Abstract
A new CS-based inverse synthetic aperture radar (ISAR) imaging framework is proposed to enhance both the image performance and the robustness at a low SNR. An ISAR echo preprocessing method for enhancing the ISAR imaging quality of compressed sensing (CS) based algorithms is developed by implementing matched filtering, echo denoising and matrix optimization sequentially. After the preprocessing, the two-dimensional (2D) SL0 algorithm is applied to reconstruct an ISAR image in the range and cross-range plane through a series of 2D matrices using the 2D CS theory, rather than converting the 2D convex optimization problem to the one-dimensional (1D) problem in the image reconstruction process. The proposed preprocessing framework is verified by simulations and experiment. Simulations and experimental results show that the ISAR image obtained by the 2D sparse recovery algorithm with our proposed method has a better performance.
Highlights
In the synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR) imaging systems, the range resolution is determined by the bandwidth of the transmitting signal
The range cell migration, which is usually caused by a wide rotation angle, greatly degrades the ISAR imaging quality
We focus on the signal preprocessing framework which has not been used in other papers, and we use some classical methods because we focus on the preprocessing, not the classical methods modification
Summary
In the synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR) imaging systems, the range resolution is determined by the bandwidth of the transmitting signal. The larger the bandwidth is, the better the resolution will be [1]. A large signal bandwidth requires a massive amount of data and an expensive system. The cross-range resolution depends on the total rotation angle of the target during the observation time [1]. The range cell migration, which is usually caused by a wide rotation angle, greatly degrades the ISAR imaging quality. It is hard to achieve a high-resolution ISAR imaging in practice because the imaging quality is limited by a narrow bandwidth and a small aperture
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