High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery

Abstract

Synthetic Aperture Radar (SAR) raw data missing occurs when radar is interrupted by various influences. In order to cope with this problem, a new method is proposed to focus the azimuth missing SAR raw data via segmented recovery in this paper. A reference function in time domain is designed to make the missing raw data sparser in two dimensional frequency domain. Afterwards, greedy algorithms are available to recover the missing data in two dimensional frequency domain. In addition, in order to avoid range frequency aliasing problem caused by reference function multiplication in time domain, the missing raw data is split into several parts in range direction and is recovered with a segmented recovery strategy. Then, the recovered raw data is available to be focused with traditional SAR imaging algorithms. The range migration algorithm is chosen to deal with the recovered raw data in this paper. Point target and area target simulations are carried out to validate the effectiveness of the proposed method on azimuth missing SAR raw data. Moreover, the proposed method is implemented on real SAR data in order to further provide convincing demonstration.