Abstract
Abstract
Moving target indication is an important application of radar. With the increasing
demand for application, the ground moving target indication (GMTI) method based on
Synthetic Aperture Radar (SAR) is developing rapidly. Especially, the multi-channel
SAR-GMTI method can take advantage of the multiple channels to suppress the ground
clutter effectively, so it widely used in radar airspace surveillance and remote warning.
But the sample number of multi-channel SAR-GMTI method is heavily large, which
increases the load of A/D converter, data transmission and data storage. In this thesis,
the multi-channel SAR-GMTI methods with limited samples are studied.
In this thesis, the two existing GMTI methods based on the Compressive sensing
theory are analyzed firstly. For the above two methods, the influence of noise is ignored.
To mitigate this problem, a method based on weighted two-dimensional compressed
sensing SAR imaging and moving target indication is proposed. The method makes the
algorithm more close to l0 norm model by means of a weighted way. Thus, it improves
the accuracy and robustness of reconstruction under a condition of low signal to noise
ratio (SNR). In addition, for the cases of the larger redundancy resulted from
double-channel echo data, we propose a novel dual-channel SAR-GMTI method based
on distributed compressed sensing. In the proposed method, dual-channel echo data are
jointly processed, which makes the correlation and redundancy of two channel data be
used, so the sample rate be further reduced.
Keywords: synthetic aperture radar (SAR) ground moving target indication
(GMTI) sparse sampling compressive sensing (CS) distributed compressed
sensing
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