An extended sampling-ensemble Kalman filter approach for partial data inverse elastic problems

Inverse problems are more challenging when only partial data available in general. In this paper, we propose a two-step approach combining the extended sampling method and ensemble Kalman filter to reconstruct an elastic rigid obstacle using data. first step, approximate location of unknown is obtained by method. second employed shape. The step guides construction initial particles filter, which critical performance step. Both steps based on same physical model use scattering Numerical examples shown demonstrate effectiveness proposed