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Phase Retrieval for Radar Waveform Optimization

机译:相位检索以优化雷达波形

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摘要

An important problem in radar waveform optimization is the synthesis of discrete time constant modulus signals from Fourier magnitude data. Iterative algorithms for solving this problem have been proposed in the literature, but the algorithms are only applicable in limited cases, and the convergent behavior of these algorithms has not been established. We connect waveform design to the well-studied problem of phase retrieval. This is useful for explaining the success of the proposed iterative methods. We generalize and extend the existing algorithms to handle the case in which the dimensions of the time domain waveform and the frequency domain data are unequal, and we provide a convergence analysis. We also relate the phase retrieval problem to the problem of synthesizing discrete time constant modulus signals from power spectral density (PSD) data, which is different and more appropriate for the waveform design problem. We compare the iterative methods to direct search gradient methods for both problems, and establish that the proposed algorithms can provide comparable performance with reduced computational complexity.
机译:雷达波形优化中的一个重要问题是根据傅立叶幅值数据合成离散时间常数模量信号。文献中已经提出了用于解决该问题的迭代算法,但是该算法仅在有限的情况下适用,并且尚未建立这些算法的收敛行为。我们将波形设计与经过充分研究的相位检索问题联系起来。这对于解释所提出的迭代方法的成功很有用。我们对现有算法进行了概括和扩展,以处理时域波形和频域数据的尺寸不相等的情况,并提供了收敛性分析。我们还将相位检索问题与从功率谱密度(PSD)数据合成离散时间常数模量信号的问题联系起来,该问题是不同的,并且更适合于波形设计问题。我们比较了迭代方法和直接搜索梯度方法对这两个问题的影响,并确定了所提出的算法可以在降低计算复杂度的同时提供可比的性能。

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