针对干涉合成孔径雷达干涉图由于局部噪声、阴影或条纹断裂等原因导致残差点集中、产生不可靠数据点噪声斑块, 从而引起相位解缠困难的情况, 提出基于掩膜滤波的质量图引导权值的四向加权最小二乘相位解缠迭代算法.首先对噪声斑块区域进行掩膜滤波处理, 有效保留该区域真实相位信息, 防止大误差传播.再结合最大相位梯度和相位导数变化的质量图法来定义权值, 构造新的四项最小二乘迭代法, 并用其对掩膜区域进行填充, 抑制误差传递、提高运算速度、改善过度平滑作用.模拟及真实数据实验表明, 该方法解缠精度高, 能真实还原干涉合成孔径雷达干涉图局部噪声斑块的原始相位.与传统最小二乘法相比, 其差分方程矩阵带宽变大, 填充效果更好, 迭代次数更少, 精确度更高, 解决了因噪声集中导致干涉合成孔径雷达图像解缠难度大的问题.

Four-direction weighted least squares phase unwrapping iterations algorithm is proposed based on regional mask filtering and the method of quality map leading weigh to solve the problem that interferometric synthetic aperture radar interferogram is difficult for phase unwrapping due to local noise, shadows or stripe breaks, which result in residual focus and unreliable data patches. Firstly, the noise patch region is masked and filtered. Therefore the real phase information is preserved and the error propagation is prevented effectively. Then, the four-direction least-squares iteration method, which can redefine the weight value by using the quality map method which can describe the maximum phase gradient and the change of phase derivative, is used to fill the mask region to suppress the error propagation, increase the computing speed and improve the over-smoothing effect. Simulation and real data experiments show that the proposed method has high unwrapping accuracy and can restore the original phase of the local patch of interferometric synthetic aperture radar interferogram. Compared with the traditional least squares method, it has the advantages of larger bandwidth of the difference equation matrix, better filling effect, less number of iterations and higher accuracy, which can solve the difficulty of interferometric synthetic aperture radar image unwrapping caused by noise concentration.