TY - JOUR
T1 - A ship ISAR imaging algorithm based on generalized radon-fourier transform with low SNR
AU - Ding, Zegang
AU - Zhang, Tianyi
AU - Li, Yong
AU - Li, Gen
AU - Dong, Xichao
AU - Zeng, Tao
AU - Ke, Meng
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - Existing ship inverse synthetic aperture radar (ISAR) imaging algorithms are not applicable, when the signal-to-noise ratio (SNR) is low, for the translational motion that cannot be well compensated by existing algorithms. To achieve ship ISAR imaging with low SNR, a ship ISAR imaging algorithm based on the generalized radon-Fourier transform (GRFT) is proposed in this paper. Considering not only the rotational motion but also the translational motion between the radar and the ship, the proposed algorithm uses the GRFT to simultaneously compensate the time-variant range envelopes and the Doppler phase. Thus, the signal coherence is fully utilized, and the coherent integration of the ship's multicomponent echo signal is realized. Subsequently, to overcome the problem of the heavy computational load and improve the efficiency of the proposed algorithm, the scheme of cascaded GRFTs that consists of the coarse GRFT and the subsequent fine GRFT is adopted. The coarse GRFT with large search ranges and intervals is aimed at obtaining the real ranges of ship scatter points' motion parameters. Based on the coarse GRFT result, the fine GRFT with small search ranges and intervals is performed to efficiently obtain the coherent integration result. Then, based on the coherent integration result, the constant false alarm rate (CFAR) detection is performed to obtain the desired scatter points and their amplitudes and motion parameters, and the multicomponent signal is reconstructed. Finally, based on the reconstructed multicomponent signal, the high-quality instantaneous ship ISAR image can be obtained. Computer simulations and experiment results validate the effectiveness of the proposed algorithm.
AB - Existing ship inverse synthetic aperture radar (ISAR) imaging algorithms are not applicable, when the signal-to-noise ratio (SNR) is low, for the translational motion that cannot be well compensated by existing algorithms. To achieve ship ISAR imaging with low SNR, a ship ISAR imaging algorithm based on the generalized radon-Fourier transform (GRFT) is proposed in this paper. Considering not only the rotational motion but also the translational motion between the radar and the ship, the proposed algorithm uses the GRFT to simultaneously compensate the time-variant range envelopes and the Doppler phase. Thus, the signal coherence is fully utilized, and the coherent integration of the ship's multicomponent echo signal is realized. Subsequently, to overcome the problem of the heavy computational load and improve the efficiency of the proposed algorithm, the scheme of cascaded GRFTs that consists of the coarse GRFT and the subsequent fine GRFT is adopted. The coarse GRFT with large search ranges and intervals is aimed at obtaining the real ranges of ship scatter points' motion parameters. Based on the coarse GRFT result, the fine GRFT with small search ranges and intervals is performed to efficiently obtain the coherent integration result. Then, based on the coherent integration result, the constant false alarm rate (CFAR) detection is performed to obtain the desired scatter points and their amplitudes and motion parameters, and the multicomponent signal is reconstructed. Finally, based on the reconstructed multicomponent signal, the high-quality instantaneous ship ISAR image can be obtained. Computer simulations and experiment results validate the effectiveness of the proposed algorithm.
KW - Generalized radon-Fourier transform (GRFT)
KW - inverse synthetic aperture radar (ISAR) imaging
KW - low signal-to-noise ratio (SNR)
KW - noncooperative ship
UR - http://www.scopus.com/inward/record.url?scp=85072047864&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2019.2905863
DO - 10.1109/TGRS.2019.2905863
M3 - Article
AN - SCOPUS:85072047864
SN - 0196-2892
VL - 57
SP - 6385
EP - 6396
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 9
M1 - 8691556
ER -