Inverse scattering reconstruction of a three dimensional sound-soft axis-symmetric impenetrable object*The work of JL was partially supported by the Funds for Creative Research Groups of NSFC (No. 11621101) and NSFC Grant No. 11871427. (24th September 2020)

• Record Type: Journal Article
• Authors: Borges, Carlos; Lai, Jun
• Is Part Of: Inverse problems. Volume 36:Number 10(2020)
• Publication Date: 2020-09-24
• Subjects: boundary integral equations -- inverse obstacle problem -- axis-symmetric object -- Helmholtz equation -- recursive linearization; Inverse problems (Differential equations) -- Periodicals; 515.357
• DOI: 10.1088/1361-6420/abac9b
• Languages: English
• ISSNs: 0266-5611

Abstract

Abstract: In this work, we consider the problem of reconstructing the shape of a three dimensional impenetrable sound-soft axis-symmetric obstacle from measurements of the scattered field at multiple frequencies. This problem has important applications in locating and identifying obstacles with axial symmetry in general, such as, land mines. We obtain a uniqueness result based on a single measurement and propose a two-part framework for recovering the shape of the obstacle. In part 1, we introduce an algorithm to find the axis of symmetry of the obstacle by making use of the far field pattern. In part 2, we recover the shape of the obstacle by applying the recursive linearization algorithm (RLA) with multifrequency measurements of the scattered field. In the RLA, a sequence of inverse scattering problems using increasing single frequency measurements are solved. Each of those problems is ill-posed and nonlinear. The ill-posedness is treated by using a band-limited representation for the shape of the obstacle, while the nonlinearity is dealt with by applying the damped Gauss–Newton method. When using the RLA, a large number of forward scattering problems must be solved. Hence, it is paramount to have an efficient and accurate forward problem solver. For the forward problem, we apply separation of variables in the azimuthal coordinate and Fourier decompose the resulting problem, leaving us with a sequence of decoupled simpler forward scattering problems to solve. Numerical examples for the inverse problem are presented to show the feasibility of our two-part framework in different scenarios, particularly for objects with non-smooth boundaries.