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Wang Y.,National Key Laboratory of Microwave Imaging Technology MITL | Wang Y.,CAS Institute of Electronics | Du L.,National Key Laboratory of Microwave Imaging Technology MITL | Du L.,CAS Institute of Electronics | And 7 more authors.
Eurasip Journal on Advances in Signal Processing | Year: 2010

This paper presents a three-dimensional (3D) range migration algorithm (RMA) suitable for downward-looking 3D-SAR with single-transmitting and multiple-receiving linear array antennas (STMR-LAA). As the round-trip range equation in 3D-SAR with STMR-LAA is a dual square root, the signal spectrum in 3D wavenumber domain contains nonlinear phase terms besides constant and linear phase terms. In this paper, the approximate expression of the signal spectrum is derived by expanding the implicit phase term to its Taylor series. Then the constant and nonlinear phase terms are calculated and compensated by multiplying the wavenumber filters. Finally, a 3D wavenumber mapping is proposed to make the signal evenly sampled in 3D wavenumber domain. Some simulating results are presented to validate the correctness of the analysis and the feasibility of the algorithm. In addition, the required accuracy on the platform position is analyzed at the end of the paper. © 2010 Lei Du et al.


Jiang H.,National Key Laboratory of Microwave Imaging Technology MITL | Jiang H.,CAS Institute of Electronics | Jiang H.,University of Chinese Academy of Sciences | Zhang B.,National Key Laboratory of Microwave Imaging Technology MITL | And 9 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2010

Recent theory of compressed sensing (CS) suggested that exact recovery of an unknown sparse signal can be achieved from few measurements with overwhelming probability. In this paper, we combine CS technology with a random noise SAR and proposed the concept of random noise SAR based on CS. The block diagram of the radar system and the collected data processing procedure was presented. Theoretic analysis show that the sensing matrix of the random noise SAR exhibits good restricted isometry property (RIP). When the target scene is sparse or sparse in any basis, the random noise radar based on CS can get high accuracy image by collecting far less amount of echo data than traditional noise radar does. The conclusions are all demonstrated by simulation experiments. © 2010 IEEE.


Lin Y.,National Key Laboratory of Microwave Imaging Technology MITL | Lin Y.,CAS Institute of Electronics | Lin Y.,University of Chinese Academy of Sciences | Zhang B.,National Key Laboratory of Microwave Imaging Technology MITL | And 7 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2010

This paper analyses ambiguity suppression caused by multiple-input multiple-output (MIMO) SAR azimuth nonuniform samplings. Two methods are analyzed: azimuth spectrum reconstruction algorithm and minimum mean square error (MMSE) imaging algorithm. The azimuth spectrum reconstruction algorithm can reconstruct the scene fine resolution, while the nonideal orthogonality of multichannel encoding waveforms causes azimuth ambiguous in SAR imaging. The MMSE imaging algorithm can perfectly reconstruct, while it requires high SNR. © 2010 IEEE.

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