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在机载雷达空时二维自适应处理 (STAP)中 ,足够数量的IID采样数据才可以构成杂波相关矩阵的有效估计 ,而实际雷达工作环境中的采样数总是有限的 针对这一问题 ,提出了将前后平均 ,对角加载 ,与降维处理相结合来降低采样数目要求 ,解决采样支持问题的方案 ,并进行了理论分析与仿真。显然 ,通过采用适当的降维处理与前后平均及对角加载相结合 ,所需采样数最多可降低到仅用 3～ 5个
In space-time two-dimensional adaptive processing (STAP) of airborne radars, a sufficient number of IID sample data can constitute a valid estimation of the clutter correlation matrix, and the number of samples in the actual radar working environment is always limited for this problem , A scheme of reducing the number of samples and solving the problem of sampling support by averaging the front and the rear, loading diagonally and reducing the dimensionality is proposed, and theoretical analysis and simulation are carried out. Obviously, the number of samples required can be reduced to as little as 3 to 5 by using appropriate dimensionality reduction processing in combination with anterior-posterior mean and diagonal loading