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研究ISAR成像模型,针对MUSIC(多信号分类)成像算法中运算量大、分辨门限高,且散射点数目难以确定等局限性,提出基于波束空间的MUSIC(BMUSIC)超分辨成像算法。利用新的盖世圆盘方法准确判定散射点数目,通过波束空间处理,有效地降低了计算复杂度,同时抑制了噪声影响。理论分析和仿真结果表明,该方法在提高计算效率的同时,减小了算法对噪声的敏感度,改善了成像质量。
To study the ISAR imaging model, this paper proposes a MUSIC (BMUSIC) super-resolution imaging algorithm based on beam space for the limitations of MUSIC (multi-signal classification) imaging algorithm, such as high computational complexity, high resolution threshold, and difficult to determine the number of scattering points. Using the new Gai disc method to accurately determine the number of scattering points, the beam space processing, effectively reducing the computational complexity, while suppressing the noise impact. Theoretical analysis and simulation results show that this method not only increases the computational efficiency, but also reduces the sensitivity of the algorithm to noise and improves the imaging quality.