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针对联合像素类的干涉相位估计方法在地形起伏较大时难以获得足够的独立同分布样本准确估计协方差矩阵的问题,该文提出了一种利用原始干涉图像对的观测数据及其复共轭所包含的数据信息来共同构建估计协方差矩阵时所需样本的方法。该方法结合对整个估计窗口内数据矢量的前后向滑窗作处理,将干涉数据的有效视数增加了一倍,有效缓解了在独立同分布样本不足的情况下进行稳健干涉相位估计的问题。仿真数据和实测数据的处理结果表明,在独立同分布样本不足的情况下,可以获得稳健的干涉相位估计。
It is difficult to obtain enough independent co-distribution samples to accurately estimate the covariance matrix when the terrain undulation is large for the co-pixel interferometric phase estimation method. In this paper, we present a new method to estimate the covariance matrix using the original interferometric image pairs, Contains the data information to jointly construct the sample required to estimate the covariance matrix. Combining with the forward and backward sliding window of the data vector in the entire estimation window, this method doubled the effective visual number of the interference data and effectively solved the problem of robust interferometric phase estimation under the condition of independent and identically distributed samples. The processing results of simulation data and measured data show that the robust interferometric phase estimation can be obtained under the condition of independent and identically distributed samples.