A modified ISAR autofocus algorithm based on single eignvector

Phase autofocus is a key step of translational motion compensation (TMC) in inverse synthetic aperture radar (ISAR). In this paper, a modified phase autofocus algorithm is proposed for ISAR to improve the computational efficiency of single eigenvector based autofocusing method. Under the circumstance that a relatively prominent scatterer exists, it is found that the signal subspace can be obtained as an estimation of the phase error caused by target translational motion. In the proposed method, samplings in multiple pulses are used to construct the covariance matrix and obtain the signal subspace, which is equivalent to the existing method with samplings along multiple range bins. Finally, the results of real measured data are provided to demonstrate the effectiveness of the proposed method.