Abstarct: Potential field data such as gravity are widely used in the exploration of natural resources, engineering works and archeology. In order to detect and enhance the subsurface targets with potential field data, the variety methods created and used to extract the features of the structure. Usage of gravity gradient tensor (GGT) components rather than the vertical component of the gravity anomalies is more suitable to detect subsurface structures and increases the accuracy of the interpretation. For this reason, many researchers have used the gravity gradient tensors to interpret gravity anomalies, especially for detecting the border of anomalies. In this study, we used gradient tensor components despite of vertical and horizontal gradients of gravity data for interpretation of gravity anomalies due to subsurface bodies. Also, the benefits of using the gravity gradient tensors to detect subsurface anomalies in both synthetic and real data are investigated. For this purpose, a program has been written in MATLAB environment, that calculates the gradient tensor components of gravity data by the Fourier and cosine transforms. The results shows, the components of the gravity gradient tensor are derived from two transforms are suitable, but the cosine transform method is more suitable for the stability against noise. Then another code has written in MATLAB software, which uses the eigenvalues of tensors and tilt derivatives for separating and detecting of gravity anomalies derived from artificial models and real data. In the other hands, this study describes an edge enhancement technique baxsed on the eigenvalues and tilt derivatives obtained from the gravity gradient tensor. The obtained results have shown that the eigenvalues of tensors respect are sensitive to density contrast and they could not detect all of the anomalies alone, so that the zero contours of the small Eigenvalues of GGT only can be delineate edges of bodies have negative density contrast and location of the edges of the anomalous sources. Unlike, the zero contours of the large eigenvalues of gravity gradient tensor only can be delineate edges of bodies have positive density contrast. However, in real geological structures and anomalies at the same time exist both kind of density contrast and this method cannot be used in delineation of edges of causative bodies. To overcome this problem, here have been used improved eigenvalue (IE) of GGT. The improved method can be utilized to outline edges of causative sources in any case. The results from the Applying the tilt derivatives filters on synthetic and real data have shown that the combination of gravity gradient tensor components with tilt angle provide excellent results in determining the edges of anomalous bodies. The θ_x and θ_yhave maximum-minimum pair along the edges that are perpendicular to x and y axis direction, respectively. The filters θ_z and θ_MHChave zero and maximum value on edges of the anomalous bodies, respectively. Both tilt derivatives and IE filters has agreed closely in detecting the horizontal locations of geological features in the subsurface with good precision.