The ability of a radar to discriminate in both range and Doppler velocity is completely characterized by the ambiguity function (AF) of its transmit waveform. Mathematically, it is obtained by correlating the waveform with its Doppler-shifted and delayed replicas. We consider the inverse problem of designing a radar transmit waveform that satisfies the specified AF magnitude. This process can be viewed as a signal reconstruction with some variation of phase retrieval methods. We provide a trust-region algorithm that minimizes a smoothed non-convex least-squares objective function to iteratively recover the underlying signal-of-interest for either time- or band-limited support. The method first approximates the signal using an iterative spectral algorithm and then refines the attained initialization based upon a sequence of gradient iterations. Our theoretical analysis shows that unique signal reconstruction is possible using signal samples no more than thrice the number of signal frequencies or time samples. Numerical experiments demonstrate that our method recovers both time- and band-limited signals from even sparsely and randomly sampled AFs with mean-square-error of $1\times 10^{-6}$ and $9\times 10^{-2}$ for the full noiseless samples and sparse noisy samples, respectively.
翻译:雷达在射程和多普勒速度上进行区分的能力完全以其传输波形的模糊功能(AF)为特征。从数学角度讲,它是通过将波形与其多普勒变换和延迟复制相连接而获得的。我们考虑了设计雷达传输波形以满足规定的 AF 音量的反向问题。这个过程可以被看作是信号重建,并在一定程度上改变阶段检索方法。我们提供了一种信任区域算法,将平滑的非convex最小方形目标功能降到最低,以迭接地恢复潜在利益信号,用于有时间或带限制的支持。这种方法首先使用迭代光谱算法将信号与多普勒变换换和延迟复制相连接,然后根据一个梯度序列来完善所实现的初始化。我们的理论分析表明,使用信号样本进行的独特信号重建的可能性不大于信号频率或时间样本数。我们的方法从甚至稀有和随机抽样的AFSM中恢复了时间和带有限信号,而没有平均比例值的信号值为9美元至2美元,而完全的样品为10美元。