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Joint-Time-Frequency Gaussian-Chirplet Procesing Of Coherent Ladar Returns From Resolved Vibrating Diffuse Surfaces

机译:连贯的激光乐队的关节时间频率和高斯 - 啁啾加工从分辨的振动漫射表面返回

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Of the standard JTFT's found in the literature, the Born-Jordan JTFT has been shown to be the best for the suppression of local oscillator laser noise while preserving the target signature in CW coherent ladar applications. The JTFT's are superior to spectrogram algorithms but at the cost of additional computation. Processing of the JTFT image (or spectrogram image) maxima at each time point was found to be superior to processing the centroid at each time point. The centroid calculation is biased toward 0 Hz, particularly at low CNR levels. Sinusoidal-FM processing is degraded by the random location of speckle maxima not being near the frequency excursion maxima points where most of the information lies. Linear-FM homodyne (stretch processing) allows a simple summation in time because all the random speckle maxima lie along two frequencies only, resulting in a robust range estimate nearly unaffected by speckle. The Bom-Jordan JTFT tested allows high frequency and temporal resolution of the target spectra. The well resolved time length of the speckle maxima allow an estimate to be made of the target's spectral width, which is due to the spin rate x cross-range dimension in unresolved target scenarios. Given additional information of one of these parameters, the second can be estimated. Resolved target vibration spectra due to piston and higher order mechanical vibration modes can also be efficiently processed for use in autonomous target identification applications. Finally, we note that the technique of Gaussian-chirplet decomposition of a CW coherent ladar's output signal appears to be about as good, with respect to LO noise suppression and signature fidelity, as the Born-Jordan JTFT. This wavelet-like approach is being studied in terms of target feature extraction and target vibration signature construction. The number of numerical operations appears to be less than that of the various JTFT's depending on parameter settings, but is under investigation.
机译:在文献中的标准JTFT的中,Born-Jordan JTFT已被证明是抑制本地振荡器激光噪声的最佳,同时在CW连贯的LADAR应用中保持目标签名。 JTFT的谱图算法优于频谱图算法,但额外的计算成本。发现每个时间点的JTFT图像(或频谱图图像)最大值优于处理每个时间点的质心。质心计算偏向0Hz,特别是在低CNR水平。 SinUnoidal-FM处理因散斑最大值的随机位置而没有靠近频率偏移最大值点的随机位置,其中大多数信息呈现。 Linear-FM Homodyne(拉伸处理)允许简单的求和,因为所有随机散斑最大值仅沿两个频率躺在两个频率,导致稳健的范围估计几乎不受斑点的影响。 BOM-JORDAN JTFT测试允许对目标光谱的高频和时间分辨率进行高频和时间分辨率。散斑最大值的良好分辨的时间长度允许估计是目标的光谱宽度,这是由于未解决目标场景中的旋转速率x交叉范围维度。给出了这些参数之一的附加信息,可以估计第二个参数。也可以有效地处理由于活塞和高阶机械振动模式引起的分辨目标振动谱用于自主目标识别应用。最后,我们注意到CW相干LDAR的输出信号的高斯 - 啁啾分解技术似乎与LO噪声抑制和签名保真度一样好,作为出生的Jordan JTFT。在目标特征提取和目标振动特征结构方面正在研究这种类似的方法。根据参数设置,数值操作的数量似乎小于各种JTFT的数量,而是正在调查中。

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