Abstract
Due to the spinning target’s distribution on a continuous scene, it is impossible to guarantee that all scatterers are located exactly on the pre-discretized grid. Off-grid problem will lead to the mismatch of sensing matrix, which severely affect the performance of conventional narrow-band radar imaging based on compressed sensing. By reformatting the signal model and improving the sparse recovery algorithm, a robust narrow-band radar imaging method for off-grid spinning targets is proposed. Firstly, an imaging model, considering the gridding error, is developed, which is more close to the distribution of real target. Secondly, we put forward an improved orthogonal matching pursuit algorithm for the optimization of reconstruction, and introduce the nonlinear least squares method to further improve the reconstruction accuracy of scatterers. Finally, the effectiveness of the proposed method is verified by simulation and real data, and the selection rule of grid size is presented by quantitative analysis.
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Acknowledgments
This work was supported in part by the National Natural Science Foundations of China (NSFC) under Grant 61472324 and the Fundamental Research Funds for the Central Universities under Grant NSIY221418. The authors would like to thank the journal manager, the handling editor and the anonymous reviewers for their valuable and helpful comments.
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Sun, C., Wang, B., Fang, Y. et al. Narrow-band radar imaging for off-grid spinning targets via compressed sensing. Multidim Syst Sign Process 28, 1167–1181 (2017). https://doi.org/10.1007/s11045-016-0384-5
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DOI: https://doi.org/10.1007/s11045-016-0384-5