Published in IET Radar, Sonar and Navigation
Received on 4th July 2011
Revised on 25th January 2013
Accepted on 26th February 2013
doi: 10.1049/iet-rsn.2011.0363
ISSN 1751-8784
Single snapshot imaging method in multiple-input
multiple-output radar with sparse antenna array
Fufei Gu
1
, Long Chi
1
, Qun Zhang
1,2
, Feng Zhu
1
1
School of Information and Navigation, Air Force Engineering University, Xi’an 710077, People’s Republic of China
2
Key Laboratory of Wave Scattering and Remote Sensing Information (Ministry of Education), Fudan University,
Shanghai 200433, People’s Republic of China
E-mail: zhangqunnus@gmail.com
Abstract: In this study, a single snapshot imaging method of the moving targets in multiple-input multiple-output (MIMO) radar
with sparse antenna array is proposed. First, a configuration of sparse antenna array is presented and then, on the basis of this, an
imaging method based on compressed sensing theory is put forward. With this method, the image of a moving target can be
achieved via single snapshot imaging processing. It not only can avoid motion compensation processing as required by
conventional inverse synthetic aperture radar imaging, but also can dramatically reduce the number of the antenna elements,
which is a quite large number in the typical configuration of MIMO radar system with linear antenna array. Finally, the
effectiveness of this method is validated by the simulation results.
1 Introduction
With the development of modern radar technology, some
important characteristics of the moving targets can be
obtained for classification and identification by using
high-resolution two-dimensional image. Inverse synthetic
aperture radar (ISAR) is a powerful tool that can provide a
two-dimensional image of a moving target. Nowadays,
ISAR has been applied widely for civil and military
purposes since it can be employed in all weather and day/
night conditions. We all know that the motion
compensation is the first step in the ISAR image
reconstruction process. The motion compensation problem
has received great attentions since the beginning of ISAR
[1]. However, the target being imaged is often engaged in
complicated manoeuvres in real-world ISAR imaging
scenarios. Without a good motion compensation algorithm,
the final ISAR imaging result will be seriously blurred by
using the conventional ISAR imaging processing [2, 3]. To
avoid the complicated motion compensation process, the
technique of real aperture antenna array can be utilised to
reconstruct an image of a manoeuvring target [4–6].
Nevertheless, the physical aperture of a real aperture
antenna array should be large enough to achieve the high
cross-range resolution in this case.
Recently, the multiple-input multiple-output (MIMO) radar
has drawn considerable attention as reported in literatures [7 –
12]. A MIMO radar system is advantageous in two different
scenarios. One is that the transmitting antennas are located
far apart from each other relative to their distance to the
target [7], and the other is that the transmitting antennas
and receiving antennas are close to each other relative to
the target [8]. In the last scenario (we consider this situation
throughout this paper), the phase differences induced by
transmitting and receiving antennas can be exploited to
form a long virtual array and then the same imaging quality
of the real aperture antenna array can be achieved by using
less actual antenna elements [11, 12]. An imaging method
by combinin g MIMO techniques and ISAR imaging theory
has been presented in [11], in which the same cross-range
resolution can be obtained by using few antenna elements
and the coherent processing interval can be reduced
substantially compared with the conventional ISAR
imaging. However, the motion compensation process cannot
be left out in the method. A single snapshot imaging
method with wideband MIMO radar system is proposed in
[12]. With this method, the complex motion compensations
can be avoided because of the parallel sampling with a
single snapshot illumination, but the number of the antenna
is still quite larger. Hence, we intend to find an imaging
method of manoeuvring targets which not only avoids the
motion compensation processing but also reduces the
number of antennas to be practical.
Compressed sensing (CS) theory is a kind of data
compressing and reconstructing theory, which is proposed
by Donoho in 2006 [13]. CS theory enables us to
reconstruct the signals exactly from very limited
measurements with high probability when some specific
conditions are satisfied [13, 14]. Owing to this prominent
advantage, the CS theory has been widely used in many
applications [15, 16]. Meanwhile, the idea of CS has also
been used in some radar systems, such as conventional
radar system [17], imaging radar system [18–21] and
MIMO radar system [22, 23]. A waveform designing
method is put forward to reduce the correlations between
target responses in [22]. In the case of the targets that are
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