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从含噪数据中提取信号从而提升数据采集系统精度是极为重要的问题.奇异谱分析(singular spectrum analysis,SSA)作为一种无参数频谱估计技术,广泛用于区分系统模型未知情况下的动态系统信号的复杂成分.本文应用SSA方法提取双光梳飞秒激光测距系统中的含噪时间序列的距离信息,数值仿真显示SSA方法可以从含有有色噪声的信号中提取距离信号.实验中,SSA方法成功地从含有量子噪声的测距信号中提取出激光与目标之间的距离信息,提取后的信号有13倍的精度提升.这种方法同样适用于高维信号,如基于飞秒激光测距的高精度、高速率表面形貌测量的图像提取.Optical methods in distance measurement, which are categorized by interferometry and time-of-flight (TOF) detection, have received widespread attention in recent years. However, interferometry cannot provide absolute distance and traditional TOF measurement cannot obtain a high precision measurement result either. The TOF ranging by femtosecond lasers, a novel precise measurement approach, enabling a sub-micrometer precision for long distance absolute ranging, can solve the problems above and has a wide application prospect in aerospace, remote sensing and surface profilometry. Particularly, a dual-comb ranging approach has attracted great attention due to high update rate (~kHz) and a simple system structure (i.e., working with free running mode-locked laser system). However, the quantum limited timing jitter of mode-locked lasers will inevitably introduce uncertainty into TOF estimation due to the equivalent sampling nature of a dual-comb scheme. As a result, the distance measurement precision is significantly degraded. Even though a simple multiple averaging can be used to alleviate this problem, the measurement speed is limited to a very low level, which is unacceptable to many applications. Moreover, multiple averaging fails in the presence of more complex noise sources. Singular spectrum analysis (SSA), known as a non-parametric spectral estimation technique, has been widely used in dynamic systems to distinguish complex patterns in signals without a priori knowledge of the dynamical model. In this paper, for the first time, we apply SSA to extract distance information from a noisy time series generated by a high update rate dual-comb ranging system. Numerical simulation shows that the SSA is a powerful tool for separating distance series into signal and random noise regardless its color. Specifically, we extract a one-dimensional step profile with high precision in the presence of violet noise (density proportional to f2). In experiment, a dual-comb ranging system is built based on two home-built polarization maintaining mode-locked fiber lasers by using carbon nanotube as saturable absorber. Their repetition rates are both about 74 MHz, their difference being about 2 kHz. We measure the distance of a moving target placed at ~0.5 m away from the range finder and use the SSA for signal extraction. The direct measurement precision is 1.9968 m rms at 200 Hz update rate. The SSA successfully separates the quantum noise from the ranging time series, resulting in 0.1522 m rms ranging precision, corresponding to about 13 times ranging precision improvement. This method can be further extended to high dimension, enabling high precision and high speed profilometry for complex surfaces based on femtosecond laser ranging.
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Keywords:
- femtosecond /
- distance measurement /
- algorithm /
- noise
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[1] Bobroff N 1993 Meas. Sci. Technol. 4 907
[2] Smullin L D, Fiocco G 1962 Nature 194 1267
[3] Minoshima K, Matsumoto H 2000 Appl. Optics 39 5512
[4] Coddington I, Swann W C, Nenadovic L, Newbury N R 2009 Nat. Photonics 3 351
[5] Lee J, Kim Y J, Lee K, Lee S, Kim S W 2010 Nat. Photonics 4 716
[6] Qin P, Chen W, Song Y J, Hu M L, Chai L, Wang C Y 2012 Acta Phys. Sin. 61 240601 (in Chinese) [秦鹏, 陈伟, 宋有建, 胡明列, 柴路, 王清月 2012 物理学报 61 240601]
[7] Xing S J, Zhang F M, Cao S Y, Wang G W, Qu X H 2013 Acta Phys. Sin. 62 170603 (in Chinese) [邢书剑, 张福民, 曹士英, 王高文, 曲兴华 2013 物理学报 62 170603]
[8] Zhang X S, Yi W M, Hu M H, Yang Z H, Wu G H 2016 Acta Phys. Sin. 65 080602 (in Chinese) [张晓声, 易旺民, 胡明皓, 杨再华, 吴冠豪 2016 物理学报 65 080602]
[9] Shi H, Song Y, Liang F, Xu L, Hu M, Wang C 2015 Opt. Express 23 14057
[10] Broomhead D S, King G P 1986 Physica . 20 217
[11] Vautard R, Ghil M 1989 Physica . 35 395
[12] Vautard R, Yiou P, Ghil M 1992 Physica . 58 95
[13] Hassani H, Zhigljavsky A 2009 J. Syst. Sci. Complex. 22 372
[14] Hassani H, Webster A, Silva E S, Heravi S 2015 Tourism Manage. 46 322
[15] Chen Q, van Dam T, Sneeuw N, Collilieux X, Weigelt M, Rebischung P 2013 J. Geodyn. 72 25
[16] Zabalza J, Ren J, Wang Z, Marshall S, Wang J 2014 IEEE Geosci. Remote S. 11 1886
[17] Zabalza J, Ren J, Wang Z, Zhao H, Wang J, Marshall S 2015 IEEE J. Sel. Top. Appl. 8 2845
[18] Zabalza J, Ren J, Zheng J, Han J, Zhao H, Li S, Marshall S 2015 IEEE T. Geosci. Remote 53 4418
[19] Rafert J B, Zabalza J, Marshall S, Ren J 2016 Appl. Spectrosc. 70 1582
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