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RESEARCH PAPER
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Special Issue
SCIENCE CHINA
Information Sciences
August 2012 Vol. 55 No. 8: 1852–1859
doi: 10.1007/s11432-012-4604-9
c
Science China Press and Springer-Verlag Berlin Heidelberg 2012 info.scichina.com www.springerlink.com
Sparse synthetic aperture radar imaging with
optimized azimuthal aperture
ZENG Cao
∗
, WANG MinHang, LIAO GuiSheng & ZHU ShengQi
National Lab of Radar Signal Processing, Xidian University, Xi’an 710071,China
Received November 28, 2011; accepted April 21, 2012; published online June 22, 2012
Abstract To counter the problem of acquiring and processing huge amounts of data for synthetic aperture
radar (SAR) using traditional sampling techniques, a method for sparse SAR imaging with an optimized az-
imuthal aperture is presented. The equivalence of an azimuthal match filter and synthetic array beamforming
is shown so that optimization of the azimuthal sparse aperture can be converted to optimization of synthetic
array beamforming. The azimuthal sparse aperture, which is composed of a middle aperture and symmetrical
bilateral apertures, can be obtained by optimization algorithms (density weighting and simulated annealing
algorithms, respectively). Furthermore, sparse imaging of spectrum analysis SAR based on the optimized sparse
aperture is achieved by padding zeros at null samplings and using a non-uniform Taylor window. Compared
with traditional sampling, this method has the advantages of reducing the amount of sampling and alleviating
the computational burden with acceptable image quality. Unlike periodic sparse sampling, the proposed method
exhibits no image ghosts. The results obtained from airborne measurements demonstrate the effectiveness and
superiority of the proposed method.
Keywords sparse SAR, aperture optimization, beamforming, density weighting, simulated annealing
Citation Zeng C, Wang M H, Liao G S, et al. Sparse synthetic ap erture radar imaging with optimized azimuthal
aperture. Sci China Inf Sci, 2012, 55: 1852–1859, doi: 10.1007/s11432-012-4604-9
1 Introduction
As an all-day, all-weather, long-distance active sensor, a synthetic aperture radar (SAR) [1,2] installed
on an airborne or a space-borne platform acquires real-time remote-sensing information for many civil
and military applications. With faster platform velocities and smaller antenna apertures, the azimuth
bandwidth becomes much broader, thus requiring a higher pulse repetition frequency (PRF). According
to the Nyquist sampling theory, the PRF must be greater than two times the azimuthal bandwidth to
avoid azimuth ambiguity. Thus a dual challenge of obtaining considerable amounts of data with the
associated heavy burden of signal processing is created.
There may be three ways to overcome the challenge. The first way is through uniform or periodic
azimuthal down-sampling [3]; however the former is limited by azimuthal bandwidth and the latter leads
to beamforming grating lobes. A second way, which has received a lot of attention recently [4,5], is by
compressive sensing (CS), i.e., extracting useful information with less sampling data using the sparse
characteristic. CS applied to SAR requires further research in the following areas: (1) how to obtain
∗
Corresponding author (email: czeng@mail.xidian.edu.cn)
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