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FRI sampling and time-varying pulses: Some theory and four short stories

机译:FRI采样和时变脉冲:一些理论和四个短篇小说

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The field of signal processing is replete with exemplary problems where the measurements amount to time-delayed and amplitude scaled echoes of some template function or a pulse. When the inter-pulse spacing is favorable, something as primitive as a matched filter serves the purpose of identifying time-delays and amplitudes. When the inter-pulse spacing poses an algorithmic challenge, high-resolution methods such as finite-rate-of-innovation (FRI) may be used. However, in many practical cases of interest, the template function may be distorted due to physical properties of propagation and transmission. Such cases can not be handled well by existing signal models. Inspired by problems in spectroscopy, radar, photoacoustic imaging and ultra-wide band arrays, on which we base our case studies, in this work we take a step towards recovering spikes from time-varying pulses. To this end, we re-purpose the FRI method and extend its utility to the case of phase distorted pulses. Application of our algorithm on the above-mentioned case studies results in substantial improvement in peak-signal-to-noise ratio, thus promising interesting future directions.
机译:信号处理领域充满了示例性问题,其中测量等于某些模板函数或脉冲的时延和幅度缩放回波。当脉冲间间隔合适时,诸如匹配滤波器之类原始的东西用于识别时间延迟和幅度。当脉冲间间隔带来算法挑战时,可以使用高分辨率的方法,例如有限创新率(FRI)。但是,在感兴趣的许多实际情况下,模板功能可能会由于传播和传输的物理属性而失真。现有信号模型无法很好地处理此类情况。受光谱,雷达,光声成像和超宽带阵列等问题的启发,我们以案例研究为基础,在这项工作中,我们迈出了从时变脉冲中恢复尖峰的一步。为此,我们重新调整了FRI方法的用途,并将其效用扩展到了相位失真脉冲的情况。我们的算法在上述案例研究中的应用导致峰值信噪比的显着提高,因此有望成为有趣的未来方向。

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