相干目标点稀疏与斑点噪声阻碍了InSAR技术在形变监测中的应用。为了解决这一问题，本文提出了一种新的基于特征值分解和自适应滤波的极化相位优化方法（EVD-FPO）。该方法利用Sentinel-1A双极化数据幅度信息识别DS与PS目标，并基于时空间相干矩阵，利用特征值分解极化相位优化技术和自适应均值滤波技术提高相位质量。为了证明本文方法的可行性与有效性，17景Sentinel-1A双极化（VV-VH）SAR数据用于评估本文方法的性能。结果表明，EVD-FPO方法能够有效提高相干目标点的密度和改善相位质量，相较于单极化振幅离差法（VV- ）和振幅离差极化相位优化方法（ESM- ）相干点目标分别增加了9.06倍和1.64倍，相较于单极化CAESAR方法提取的PS目标更加完整。EVD-FPO方法能够在保护PS目标相位的条件下抑制DS目标相位噪声，相位质量优于ESM- 方法和CAESAR方法。

The sparse coherent target points and speckle noise hinder the application of InSAR technology in deformation monitoring. In order to solve this problem, this paper proposes a new polarimetric phase optimization method (EVD-FPO) based on eigenvalue decomposition and adaptive filtering. This method uses Sentinel-1A dual-polarization data amplitude information to identify DS and PS targets, and based on the temporal and spatial coherence matrix, uses eigenvalue decomposition polarimetric phase optimization technology and adaptive mean filtering technology to improve the phase quality. In order to prove the feasibility and effectiveness of this method, 17 Sentinel-1A dual-polarization (VV-VH) SAR data are used to evaluate the performance of this method. The results show that the EVD-FPO method can effectively increase the density of coherent target points and improve the phase quality. Compared with the single polarimetric amplitude dispersion method (VV- ) and the amplitude dispersion polarimetric phase optimization method (ESM- ), this method increases the coherence point target by 9.06 times and 1.64 times, respectively. Compared with the single-polarization CAESAR method, the PSs extracted is more complete. The EVD-FPO method can suppress the phase noise of the DSs while protecting the phase of the PSs, and the phase quality is better than the ESM- method and the CAESAR method.