Publication Date:
2016-07-19
Description:
When a bistatic inverse synthetic aperture radar (ISAR) system fails to collect complete radar cross section (RCS) datasets, bistatic ISAR (Bi-ISAR) images are usually corrupted using the conventional Fourier transform (FT)-based imaging algorithm. To overcome this problem, this paper proposes a new Bi-ISAR image reconstruction method that includes three steps: suboptimal estimation of parameters regarding the bistatic angle in the Bi-ISAR signal model via an orthogonal matching pursuit-type group-searching scheme, Bi-ISAR signal reconstruction using the estimated parameters, and Bi-ISAR image generation using the FT-based imaging algorithm applied to the reconstructed Bi-ISAR signal. To validate the reconstruction capability of the proposed method, bistatic-scattered field data using the physical optics technique as well as the point-scatterer model are used for Bi-ISAR image reconstruction. The results show that the proposed sparse-recovery-interpolation approach based on the Bi-ISAR signal model reconstruction combined with the classical FT-based algorithm can yield high reconstruction accuracy for incomplete bistatic RCS data compared to conventional numerical interpolation methods and existing direct sparse reconstruction techniques.
Print ISSN:
0018-9251
Electronic ISSN:
1557-9603
Topics:
Electrical Engineering, Measurement and Control Technology
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Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
