erenkov luminescence tomography (CLT) has become a novel three-dimensional (3D) non-invasive technology for biomedical applications such as tumor detection, pharmacodynamics evaluation, etc. However, the reconstruction of CLT still remains a challenging task because of the strong absorbing effect and scattering effect of Cherenkov photon transport process. In this study, we proposed a novel robust sparse reconstruction method named look ahead orthogonal matching pursuit (LAOMP) algorithm to improve the robustness and accuracy of reconstruction for CLT instead of traditional OMP algorithm based on a look ahead strategy. To validate the reconstruction performance of LAOMP method, a series of numerical simulations were conducted. The results showed that LAOMP method obtained the higher robustness and accuracy in locating the optical sources compared with the OMP and StOMP algorithms.Cherenkov luminescence tomography (CLT) has become a novel three-dimensional (3D) non-invasive technology for biomedical applications such as tumor detection, pharmacodynamics evaluation, etc. However, the reconstruction of CLT still remains a challenging task because of the strong absorbing effect and scattering effect of Cherenkov photon transport process. In this study, we proposed a novel robust sparse reconstruction method named look ahead orthogonal matching pursuit (LAOMP) algorithm to improve the robustness and accuracy of reconstruction for CLT instead of traditional OMP algorithm based on a look ahead strategy. To validate the reconstruction performance of LAOMP method, a series of numerical simulations were conducted. The results showed that LAOMP method obtained the higher robustness and accuracy in locating