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A novel approach of joint gravity and gravity gradient inversion is presented for passive subsurface object detection in this letter. Gravity and gravity gradient anomalies induced by an object can be measured and inversed to estimate the mass, orientation, and distance of the object. The new equations of gravity inversion are explored, and the weighted least squares estimation is constructed. Therefore, the two kinds of data are complementary to each other in the joint inversion via the self-adaptive weights. Simulation results show that the proposed approach is more efficient and robust than the previous gravity gradient tensor inversion.