摘要
全空时自适应处理在工程实现中因计算量大、独立同分布样本难以获取等问题而使应用受到一定限制,在传统互谱法以及杂波协方差矩阵特征向量分解法两种空时自适应处理降维算法的基础上,提出了一种新的基于互谱思想的协方差矩阵特征向量分解算法,该方法根据不同的互谱值对应的信噪比损失的大小不同这一原理构造降维矩阵,有效地降低了运算量,并能够形成较好的杂波滤波凹口,实现了滤除杂波的性能,文中经过实验仿真验证了该方法的有效性。
The optimum full rank space time adaptive processing exhibits excellent performance,but its computation load and its implementation complexity are so large that can not be accepted.Two reduced-rank space time adaptive processing methods,the cross spectral method and the covariance matrix eigen-decomposition method are analyzed.Then a new method which has better capability and less computation load is proposed.The effectiveness of the proposed approach is verified by the numerical results of simulation.
出处
《雷达科学与技术》
2011年第4期330-334,共5页
Radar Science and Technology
关键词
空时自适应处理
互谱法
协方差矩阵
特征向量分解
space time adaptive processing
cross spectral method
covariance matrix
eigenvector decomposition
