This documentation supplements a set of Matlab scripts to reconstruct the shape of a two-dimensional rough surface based on scattered acoustic field data. The method is based on the approach introduced by Krynkin et al. (2016) (Krynkin et al., 2016, An airborne acoustic method to reconstruct a dynamically rough surface, J. Ac. Soc. Am. 140(3) (https://doi.org/10.1121/1.4962559). The present implementation is based on the work by Dolcetti et al. (2020) (Dolcetti et al., 2020, Robust Reconstruction of Scattering Surfaces Using a Linear Microphone Array, submitted to Journal of Sound and Vibration). This includes some improvements to the previous algorithms, including a multi-frequency extension aimed at improving the robustness of the reconstruction using broadband data. The algorithms apply to smooth sound-hard rough surfaces that satisfy the applicability of the Kirchhoff approximation. Input data can be either experimental or numerical. Algorithms to create random realisations of a rough surface with a power-function spatial spectrum, and to estimate the corresponding synthetic scattered sound field based on the Kirchhoff approximation, are included, together with a working example.

{"references": ["Dolcetti, G., Alkmim, M., Cuenca, J., De Ryck, L. and Krynkin, A. (2020) Robust reconstruction of scattering surfaces using a linear microphone array. Submitted to Journal of Sound and Vibration", "Krynkin, A., Horoshenkov, K.V. and Van Renterghem, T. (2016) An airborne acoustic method to reconstruct a dynamically rough surface. The Journal of the Acoustical Society of America, 140(3): 2064-2073", "Krynkin, A., Dolcetti, G. and Hunting, S. (2017) Acoustic imaging in application to reconstruction of rough rigid surface with airborne ultrasound waves, Review of Scientific Instruments, 88(2) 024901"]}