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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 21, Iss. 7 — Apr. 8, 2013
  • pp: 8286–8297

Anti-noise algorithm of lidar data retrieval by combining the ensemble Kalman filter and the Fernald method

Feiyue Mao, Wei Gong, and Chen Li  »View Author Affiliations

Optics Express, Vol. 21, Issue 7, pp. 8286-8297 (2013)

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The lidar signal-to-noise ratio decreases rapidly with an increase in range, which severely affects the retrieval accuracy and the effective measure range of a lidar based on the Fernald method. To avoid this issue, an alternative approach is proposed to simultaneously retrieve lidar data accurately and obtain a de-noised signal as a by-product by combining the ensemble Kalman filter and the Fernald method. The dynamical model of the new algorithm is generated according to the lidar equation to forecast backscatter coefficients. In this paper, we use the ensemble sizes as 60 and the factor δ1/2 as 1.2 after being weighed against the accuracy and the time cost based on the performance function we define. The retrieval and de-noising results of both simulated and real signals demonstrate that our method is practical and effective. An extensive application of our method can be useful for the long-term determining of the aerosol optical properties.

© 2013 OSA

OCIS Codes
(280.1100) Remote sensing and sensors : Aerosol detection
(280.3640) Remote sensing and sensors : Lidar

ToC Category:
Remote Sensing

Original Manuscript: January 14, 2013
Revised Manuscript: March 7, 2013
Manuscript Accepted: March 8, 2013
Published: March 28, 2013

Feiyue Mao, Wei Gong, and Chen Li, "Anti-noise algorithm of lidar data retrieval by combining the ensemble Kalman filter and the Fernald method," Opt. Express 21, 8286-8297 (2013)

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