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Under the target's sparse prior condition, the sparse signal recovery algorithm based on compressive sensing (CS) theory can improve the imaging resolution of the inverse synthetic aperture radar (ISAR) with limited observation samples. However, traditional sparse signal recovery algorithm has poor robustness under low SNR. In view of this problem, under the two-dimensional (2-D) ISAR signal model,...
In this paper, a novel computationally efficient algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework, which is based on dichotomous coordinate descent (DCD) iterations, homotopy, and non-convex regularization. Since traditional CS based methods have to assume that unknown scatterers exactly lie on the pre-discretized...
According to the Fourier transform relationship between target scattering function in the space domain and the echoes in the wavenumber domain, the distribution of echoes in the wavenumber domain is inherently linked to both the bandwidth of transmitted signal and the configuration of the illuminators and receivers. Therefore, a multi-aperture passive radar imaging system, which consists of multiple...
We address the problem of three-dimensional (3-D) imaging for multiple-input multiple-output (MIMO) radar in the presence of phase synchronization mismatch between each transmitter-receiver pair. Although usually set to the default values (zero) in the popular practice, such inevitable errors often occur owing to imperfect knowledge of the local oscillators and could seriously deteriorate the imaging...
The assumption, that baseline keeps invariant during the imaging time, is established acquiescently in traditional interferometic ISAR (InISAR) imaging using L-type three antennas structure. However, the baseline often changes more or less in some cases. This paper analyzes the effect of the baseline length variation on interferometic image reconstruction. Besides, the compensated variation range...
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