Fast inverse scattering solutions using the distorted Born iterative method and the multilevel fast multipole algorithm

• Published in: The Journal of the Acoustical Society of America Vol. 128; no. 2; pp. 679 - 690
• Main Authors: Hesford, Andrew J., Chew, Weng C.
• Format: Journal Article
• Language: English
• Published: Melville, NY Acoustical Society of America 01.08.2010; American Institute of Physics
• Subjects: Acoustic signal processing; Acoustical Measurements and Instrumentation; Acoustics; Algorithms; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Models, Theoretical; Motion; Numerical Analysis, Computer-Assisted; Physics; Scattering, Radiation; Signal Processing, Computer-Assisted; Sound; Time Factors; Ultrasonics; Multipole field; Inverse scattering; Fast algorithm; Born approximation; Inverse problem
• ISSN: 0001-4966; 1520-8524; 1520-9024; 1520-8524
• DOI: 10.1121/1.3458856

The distorted Born iterative method (DBIM) computes iterative solutions to nonlinear inverse scattering problems through successive linear approximations. By decomposing the scattered field into a superposition of scattering by an inhomogeneous background and by a material perturbation, large or high-contrast variations in medium properties can be imaged through iterations that are each subject to the distorted Born approximation. However, the need to repeatedly compute forward solutions still imposes a very heavy computational burden. To ameliorate this problem, the multilevel fast multipole algorithm (MLFMA) has been applied as a forward solver within the DBIM. The MLFMA computes forward solutions in linear time for volumetric scatterers. The typically regular distribution and shape of scattering elements in the inverse scattering problem allow the method to take advantage of data redundancy and reduce the computational demands of the normally expensive MLFMA setup. Additional benefits are gained by employing Kaczmarz-like iterations, where partial measurements are used to accelerate convergence. Numerical results demonstrate both the efficiency of the forward solver and the successful application of the inverse method to imaging problems with dimensions in the neighborhood of ten wavelengths.