电子学报 ›› 2014, Vol. 42 ›› Issue (3): 523-528.DOI: 10.3969/j.iss.0372-2012-2014.03.016

• 学术论文 • 上一篇    下一篇

极化辅助的非均匀场景空时自适应处理方法

杜文韬, 廖桂生, 杨志伟, 辛志慧   

  1. 西安电子科技大学雷达信号处理国家重点实验室, 陕西西安 710071
  • 收稿日期:2012-09-06 修回日期:2013-10-09 出版日期:2014-03-25
    • 作者简介:
    • 杜文韬 男,1989年2月生于安徽巢湖,现为西安电子科技大学信号与信息处理专业博士生,主要研究方向为运动平台雷达动目标检测,空时自适应处理处理等.E-mail:duwentao_xd@163.com
    • 基金资助:
    • 长江学者与创新团队发展计划 (No.IRT0954); 国家自然科学基金 (No.60901066); 中央高校基本科学研业务费专项奖金资金 (No.K5051302007); 陕西省教育厅科研计划项目 (No.2013JK1051)

Polarization-Aided Adaptive Processing for Ground Moving Target Indication in Heterogeneous Clutter

DU Wen-tao, LIAO Gui-sheng, YANG Zhi-wei, XIN Zhi-hui   

  1. National Lab of Radar Signal Processing, Xidian University, Xi'an, Shaanxi 710071, China
  • Received:2012-09-06 Revised:2013-10-09 Online:2014-03-25 Published:2014-03-25
    • Supported by:
    • Program for Changjiang Scholars and Innovative Research Team in University (No.IRT0954); National Natural Science Foundation of China (No.60901066); Special Bonus Fund of Fundamental Research Fund for the Central Universities (No.K5051302007); Program of Research Project of Education Department of Shaanxi Province (No.2013JK1051)

摘要: 空时自适应处理是强杂波背景下动目标检测的有效途径,实际检测环境中训练样本与待检测单元背景统计特性的不一致将恶化处理器的输出信杂噪比,需要结合样本挑选技术来改善非均匀场景的处理器性能.在建立机载多通道信号模型基础上,提出一种利用极化信息辅助的空时自适应处理方法,该方法通过极化分类和功率分组指导训练样本选择,利用同类样本估计待检测单元的统计特性并计算自适应权矢量,具有杂波相关矩阵估计准确度高的特点,可显著改善动目标检测的性能.最后结合国外NASA JPL AIRSAR实测数据的多通道仿真实验验证了所提方法的有效性.

关键词: 地面运动目标检测, 杂波抑制, 极化信号处理

Abstract: Space-time adaptive processing is an effective method to detect ground moving targets embedded in clutter environment,and the estimation of clutter covariance matrix with training samples is required to perform the adaptive processing commonly.In realistic environment,the characteristics of clutter in the cell under test may be different with the training samples in other range cells,which would reduce the precision of the estimated clutter covariance matrix.To improve the performance of target detection,a training sample selecting method based on polarized classification and power grouping is proposed in this paper,which would improve the precision of the clutter covariance matrix.The simulation results demonstrate the effectiveness of the proposed method.

Key words: ground moving target indication, clutter rejection, polarized signal processing

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