The Race to Improve Radar Imagery: An overview of recent progress in statistical sparsity-based techniques by Zhao, Lifan, Wang, Lu, Yang, Lei, Zoubir, Abdelhak M., Bi, Guoan

“…More recent developments in compressed sensing (CS) suggest that statistical sparsity can lead to further performance benefits by imposing sparsity as a statistical prior on the considered signal. …”
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An autofocus technique for high-resolution inverse synthetic aperture radar imagery by Zhao, Lifan, Wang, Lu, Yang, Lei, Bi, Guoan

“…For inverse synthetic aperture radar imagery, the inherent sparsity of the scatterers in the range-Doppler domain has been exploited to achieve a high-resolution range profile or Doppler spectrum. …”
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Robust frequency-hopping spectrum estimation based on sparse bayesian method by Wang, Lu, Zhao, Lifan, Bi, Guoan, Zhang, Liren, Zhang, Haijian

“…Inspired by the sparse Bayesian learning algorithm, the problem is formulated hierarchically to induce sparsity. In addition to the sparsity, the hopping pattern is exploited via temporal-aware clustering by exerting a dependent Dirichlet process prior over the latent parametric space. …”
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Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling by Meng, Dandan, Wang, Xianpeng, Huang, Mengxing, Shen, Chong, Bi, Guoan

“…Due to the use of the whole received data of array and the enhanced sparsity of solution, the proposed method effectively avoids the loss of the array aperture to achieve a better estimation performance in the environment of unknown mutual coupling in terms of both spatial resolution and accuracy. …”
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An improved auto-calibration algorithm based on sparse Bayesian learning framework by Zhao, Lifan, Bi, Guoan, Wang, Lu, Zhang, Haijian

“…In this algorithm, signal and perturbation are iteratively estimated to achieve sparsity by leveraging a variational Bayesian expectation maximization technique. …”
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Alternative to extended block sparse Bayesian learning and its relation to pattern-coupled sparse Bayesian learning by Wang, Lu, Zhao, Lifan, Rahardja, Susanto, Bi, Guoan

“…Due to entanglement of the hyperparameters, a joint sparsity assumption is made to yield a suboptimal analytic solution. …”
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Direction of Arrival Estimation for MIMO Radar via Unitary Nuclear Norm Minimization by Wang, Xianpeng, Huang, Mengxing, Wu, Xiaoqin, Bi, Guoan

“…In addition, the real-valued NC-MUSIC spectrum is used to design a weight matrix for reweighting the nuclear norm minimization to achieve the enhanced sparsity of solutions. Finally, the DOA is estimated by searching the non-zero blocks of the recovered matrix. …”
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