Synthetic estimation filters (SEFs) have been found useful for the determination of distortion parameters such as angle of rotation of objects from their images. Previous SEFs, designed using matched and phase-only filters required a knowledge of the exact location of the object to produce reasonable estimation accuracy. To overcome the limitation, use of minimum average correlation energy (MACE) filters is proposed for the construction of SEFs. Because the MACE filters are designed to have their peaks at the origin of the correlation plane, the peak can be detected without a knowledge of the exact position of the object. Computer simulations are used to study the performance of MACE-SEFs. It is found that significant errors result at rotation angles that are not part of the training set. An improved linearity leading to an increase in accuracy was realized when the minimum noise correlation energy (MINACE) concept was used in place of the MACE concept for the design of the SEFs.