MTRC compensation in high-resolution ISAR imaging via improved polar format algorithm based on ICPF

Abstract

In this paper, we present a detailed analysis on the performance degradation of inverse synthetic aperture radar (ISAR) imagery with the polar format algorithm (PFA) due to the inaccurate rotation center. And a novel algorithm is developed to estimate the rotation center for ISAR targets to overcome the degradation. In real ISAR scenarios, the real rotation center shift is usually not coincided with the gravity center of the high-resolution range profile (HRRP), due to the data-driven translational motion compensation. Because of the imprecise information of rotation center, PFA image yields model errors and severe blurring in the cross-range direction. To tackle this problem, an improved PFA based on integrated cubic phase function (ICPF) is proposed. In the method, the rotation center in the slant range is estimated firstly by ICPF, and the signal is shifted accordingly. Finally, the standard PFA algorithm can be carried out straightforwardly. With the proposed method, wide-angle ISAR imagery of non-cooperative targets can be achieved by PFA with improved focus quality. Simulation and real-data experiments confirm the effectiveness of the proposal.

High sidelobe analysis and reduction in multistatic inverse synthetic aperture radar imaging fusion with gapped data

“…The CS optimisation problem can be described as After solving the sparse vector , can be obtained by The reconstructed echo fusion result of whole target can be obtained by where is the element of vector . Then the traditional ISAR imaging method, such as PFA [25] and RDA [26], can be used for imaging. The sidelobe rising and mainlobe splitting caused by the angle discontinuity will be effectively reduced in the imaging results.…”