面向植被边坡的地基SAR高相干点选择

基于高相干点进行相位分析，才能有效保证地基SAR（Synthetic Aperture Radar，合成孔径雷达）形变测量的准确性。在差分干涉测量领域中，广泛使用幅度离差法，可以有效地选择出岩石、建筑物等PS（Permanent Scatterer，永久散射体）点作为高相干点，但对于植被边坡，采用该方法选择出高相干点数量较少，不利于差分干涉处理。在星载SAR领域，普遍采用StaMPS方法解决植被边坡的高相干点选择问题。本文探索了StaMPS方法在地基SAR领域的适用性，提出采用非PS点来计算相干系数门限，并引入DS（Distributed Scatterer，分布式散射体）选择技术，进一步提高了高相干点的数量。对一处植被边坡的实验结果表明，相比于幅度离差法和StaMPS方法，改进方法在提高高相干点数量的同时，有效保证了其相位质量。 

High-coherence Pixel Selection of Ground-based SAR for Vegetation Slopes

Phase analysis based on high-coherence points can ensure the accuracy of ground-based SAR （Synthetic Aperture Radar） deformation measurement effectively. In the field of differential interferometry， the amplitude dispersion method is widely used， it can effectively select the PS （Permanent Scatterer） such as rocks and buildings as the high coherence points. However， for the vegetation slopes， the number of high-coherence points selected by this method is small， which is not conducive to differential interferometry. Stanford Method for Persisitent Scatterers （StaMPS） are commonly used in the field of spaceborne synthetic aperture radar （SAR） to solve the problem of high-coherence point selection of vegetation slope. In this paper， the applicability of the StaMPS method in the field of Ground-based synthetic aperture radar is explored， and a non-PS point is proposed to calculate the threshold of coherence coefficient， and a DS （Distributed Scatterer） selection technique is introduced to further improve the number of high coherence points. Experimental results on a vegetation slope show that， compared with the amplitude deviation method and the StaMPS method， the improved method not only increases the number of high coherent points， but also ensures the phase quality effectively.