A Comparison of Beat Frequency Estimation Methods for Large Ring Laser

J. Nzumile
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Abstract

Autoregressive (AR2) technique has always been used to estimate frequency of the output signal from Large ring laser. However, the acquisition rate is not at near real time which is the requirement and noise level still challenge the process resulting to errors in the final estimation. A research was done to compare the Autoregressive (AR2) with the counterparts such as Pisarenko, Quinn, Hilbert and Phase looking for a better technique that will estimate the frequency at near real time to minimize errors. Secondary data from G and C – II ring laser were used during the comparison between the techniques and Autoregressive (AR2). Results shows that, the output characteristics from the counterpart does not depict the oscillations of the Earth rotation as expected contrast to that of Autoregressive (AR2) which does. Moreover, there were much deviation from the expected true value for the techniques contrast to that of AR2 which is very minimum. On the other hand, when the C – II data were used, it was observed that both techniques resemble on their output characteristics though AR2 was still better in the acquisition rate expect for Hilbert transform which does not resemble with others. Following the scope of this paper, Autoregressive (AR2) technique still emerge as a favorite frequency estimation technique contrast to the four counterparts due to its robustness, high acquisition rate as well as low noise level.
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大环形激光器拍频估计方法的比较
自回归(AR2)技术一直被用于估计大环形激光器输出信号的频率。然而,获取速率不是接近实时的,这是要求,噪声水平仍然挑战过程,导致最终估计误差。我们进行了一项研究,将自回归(AR2)与Pisarenko、Quinn、Hilbert和Phase等同类方法进行比较,寻找一种更好的技术,可以在接近实时的情况下估计频率,以尽量减少误差。用G和C - II环形激光的二次数据与自回归(AR2)进行比较。结果表明,与自回归(AR2)相比,对应的输出特征不能像预期的那样描述地球自转的振荡。此外,与AR2相比,该技术与预期真值的偏差很大,这是非常小的。另一方面,当使用C - II数据时,可以观察到两种技术的输出特性相似,尽管除了希尔伯特变换之外,AR2在采集率方面仍然更好,这与其他技术不同。在本文的范围内,自回归(AR2)技术由于其鲁棒性、高采集率和低噪声水平,仍然成为与四种同类技术相比最受欢迎的频率估计技术。
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来源期刊
Songklanakarin Journal of Science and Technology
Songklanakarin Journal of Science and Technology Multidisciplinary-Multidisciplinary
CiteScore
1.10
自引率
0.00%
发文量
0
审稿时长
25 weeks
期刊介绍: Songklanakarin Journal of Science and Technology (SJST) aims to provide an interdisciplinary platform for the dissemination of current knowledge and advances in science and technology. Areas covered include Agricultural and Biological Sciences, Biotechnology and Agro-Industry, Chemistry and Pharmaceutical Sciences, Engineering and Industrial Research, Environmental and Natural Resources, and Physical Sciences and Mathematics. Songklanakarin Journal of Science and Technology publishes original research work, either as full length articles or as short communications, technical articles, and review articles.
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