一种稀疏恢复的稳健配准补偿方法
发布时间：2019-03-26 11:12
【摘要】：常规基于配准补偿方法因子孔径损失和先验信息失配问题,导致杂波距离依赖性和补偿性能下降.为解决上述问题,将稀疏恢复算法引入到杂波距离依赖性补偿当中,并对常规基于配准补偿方法中各距离单元回波数据预处理过程加以改进,提出了一种基于稀疏恢复的稳健距离配准补偿方法——SRBC方法.该方法与常规基于配准补偿方法相比,无需子孔径平滑,不依赖于先验知识,直接利用稀疏恢复得到超分辨的杂波空时谱,计算得出过渡协方差矩阵,再通过Capon谱重构出杂波协方差矩阵.经仿真验证,SRBC方法不受先验信息失配影响,不仅能够实现杂波距离依赖性的自适应补偿,在存在阵元误差时的杂波抑制性能同样较为稳定.
[Abstract]:The problem of aperture loss and prior information mismatch based on the conventional registration compensation method results in clutter distance dependence and compensation performance degradation. In order to solve the above problems, sparse restoration algorithm is introduced into clutter distance dependence compensation, and the preprocessing process of echo data of each distance unit in the conventional registration-based compensation method is improved. A robust distance registration compensation method-SRBC method based on sparse restoration is proposed. Compared with the conventional registration-based compensation method, this method does not need sub-aperture smoothing and does not depend on prior knowledge. The super-resolution space-time spectrum of clutter is obtained directly by sparse restoration, and the transition covariance matrix is obtained by calculating the matrix of transition covariance. Then the clutter covariance matrix is reconstructed by Capon spectrum. Simulation results show that the SRBC method is not affected by prior information mismatch. It can not only compensate clutter distance dependence adaptively, but also stabilize clutter suppression performance in the presence of element errors.
【作者单位】： 空军工程大学防空反导学院;空军95100部队;
【基金】：国家自然科学基金资助项目(6150010274)
【分类号】：TN959.73
，
本文编号：2447488
[Abstract]:The problem of aperture loss and prior information mismatch based on the conventional registration compensation method results in clutter distance dependence and compensation performance degradation. In order to solve the above problems, sparse restoration algorithm is introduced into clutter distance dependence compensation, and the preprocessing process of echo data of each distance unit in the conventional registration-based compensation method is improved. A robust distance registration compensation method-SRBC method based on sparse restoration is proposed. Compared with the conventional registration-based compensation method, this method does not need sub-aperture smoothing and does not depend on prior knowledge. The super-resolution space-time spectrum of clutter is obtained directly by sparse restoration, and the transition covariance matrix is obtained by calculating the matrix of transition covariance. Then the clutter covariance matrix is reconstructed by Capon spectrum. Simulation results show that the SRBC method is not affected by prior information mismatch. It can not only compensate clutter distance dependence adaptively, but also stabilize clutter suppression performance in the presence of element errors.
【作者单位】： 空军工程大学防空反导学院;空军95100部队;
【基金】：国家自然科学基金资助项目(6150010274)
【分类号】：TN959.73
，
本文编号：2447488
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