One dimensional acoustic direct nonlinear inversion using the Volterra inverse scattering series

• Published in: Inverse problems Vol. 30; no. 7; pp. 75006 - 17
• Main Authors: Yao, Jie, Lesage, Anne-Cécile, Bodmann, Bernhard G, Hussain, Fazle, Kouri, Donald J
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.07.2014
• Subjects: Acoustic scattering; Convergence; direct nonlinear inversion; Inverse scattering; inverse scattering series; Inversions; Mathematical analysis; Mathematical models; Nonlinearity; series summation techniques; Transforms; Volterra renormalization
• ISSN: 0266-5611; 1361-6420
• DOI: 10.1088/0266-5611/30/7/075006

Direct inversion of acoustic scattering problems is nonlinear. One way to treat the inverse scattering problem is based on the reversion of the Born-Neumann series solution of the Lippmann-Schwinger equation. An important issue for this approach is the radius of convergence of the Born-Neumann series for the forward problem. However, this issue can be tackled by employing a renormalization technique to transform the Lippmann-Schwinger equation from a Fredholm to a Volterra integral form. The Born series of a Volterra integral equation converges absolutely and uniformly in the entire complex plane. We present a further study of this new mathematical framework. A Volterra inverse scattering series (VISS) using both reflection and transmission data is derived and tested for several acoustic velocity models. For large velocity contrast, series summation techniques (e.g., Cesàro summation, Euler transform, etc) are employed to improve the rate of convergence of VISS. It is shown that the VISS method with summation techniques can provide a relatively good estimation of the velocity profile. The method is fully data-driven in the respect that no prior information of the model is required. Besides, no internal multiple removal is needed. This one dimensional VISS approach is useful for inverse scattering and serves as an important step for studying more complicated and realistic inversions.