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Blind focusing algorithm applied to the acoustic signal of a maneuvering rotorcraft

机译:盲聚焦算法应用于机动旋翼飞机的声信号

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摘要

An algorithm was developed and tested to blindly focus the acoustic spectra of a rotorcraft that was blurred by time-varying Doppler shifts and other effects such atmospheric distortion. First, the fundamental frequency generated by the main rotor blades of a rotorcraft was tracked using a fixed-lag smoother. Then, the frequency estimates were used to resample the data using interpolation. Next, the motion-compensated data were further focused using a technique based upon the phase gradient autofocus (PGA) algorithm. The performance of the algorithm was evaluated by analyzing the increase in the amplitude of the harmonics due to focusing the data. For most of the data, the algorithm focused the harmonics between approximately 10-90 Hz to within 1-2 dB of an estimated upper bound (UB) obtained from conservation of energy and estimates of the Doppler shift. In addition, the algorithm was able to separate two closely spaced frequencies in the spectra of the rotorcraft. The algorithm developed can be used to preprocess data for classification, nulling, and tracking algorithms.
机译:开发并测试了一种算法,以盲目聚焦旋翼机的声谱,该声谱由于时变的多普勒频移和其他影响(如大气失真)而变得模糊。首先,使用固定滞后平滑器跟踪旋翼飞机主旋翼叶片产生的基频。然后,将频率估算值用于通过插值对数据进行重新采样。接下来,使用基于相位梯度自动对焦(PGA)算法的技术进一步对运动补偿数据进行对焦。通过分析归因于数据的谐波幅度的增加来评估算法的性能。对于大多数数据,该算法将谐波集中在从能量守恒和多普勒频移估计得出的估计上限(UB)的大约10-90 Hz之间,在1-2 dB范围内。另外,该算法能够在旋翼飞机的频谱中分离两个紧密间隔的频率。开发的算法可用于预处理数据以进行分类,归零和跟踪算法。

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