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The airborne gravimetry measurement can better highlight the anomalous response of deeper resources than ground gravity data, so an integrated survey of airborne and ground gravity data is an effective strategy to obtain the obvious response of shallow and deep mineral resources simultaneously. In order to obtain a more reliable and higher resolution 3-D density distribution model through the joint inversion of airborne and ground gravity data to support deeper source exploration, we propose a high-resolution joint inversion method with a cross-constraint technique. We use structural constraints to establish an objective function for joint inversion of airborne and surface gravity data, and add density-weighting constraints through cross-calculation to make full use of the sensitivity of different data and geological targets. Synthetic model tests prove that the cross-constraint joint inversion method of airborne and ground data improves the model resolution effectively, and can delineate the distribution of deeper targets more clearly compared to the existing joint inversion way. In order to predict the spatial distribution of deep ore-bearing rock bodies in a north Qinling area of Shaanxi province, we obtained regional measured airborne and surface gravity data. High-resolution density joint cross-constraint inversion method was used for real data interpretation, and the distribution feature of possible deep ore-forming rock bodies.