摘要
为解决星载合成孔径雷达地面动目标检测(SAR-GMTI)系统中用自适应匹配滤波(AMF)法估计运动目标径向速度参数时,因背景杂波与待检测单元的杂波不匹配或训练样本不足而导致目标速度估计的性能下降的不足,提出了一种用待检测单元数据直接重构出杂波加噪声相关矩阵,再用自适应匹配滤波算法估计动目标速度参数的新方法。仿真结果证明该法在背景杂波与待检测单元杂波不匹配时能精确估计运动目标的径向速度。
To solve the problem that the performance of radial velocity estimation was degraded when the mismatch existed between the clutter background and the cell under test （CUT） or the trained samples were insufficient in the ground moving target indication system of synthetic aperture radar using adaptive match filtering （AMF） method to estimate the radial velocity of the moving target, a novel method to utilize the CUT data to reconstruct the clutter-plus-noise covariance matrix, and estimate the velocity parameters of moving targets by the cost function of AMF algorithm was put forward in this paper. The simulations results verified that the effectiveness of the proposed method in precisely estimating the radial velocity of moving targets under circumstance of mismatch between the background clutter and CUT clutter.
出处
《上海航天》
2015年第4期13-16,72,共5页
Aerospace Shanghai
关键词
星载合成孔径雷达
地面动目标检测
能量失配
速度估计
自适应匹配滤波
Spaceborn synthetic aperture radar
Ground moving target indication
Power mismatch
Velocity estimation
Adaptive match filtering
