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Spectrally Constrained Waveform Design [sp Tips&Tricks]

机译:频谱受限的波形设计[sp技巧与窍门]

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摘要

In active sensing, transmitters emit probing waveforms into the environment. The probing waveforms interact with scatters that reflect distorted copies of the waveforms. Receivers then measure the distorted copies to infer information about the environment. The choice of the probing waveform is important because it affects slant range resolution, Doppler tolerance, clutter, and electronic countermeasures. A traditional performance metric for the probing waveform is the ambiguity function, which describes the correlation between the waveform and a delayed and (narrowband) Doppler shifted copy of the same waveform [1]. The direct synthesis of a waveform given a desired ambiguity function is exceedingly difficult [2]. Often designers focus on optimizing only the waveform?s autocorrelation function (which is the zero Doppler cut of the ambiguity function). Any method that optimizes the autocorrelation function is implicitly performing spectral shaping by trying to flatten the passband of the waveform?s spectrum [1], [2].
机译:在主动感应中,发射机将探测波形发射到环境中。探测波形与反射波形相互作用的散射交互作用。接收者然后测量失真的副本以推断有关环境的信息。探测波形的选择很重要,因为它会影响倾斜范围分辨率,多普勒容差,杂波和电子对策。探测波形的传统性能指标是模糊度函数,该函数描述了波形与同一波形的延迟和(窄带)多普勒频移副本之间的相关性[1]。给定所需模糊函数的波形的直接合成极其困难[2]。设计人员通常只专注于优化波形的自相关函数(这是模糊函数的零多普勒截止)。任何优化自相关函数的方法都是通过尝试使波形频谱的通带平坦[1],[2]隐式地执行频谱整形。

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    《IEEE Signal Processing Magazine》 |2014年第3期|157-162|共6页
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