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In this paper, we address the problem of source localization and separation using sparse methods over a spherical microphone array. A sparsity based method is developed from the observed data in spherical harmonic domain. A solution to the sparse model formulated herein is obtained by imposing orthonormal constraint on the sparsity matrix. Subsequently, a splitting method based on bregman iteration is used to jointly localize and separate the sources from the mixtures of sources. A joint estimate of location and the separated sources is finally obtained after fixed number of iterations. Experiments on source localization and separation are conducted at different SNRs on the grid database. Experimental results based on RMSE analysis and objective evaluation indicate a reasonable performance improvement when compared to other methods in literature.