An Ensemble Kalman Filter Approach Based on Level Set Parameterization for Acoustic Source Identification Using Multiple Frequency Information (Communications in Mathematical Research, 2022)
In this paper, a reconstruction problem of the spatial dependentacoustic source from multiple frequency data is discussed. Suppose that thesource function is supported on a bounded domain and the piecewise constantintensities of the source are known on the support. We characterize unknowndomain by the level set technique. And the level set function can be modeledby a Hamilton-Jacobi system. We use the ensemble Kalman filter approach toanalyze the system state. This method can avoid dealing with the nonlinearitydirectly and reduce the computation complexity. In addition, the algorithm canachieve the stable state quickly with the Hamilton-Jacobi system. From somenumerical examples, we show these advantages and verify the feasibility andeffectiveness.
Keywords: Level set; data assimilation; acoustic source; EnKF.