Fast ISAR autofocus algorithm via sub-aperture

Abstract

Translational motion compensation (TMC) is a significant step for inverse synthetic aperture radar (ISAR), while phase autofocus plays an important role in TMC. By eigenvalue decomposition (EVD), principle eigenvectors of the covariance matrix constructed by the complex range-aligned signal can be acquired for ISAR-phase autofocus. Nevertheless, for purpose of enhancing the cross-range resolution, the observation pulse number should be increased. Large observation pulse number will lead to the heavy computational complexity due to EVD, which may overburden the system. To overcome this issue, a novel sub-aperture EVD-based method is proposed here. The full-aperture signal is divided into multiple partially overlapped sub-apertures with a novel partition criterion based on the average range profiles, then the conventional EVD-based methods are utilised to obtain the phase errors in sub-apertures. After the jump-phase compensation, combine the phase-error estimation of all sub-aperture to complete the full-aperture phase autofocus. With this method, the computational efficiency can be improved remarkably in typical scenarios, compared with the traditional autofocus algorithms based on EVD. Finally, results for the simulated data and the real measured data are demonstrated to verify the validity of the proposed algorithm.

Keywords

• radar imaging
• eigenvalues and eigenfunctions
• synthetic aperture radar
• motion compensation
• covariance matrices
• fast isar autofocus algorithm
• translational motion compensation
• tmc
• significant step
• inverse synthetic aperture radar
• eigenvalue decomposition
• principle eigenvectors
• covariance matrix
• complex range-aligned signal
• isar-phase autofocus
• cross-range resolution
• observation pulse number
• heavy computational complexity
• sub-aperture evd-based method
• full-aperture signal
• multiple partially overlapped sub-apertures
• average range profiles
• conventional evd-based methods
• phase errors
• jump-phase compensation
• phase-error estimation
• full-aperture phase autofocus
• computational efficiency
• traditional autofocus algorithms