极化干涉SAR（PolInSAR）估计的复相干性包含相干性幅度和干涉相位，相干性幅度高低可以衡量干涉相位的质量，干涉相位是散射目标相位中心位置的重要体现，相干性幅度和干涉相位估计精度决定植被参数反演精度。由不同极化状态构成的相干区域中，相干性幅度差最大和干涉相位差最大的估计准则都从复相干性的某一方面建立最优估计函数，不能有效利用相干性幅度和相位信息。本文以相干区域边界为基础，结合相干性幅度和干涉相位信息，利用关联度建立联合干涉相位和相干性幅度的最优相干性估计准则，并在相干区域范围内获取最优散射机制及其相干性。试验结果表明，联合干涉相位和相干性幅度的最优估计准则可以有效区分地表散射和森林冠层散射的相干性和散射中心，提高植被高反演的可靠性。
The complex coherence of polarimetric synthetic aperture radar interferometry (PolInSAR) includes the magnitude and phase. The magnitude of coherence is used to measure the quality of the interference phase, and phase center represents the position of the scattering. So, how to improve the accuracy of the coherence magnitude and phase is very important for the forest parameters inversion. Maximum difference of the coherence magnitude or maximum separation of the phase, based on the coherence region, is considered partial information of the complex coherence. In this paper, a new method of coherence optimization, combined with the coherence magnitude and phase information, is established with relational degree. Applied the new approach to estimate the optimal coherence, the optimal polarimetric state of the scattering can be obtained to estimate the optimization coherence. Experimental results show that the optimal coherence criterion, jointed coherence magnitude and phase, can effectively distinguish the phase center of surface scattering and the forest canopy, and improve the reliability of the forest height inversion.
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