基于卡尔曼滤波的PS-InSAR地表形变预测方法

PS-InSAR是用于监测大范围地表形变的微波遥感技术,可提供精确地表形变信息,但该技术无法对形变趋势进行预测。现有形变预测方法只能预测少数监测点的形变,不适用于大面积预测。针对这些问题,提出一种基于卡尔曼滤波的PS-InSAR地表形变预测方法。结合PS-InSAR方法的技术流程,从理论上推导设计卡尔曼滤波器,通过真实的多时相SAR数据对该方法进行验证。实验结果表明,该算法可充分利用PS-InSAR形变监测信息,有效预测大面积观测区域的形变趋势。

PS-InSAR surface deformation prediction method based on Kalman filter

PS-InSAR is a microwave remote sensing technique which provides high-resolution maps of large-scale ground displacement. However, it is incapable of deformation prediction. The existing deformation prediction approaches can be only applied to a few point targets, but are limited in monitoring relatively large areas. In this work, a surface deformation prediction method of PS-InSAR is proposed based on Kalman filter. First, the process of PS-InSAR is outlined. Then a Kalman filter is designed theoretically. Finally, the experiments performed on the real multi-temporal SAR data confirm the validity of the proposed method. The experimental results show that the proposed approach makes full use of the displacement information acquired from PS-InSAR and effectively predicts the trend of ground deformation over wide areas.