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NOVEL MIMO SAR FOR URBAN REMOTE SENSING APPLICATIONS 
Wen-Qin Wang 3 ' b ’ *, Qicong Peng a , Jingye Cai a 
a Lab 140, School of Communication and Information Engineering 
University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China 
b Beijing Key Lab of Spatial Information Integration and 3S Application, Peking University, Beijing 100871, China 
- wqwang@uestc.edu.cn 
Youth Forum 
KEY WORDS: Urban Remote Sensing, Synthetic Aperture Radar (SAR), Multiple-input and Multiple-output (MIMO), MIMO 
SAR, MIMO radar, Geographic Information Systems (GIS). 
ABSTRACT: 
The world is experiencing a rapid rate of urban expansion mainly caused by the rapid population growth. Remote sensing images 
can give patterns of urban growth, but urban areas are difficult to map because of the wide range of spectral signatures, sometimes 
combined with the occurrence of mixed pixels. So, some effective new remote sensing means should be developed. Inspired by 
recent advance in multiple-input and multiple-output (MIMO) radar, this paper investigated the applications of MIMO SAR 
(synthetic aperture radar) for urban mapping. The fundamental difference between MIMO SAR and other SAR is that the latter seeks 
to maximize coherent processing gain, while MIMO SAR capitalizes on the diversity of target scattering to improve imaging 
performance. This paper deals with conceptual analysis, as opposed to technological implementation. The system concept, signal 
models, and corresponding processing algorithm are formed. Some potential applications are investigated. It is shown that MIMO 
SAR may provide a satisfied solution to urban remote sensing. 
1. INTRODUCTION 
The world is experiencing a rapid rate of urban expansion 
mainly caused by the rapid population growth together with the 
improved efficiency in the transportation sector and increasing 
dependence on cars. Consequently, changes in land use and 
land cover can transform the habitat and microclimatic patterns. 
Thus, rehabilitating cities, soil and water conservation, 
participatory planning, individual lifestyle changes, are some of 
the measures that can be under-taken to minimize urban sprawl. 
However, the adoption of such new policies requires new 
strategies supported by new tools. In this case, microwave 
remote sensing and geographic information systems (GIS) are 
important tools, because microwave remote sensing images give 
patterns of urban growth, while GISs record data and its 
transformed information support decision making. 
However, urban areas are difficult to map because of the wide 
range of spectral signatures, sometimes combined with the 
occurrence of mixed pixels. Atmospheric effects and temporal 
gaps between different sensors contribute to inaccuracies in 
urban mapping. It is concluded in (Paul, 2007) that urban 
mapping can be improved through: accurate spatial registration, 
appropriate field verification, improved classification 
algorithms, and the use of high spatial and spectral resolution 
satellite imagery. But, even as good as current synthetic 
aperture radar (SAR) techniques, they cannot effectively handle 
the imaging problems of target RCS (radar cross section) 
scintillations, and varying or unstable signatures (Dunn and 
Howard, 1968). But these targets represent an important kind of 
SAR applications dealing with urban mapping. Both 
experimental measurements and theoretical results demonstrate 
that scintillations of 10—15dB in the reflected energy may be 
experienced for a small change in aspect angle (Skolnik, 2002). 
This scintillation will cause degradation in the SAR imagery, 
even make a reliable target detection impossible. 
Inspired by recent advance in multiple-input and multiple- 
output (MIMO) radar (Fishier et al., 2006, Bekkerman and 
Tabrikian, 2006), this paper investigated the applications of 
MIMO SAR for urban mapping. Given that MIMO Radar is in 
its infancy, there is no one clear definition of what it is. It is 
generally assumed that independent signals are transmitted 
through different antennas, and that these signals, after 
propagating through the environment, are received by multiple 
antennas (Forsythe and Bliss, 2005). Generally speaking, 
MIMO radar has two advantages while compared to traditional 
radars: one is diversity, given differences in viewing angles on 
a particular target, the diversity in the scattering response of the 
target can overcome performance degradations caused by RCS 
scintillations (Lehmann et al., 2006) and significantly improve 
parameter identifiability (Li et al., 2007). The second advantage 
is resolution improvement. Due to the significantly larger 
number of degrees-of-freedom of a MIMO system, improved 
resolution can be achieved by coherently processing of multiple 
simultaneous waveforms at multiple receivers. 
Literature search shows that current researches are usually 
focus on transmitter/receiver design, signal detection and 
estimation, and waveform design (Yang and Blum, 2007), but 
little work on the MIMO radar with moving platforms has been 
reported. Even less effort has been placed on MIMO SAR 
(Wang, 2007). We have investigated the system concept of 
MIMO SAR and its advantages over general SAR in (Wang, 
2007). The key aspect of a MIMO SAR is the use of M 
orthogonal waveforms each transmitted from different phase 
centers and N received phase centers. At each of the receive 
phase centers, the received signals are matched filtered for each 
of the transmitted waveforms forming M*N channels. This 
differs substantially from current SAR in which closely spaced