一种基于SAR稀疏采样数据的动目标运动参数估计方法

Parameter Estimation Method of Moving Targets with SAR Sparse Sampling Data

该文针对地面动目标运动参数估计问题进行研究,提出一种利用单天线合成孔径雷达(SAR)稀疏采样数据的动目标2维速度估计方法。首先以目标2维速度为参数构建一个等效参数化模型将动目标回波数据转化为小斜视回波数据,然后利用改进的迭代阈值算法实现不同参数条件下的动目标2维成像,最后以成像结果的图像熵值为优化准则对初始模型参数进行搜索,从而获得准确的动目标运动参数。该方法以稀疏采样数据为输入,可以减少所需数据量,并且能够有效避免多普勒模糊问题,在较低信杂比条件下仍然能够准确估计出目标运动参数。仿真实验结果验证了所提动目标参数估计方法的有效性。

To solve the problem of motion parameter estimation of ground moving target, a parameter estimation method of moving targets with sparse sampling data of single SAR sensor is proposed. First, based on the 2 dimensional velocity of moving targets, an equivalent parametric model is constructed to transform the moving target echo into squint SAR echo. Then, with different parameters the modified iterative thresholding algorithm is applied to achieving imagery of moving target. Finally, the motion parameters of targets are obtained by minimizing the image entropy. It is shown that, using the proposed method, the required echo sampling can be reduced, the Doppler ambiguity problem can be avoided and accurate velocity estimation can be obtained even in low signal-to-clutter ration scenarios. Simulation results verify the effectiveness of the proposed method.