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A novel measurement matrix optimization method for radar sparse imaging with OFDM-LFM signals

机译:一种新型测量矩阵优化方法,具有DODM-LFM信号的雷达稀疏成像

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Compressed Sensing (CS) has been widely used in radar imaging field to reduce the data amount. The measurement matrix has direct effect on the degree of dimension reduction and the quality of target image. However, the measurement matrix is usually chosen as random Gaussian matrix or local Fourier matrix, and the influence from target characteristics to the measurement matrix optimization has not been considered. In this paper, focuses on the OFDM-LFM signals, a novel measurement matrix optimization method for radar sparse imaging is proposed. In this method, genetic algorithm is used to implement the measurement matrix optimization by equaling the measurement matrix to the chromosome. And then the satisfied imaging result can be achieved with minimal measurement dimension by using the obtained optimal measurement matrix. Some simulation results illustrate the effectiveness of the proposed method.
机译:压缩传感(CS)已广泛用于雷达成像字段,以减少数据量。测量矩阵对尺寸减小程度和目标图像质量具有直接影响。然而,通常选择测量矩阵作为随机高斯矩阵或局部傅立叶矩阵,并且尚未考虑对测量矩阵优化的目标特性的影响。在本文中,专注于OFDM-LFM信号,提出了一种用于雷达稀疏成像的新型测量矩阵优化方法。在该方法中,遗传算法用于通过将测量矩阵等于染色体来实现测量矩阵优化。然后,通过使用所获得的最佳测量矩阵,可以通过最小的测量维度实现满足的成像结果。一些仿真结果说明了该方法的有效性。

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