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Terahertz radar coded-aperture imaging technology can achieve high-resolution, forward-looking and staring imaging by producing spatiotemporal independent signals in the imaging area. Sparse reconstruction algorithm is efficient in the point target imaging, whereas it becomes invalid for complex area targets. This paper proposes a method combining wavelet transform and orthogonal matching pursuit...
This paper presents a method for imaging of moving targets via the compress sensing by treating the imaging as a problem of signal representation in an over-complete dictionary. The essential idea behind sparse signal representation models comes from the fact that SAR ground moving targets are sparsely distributed in the observation scene and the received SAR echo is decomposed into the sum of basis...
There is an increasing interest in high-resolution radar imaging of objects, and recent developments of terahertz sensing techniques provide the depiction ability of objects in detail. In this paper, the compressed sensing theory is introduced to terahertz radar imaging. A terahertz radar azimuth-elevation imaging scheme based on block sparse Bayesian learning framework is proposed. By exploiting...
This paper presents a SAR raw data simulation approach using the inverse frequency scaling algorithm (IFSA) based on deramp processing. It is time-saving and can take motion error into account. The limitation of the inverse chirp scaling algorithm (ICSA) on transmitted waveforms is also overcome. Simulated results show the validity of the algorithm.
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