法利用随机矩阵理论(Random Matrix Theory, RMT)中特征值统计分布特性建立参数化的概率模型,结合最小描述长度(Minimum Description Length, MDL)准则关于信源检测的思想估计杂波自由度。该方法能够在有限训练样下实现杂波自由度的有效估计,仿真结果验证了方法的有效性。
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出版历程
  • 收稿日期:  2016-01-29
  • 修回日期:  2016-06-23
  • 刊出日期:  2016-12-19

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