雷达成像中稀疏孔径外推新算法

A New Algorithm for Sparse Aperture Extrapolation in Radar Imaging

该文提出一种由稀疏孔径数据外推全孔径估计算法,这种算法对于稀疏孔径存在大的空缺的情况,可以利用已知稀疏孔径用参数化方法得到准确的稀疏孔径频域能量分布估计,把稀疏孔径功率谱估计作为先验信息,以最小加权范数为约束进行外推估计空缺孔径,得到完整孔径估计。该算法可有效应用于合成孔径雷达稀疏孔径成像,仿真与实际数据处理结果证实算法的有效性。

An algorithm for estimating full aperture by sparse data is proposed in this paper. For big vacant aperture in sparse data, by measuring sparse data actually, accurate sparse data frequency domain energy distribution estimate can be obtained with parametric approaches. With estimated power spectrum as prior information, minimum weighting norm as the restraint, underdetermined equations are solved to interpolate vacant aperture, thus wide aperture data segment estimate is .obtained. This algorithm can be effectively applied to SAR imaging in sparse data. Resulting simulation and actual data processing results confirm validity of the proposed algorithm.