Lasers, Fiber Optics, and Communications

Performance of estimated Doppler velocity by maximum likelihood based on covariance matrix

[+] Author Affiliations
Yanwei Wu, Pan Guo, Siying Chen, Yinchao Zhang, He Chen

Beijing Institute of Technology, School of Optoelectronics, Laser Radar Laboratory, No. 5, Zhongguancun South Street, Haidian District, Beijing 100081, China

Opt. Eng. 55(9), 096112 (Sep 29, 2016). doi:10.1117/1.OE.55.9.096112
History: Received May 26, 2016; Accepted August 31, 2016
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Abstract.  This paper investigates the efficient estimator of echo data processing to clean the spectrum through the denoising process. The maximum likelihood based on covariance matrix (MLCM) method without a priori knowledge of the spectral width is proposed for denoising the atmospheric signal. This method is applied to simulated and actual data to estimate the spectrum parameters. The probability density function of estimators as an empirical model is used to describe the performance of the estimators. The MLCM method is suggested to be an alternate estimator to precisely obtain the essential spectrum parameters with a lower standard deviation of good estimators and a larger detected range, which is improved by 20%, compared with the maximum likelihood method with a priori knowledge of the spectral width. Moreover, it can reduce the large velocity volatility and the uncertainties of the spectral width in the low signal-to-noise ratio regime. The MLCM method can be applied to obtain the whole wind profiling by the coherent Doppler lidar.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Yanwei Wu ; Pan Guo ; Siying Chen ; Yinchao Zhang and He Chen
"Performance of estimated Doppler velocity by maximum likelihood based on covariance matrix", Opt. Eng. 55(9), 096112 (Sep 29, 2016). ; http://dx.doi.org/10.1117/1.OE.55.9.096112


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