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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。
In order to reduce the computational complexity of the synthetic aperture radar (SAR) imaging algorithm, an effective target 3D feature extraction method is proposed. The method extracts the three-dimensional features of scattering points one by one based on slackness and decouples the positions of scattering points as the order estimates by using the weak coupling between the distance parameters of scattering points and the parameters (azimuth and height) perpendicular to the distance direction. Due to the adoption of a series of low-dimensional optimization processes to obtain parameter estimates of all scattering points, this method has a lower computational cost. The simulation results show that this method can effectively image three-dimensional target and the performance of parameter estimation is comparable with other curved SAR imaging algorithms. So this algorithm has not caused the performance loss while reducing the computational complexity.