Synthetic Aperture Radar（SAR） sensors have important properties on the operational level

since they are capable of acquiring data in all weather conditions

and are not affected by cloud cover or different sunlight conditions.Their advantages have aided the development of SAR techniques.In recent years

SAR systems have acquired data that are used for various tasks

such as imagery fusion

temporal change detection and SAR interferometry（InSAR）.The basis of all these tasks is accurate imagery registration

though the registration accuracy may vary from one task to the other.In addition

the use of an automatic registration procedure is important due to the increasing volumes of SAR data and their use in a wide range of applications.Referring to the problem of automatic SAR imagery registration

researchers of SAR community have developed and applied various imagery-intensity-based and feature-based algorithms.However

their methods have deficiencies.This paper addresses the problem of automatic registration of spaceborne SAR images.The spectral phase of an imagery given by the Fourier transform is an important source of information since it preserves the location of objects;then

registration techniques based on spectral phase information are a suitable solution to overcome the limitations of the general area-based or feature-based automatic registration methods.The application of the Symmetric Phase Only Matching Filtering to Fourier-Mellin Invariant（SPOMF-FMI） descriptors

one of the spectral information based registration methodologies

allows a registration of translated

rotated and scaled imagery.However

this approach has some limitations

such as imagery size restrictions and weak capability of processing non-linear geometric distortions.In this paper

an enhanced automatic registration method and its utility on the registration of spaceborne SAR imagery are investigated.The approach consists of two main steps: coarse registration using a Range-Doppler equation whose parameters come from ephemeris;and fine registration using the enhanced SPOMF-FMI algorithm.The significant advantage of the enhanced SPOMF-FMI is its capability to process non-linear geometric distortions and its relaxed restrictions on imagery size due to imagery sectioning and Kriging interpolation.As a rule

the general SPOMF-FMI algorithm is based on a rigid body transformation used as the global mapping function for the geometric transformation of the sensed imagery.A simple rigid body transformation can not achieve accurate registration of images with non-linear geometric distortions which are introduced by sensor non-linearity and other random factors.With the help of imagery sectioning and Kriging interpolation

this problem can be resolved.Imagery size restriction is another defection of the general SPOMF-FMI procedure;however

it can also be solved by imagery sectioning and Kriging interpolation.The implementations of our method for Radarsat-1 images

ENVISAT-1 ASAR images are validated by the experiments of automatic imagery registration.The results demonstrate that the new approach can achieve sub-pixel registration when dealing with the same sensor SAR images that have the same orbit number within a repeating cycle or the same orbit pass which guarantees similar imagery textures.