17 December 2015 ISAR imaging based on sparse subbands fusion
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Proceedings Volume 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis; 98110D (2015) https://doi.org/10.1117/12.2230202
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Data fusion using subbands, which can obtain a higher range resolution without altering the bandwidth, hardware, and sampling rate of the radar system, has attracted more and more attention in recent years. A method of ISAR imaging based on subbands fusion and high precision parameter estimation of geometrical theory of diffraction (GTD) model is presented in this paper. To resolve the incoherence problem in subbands data, a coherent processing method is adopted. Based on an all-pole model, the phase difference of pole and scattering coefficient between each sub-band is used to effectively estimate the incoherent components. After coherent processing, the high and low frequency sub-band data can be expressed as a uniform all-pole model. The gapped-data amplitude and phase estimation (GAPES) algorithm is used to fill up the gapped band. Finally, fusion data is gained by high precision parameter estimation of GTD-all-pole model with full-band data, such as scattering center number, scattering center type and amplitude. The experimental results of simulated data show the validity of the algorithm.
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Gang Li, Gang Li, Biao Tian, Biao Tian, Shiyou Xu, Shiyou Xu, Zengping Chen, Zengping Chen, } "ISAR imaging based on sparse subbands fusion", Proc. SPIE 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis, 98110D (17 December 2015); doi: 10.1117/12.2230202; https://doi.org/10.1117/12.2230202

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