In near-field applications, 3-D imaging with the millimeter-wave multiple-input-multiple-output (MIMO) array provides accurate reconstruction with high dynamic range. However, current algorithms make it difficult to process multidimensional echo data in real-time with ordinary computational power. To improve the imaging speed, the property of the focus position control by closed-form discrete fractional Fourier transform (CF-DFrFT) is used to replace the matched filtering operation. According to the difference of range cell migration correction (RCMC), three improved imaging algorithms based on the CF-DFrFT are proposed in this article. We numerically analyze the CF-DFrFT of different imaging algorithms in terms of imaging computational load and feasibility. The imaging difference is also discussed using simulated data and published actual data. Compared to the fastest known algorithm, the simulation results show that the imaging time of the proposed algorithms is reduced by 38% at most. All the proposed algorithms improve the imaging efficiency while preserving the properties of the original RCMC.

中文翻译：

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基于CF-DFrFT的快速3D毫米波MIMO阵列成像算法

在近场应用中，采用毫米波多输入多输出 (MIMO) 阵列的 3D 成像可提供高动态范围的精确重建。然而，当前的算法很难用普通的计算能力实时处理多维回波数据。为了提高成像速度，利用闭式离散分数傅里叶变换（CF-DFrFT）焦点位置控制的特性来代替匹配滤波操作。根据距离细胞迁移校正(RCMC)的差异，本文提出了三种基于CF-DFrFT的改进成像算法。我们从成像计算量和可行性方面对不同成像算法的 CF-DFrFT 进行了数值分析。还使用模拟数据和已发布的实际数据讨论了成像差异。仿真结果表明，与已知最快的算法相比，该算法的成像时间最多减少了38%。所有提出的算法都提高了成像效率，同时保留了原始 RCMC 的属性。