基于干涉图的传统干涉相位估计方法,当由于图像配准误差而导致的干涉图质量较差时,就难以恢复出准确的真实干涉相位。本文提出了一种基于加权联合导向矢量模型的InSAR干涉相位估计方法。该方法构造最优联合观测矢量和加权联合导向矢量,同时利用相邻像素的相干信息,并采用波束形成技术,因此具有自适应图像配准和降低相位噪声的功能,因而可以在SAR图像配准精度很差(可以允许达到一个分辨单元)的条件下准确地估计相应像素间的干涉相位。仿真及实测数据的处理结果证明了此方法的有效性。
The conventional interferometric synthetic aperture radar (InSAR) interferometric phase estimation methods are mosth based on interferogram filtering. When the quality of an interferogram is extremely poor due to a large coregistration error, it is difficult for these methods to retrieve the true terrain interferometric phases. Therefore, a method is presented to estimate the InSAR interferometric phase based on the model of weight joint steering vector. In the method, the optimal joint data vector and the weight joint steering vector are construct- ed. Then, the beamforming technique with the steering vector is used to estimate the InSAR interferometric phase. The method takes advantage of the coherence information of neighboring pixel pairs for auto-coregistering SAR images. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the terrain interferometric phase (interferogram) even if the coregistration error reaches one pixel. The effectiveness of the method is verified by simulation data and real data.