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Sensors 2018, 18(3), 783; https://doi.org/10.3390/s18030783

A Novel Sidelobe Reduction Algorithm Based on Two-Dimensional Sidelobe Correction Using D-SVA for Squint SAR Images

1
,
2,* and 1
1
Qian Xuesen Laboratory of Space Technology, Beijing 100094, China
2
Beijing Institute of Remote Sensing Information, Beijing 100192, China
*
Author to whom correspondence should be addressed.
Received: 30 January 2018 / Revised: 22 February 2018 / Accepted: 3 March 2018 / Published: 5 March 2018
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Abstract

Sidelobe reduction is a very primary task for synthetic aperture radar (SAR) images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA) filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA) for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method. View Full-Text
Keywords: squint SAR; sidelobe reduction; double spatially variant apodization (D-SVA); non-integer Nyquist sampled imagery; impulse response squint SAR; sidelobe reduction; double spatially variant apodization (D-SVA); non-integer Nyquist sampled imagery; impulse response
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Liu, M.; Li, Z.; Liu, L. A Novel Sidelobe Reduction Algorithm Based on Two-Dimensional Sidelobe Correction Using D-SVA for Squint SAR Images. Sensors 2018, 18, 783.

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