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We consider the problem of imaging a crack network embedded in somehomogeneous background from measured multi-static far field data generated byacoustic plane waves. We propose two novel approaches that can be seen asextensions of linear sampling-type methods and that provide indicator functionswhich are sensitive to local cracks densities. The first approach uses multiplefrequencies data to compute spectral signatures associated with artificiallyembedded localized obstacles. The second approach also exploits the idea ofincorporating an artificial background but uses data for a single frequency.The indicator function is built using a similar concept as for differentialsampling methods: compare the solution of the interior transmission problem forhealthy inclusion with the one with embedded cracks. The performance of themethods is tested and discussed on synthetic examples and the numerical resultsare compared with the ones obtained using the classical factorization method.

Qualitative indicator functions for imaging crack networks using acoustic waves