非均匀杂波背景下STAP降维算法研究

Research on STAP Dimensionality Reduction Algorithm in Non-Uniform Clutter Background

机载雷达对地观测时,面临由于平台运动引起杂波谱展宽,平台偏航引入垂直基线使杂波谱对高程敏感,导致方位与距离模糊。复杂地物场景局部杂波散射强度变化以及大量目标干扰等非理想因素,致使杂波分布非均匀,严重制约了杂波抑制性能与动目标检测性能。针对上述问题,本文所采用的空时自适应处理(STAP)降维算法可以有效解决慢速运动目标低检出问题,提高非均匀杂波背景下杂波的抑制能力,增强运动目标的检测性能。其特点在于:利用多维域数据实现在线地物区域划分,增大有效样本容量,样本充足条件下直接估计杂波加噪声协方差矩阵实现杂波抑制。针对孤立离散杂波、干扰,结合杂波谱重构解决单样本下的地形杂波抑制与干扰对消,通过实测数据分析证明了本文所提算法的有效性。

When the airborne radar observes the ground,due to the broadening of the clutter spectrum caused by the movement of the platform,the vertical baseline introduced by the platform yaw makes the clutter spectrum sensitive to the elevation,which results in ambiguity of azimuth and range.The variation of local clutter scattering strength and a large number of targets in complex ground scenarios lead to non-uniform clutter distribution,which seriously restricts the performance of clutter suppression and moving target detection.The space-time adaptive processing(STAP)dimensionality reduction algorithm adopted in this paper can effectively solve the problem of low detection rate of slow moving targets,improve the clutter suppression ability under the background of non-uniform clutter,and enhance the detection performance of moving targets.Multi-dimensional data is used to achieve online regional division of ground objects and increase the effective sample size.The clutter suppression is realized by directly estimating the clutter plus noise covariance matrix under the condition of sufficient samples.Aiming at isolated discrete clutter and interference,combined with clutter spectrum reconstruction,terrain clutter suppression and interference cancellation under a single sample are achieved.The effectiveness of the proposed algorithm is proved through analysis of measured data.