Method for high-precision distance estimation and dispersion mismatch compensation in frequency scanning interferometry

Hao Pan, Xinghua Qu, Fumin Zhang
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Abstract

The long fiber frequency sampling method has been widely used to eliminate the nonlinearity of laser tuning in the frequency-modulated continuous wave laser ranging technique. Then, fast Fourier transform (FFT) is performed on the resampling signal to obtain the distance spectral information. However, due to the picket fence and leakage of FFT-based methods, it is hard to find the precise location and achieve better range precision. In this paper, we propose a novel frequency estimation method, multiple signal classification (MUSIC), to be used instead of the conventional fast Fourier transform (FFT)-based algorithm to obtain better range precision. In addition, the induced-fiber dispersion could also lead to poor accuracy and precision in the large-bandwidth and long-distance measurements scenes. To solve this problem, a phase compensation method for resolution-enhancement is proposed.
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频率扫描干涉测量中高精度距离估计和色散失配补偿方法
在调频连续波激光测距技术中,长光纤频率采样法被广泛应用于消除激光调谐的非线性。然后对重采样信号进行快速傅里叶变换(FFT),得到距离谱信息;然而,由于基于fft的方法存在尖桩围栏和泄漏,难以找到精确的位置并获得较好的距离精度。在本文中,我们提出了一种新的频率估计方法,即多信号分类(MUSIC),以取代传统的基于快速傅里叶变换(FFT)的算法,以获得更好的距离精度。此外,在大带宽和远距离的测量场景中,诱导光纤色散也会导致精度和精度差。为了解决这一问题,提出了一种增强分辨率的相位补偿方法。
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