曲线合成孔径雷达中散射点三维特征提取方法

为了减少曲线合成孔径雷达(syntheticapertureradar,SAR)的成像算法计算复杂度,提出一种有效的目标三维特征提取方法。该方法基于松驰思想逐个提取散射点的三维特征,并利用散射点的距离参数与垂直于距离方向上参数(方位和高度)之间的弱耦合性将散射点位置估计解耦为顺序估计。由于采用了一系列的低维优化过程来获得所有散射点的参数估计,该方法具有较低的运算代价。仿真结果表明:该方法可以有效地对三维目标成像,且参数估计性能与其他曲线SAR成像算法相当。所以该算法在降低计算复杂度的同时并未造成性能上的损失。

Extraction of 3-D features of scatterers in curvilinear SAR

The computational complexity of current imaging methods for curvilinear synthetic aperture radar (SAR) is reduced by a relaxation-based sequential optimization method that extracts the scatterers' three-dimensional (3-D) features. The algorithm extracts the scatterers one by one using the relaxation and reduces the 3-D position estimate from a joint estimate into a sequential estimate because of the loose coupling between the range and cross-range parameters. By utilizing a series of lower dimensional optimizations, the algorithm dramatically reduces the computational burden. Simulation results show that the algorithm provides an efficient imaging method for curvilinear SAR with similar performance to other imaging algorithms. Therefore, the method is computationally more efficient without any performance loss.