一种基于扩展卡尔曼滤波和最小均方准则的无控制点InSAR基线估计方法

An InSAR Baseline Estimation Method Based on Extended Kalman Filter and Least Mean Square Error Criterion

基线误差是影响干涉合成孔径雷达(InSAR)测量高精度的主要误差源之一。因此,在进行数字高程图(DEM)高程反演的过程中,需要进行高精度的基线估计来提高DEM数据的精度。文章详细推导了InSAR系统的各项误差与测高精度的关系,得到了误差传播公式;然后提出了一种在扩展Kalman滤波的基础上,使用LMS最小均方误差准则的无控制点基线估计方法。该方法解决了在地面控制点获取困难的条件下,飞行平台与地面之间的相对高度未知的问题。最后,通过仿真实验验证了该方法的有效性:在相位误差、斜距误差、基线长度误差和倾角误差共同作用下,基线定标精度可达到0. 1mm,满足0. 5m相对高程精度对于基线估计的要求。

Baseline error is one of the main sources of error affecting the accuracy of interferometric synthetic aperture radar( InSAR). There for,in the process of digital elevation map( DEM) elevation inversion, high-precision baseline calibration is required to improve the accuracy of DEM data. The study deduces the relationship between various errors and elevation precision of InSAR system and obtain the error propagation formula. Then, an Extended Kalman Filter( EKF)-based baseline estimation approach using the minimum mean square error criterion is proposed. The method solves the problem that the relative height between the flight platform and the ground is unknown under the condition that the ground control point is difficult to acquire. Finally,the effectiveness of the method is verified by simulation experiments,that is,under the combined effect of phase error, slant distance error, baseline length error and inclination error, the baseline calibration accuracy can reach 0. 1 mm,which satisfies the baseline estimation requirement of 0. 5 m relative elevation accuracy.