TY - JOUR
T1 - Internal wave SAR detection method based on compressive sensing and EMD
AU - Gao, Jianhu
AU - Chen, Jie
AU - Zhang, Lvqian
PY - 2011/12
Y1 - 2011/12
N2 - Spaceborne synthetic aperture radar (SAR) can retrieve the internal wave from detection backscatter of sea surface. Compressive sensing (CS) is adopted for wave sparse sampling to solve the huge amount of echo data. However, in many practical situations, the sparsity of ocean internal wave is corrupted by the influence of noise which causes the reconstructed signal amplitude loss in CS. To solve this problem, an approach of signal reconstruction based on empirical mode decomposition (EMD) is presented. Firstly, the sparsity is enhanced and the noise level is reduced by EMD while maintenance the original signal as possible. Then reconstructed signal by employing the algorithm of orthogonal matching pursuit. Reconstruction results show that the proposed method can effectively suppress noise and improve the sparsity of the signal. Our results also demonstrate that the magnitude loss of the reconstructed signal is reduced, and the convergence speed of orthogonal matching pursuit algorithm is accelerated.
AB - Spaceborne synthetic aperture radar (SAR) can retrieve the internal wave from detection backscatter of sea surface. Compressive sensing (CS) is adopted for wave sparse sampling to solve the huge amount of echo data. However, in many practical situations, the sparsity of ocean internal wave is corrupted by the influence of noise which causes the reconstructed signal amplitude loss in CS. To solve this problem, an approach of signal reconstruction based on empirical mode decomposition (EMD) is presented. Firstly, the sparsity is enhanced and the noise level is reduced by EMD while maintenance the original signal as possible. Then reconstructed signal by employing the algorithm of orthogonal matching pursuit. Reconstruction results show that the proposed method can effectively suppress noise and improve the sparsity of the signal. Our results also demonstrate that the magnitude loss of the reconstructed signal is reduced, and the convergence speed of orthogonal matching pursuit algorithm is accelerated.
KW - Compressive sensing
KW - Empirical mode decomposition
KW - Orthogonal matching pursuit
KW - Sparse sampling
KW - Synthetic aperture radar
UR - https://www.scopus.com/pages/publications/84863022203
M3 - 文章
AN - SCOPUS:84863022203
SN - 0254-3087
VL - 32
SP - 96
EP - 102
JO - Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument
JF - Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument
IS - 12 SUPPL.
ER -