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[Crossref]

F. Mao, W. Gong, and Z. Zhu, “Simple multiscale algorithm for layer detection with lidar,” Appl. Opt. 50(36), 6591–6598 (2011).

[Crossref]
[PubMed]

W. Gong, F. Mao, and J. Li, “OFLID: Simple method of overlap factor calculation with laser intensity distribution for biaxial lidar,” Opt. Commun. 284(12), 2966–2971 (2011).

[Crossref]

P. Sakov and P. R. Oke, “A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters,” Tellus, Ser. A, Dyn. Meterol. Oceanogr. 60(2), 361–371 (2008).

[Crossref]

H. T. Fang and D. S. Huang, “Noise reduction in lidar signal based on discrete wavelet transform,” Opt. Commun. 233(1-3), 67–76 (2004).

[Crossref]

R. N. Miller, M. Ghil, and F. Gauthiez, “Advanced data assimilation in strongly nonlinear dynamical systems,” J. Atmos. Sci. 51(8), 1037–1056 (1994).

[Crossref]

G. Evensen, “Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics,” J. Geophys. Res. 99(C5), 143–162 (1994).

[Crossref]

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[Crossref]

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[Crossref]

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[Crossref]

J. L. Anderson and S. L. Anderson, “A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts,” Mon. Weather Rev. 127(12), 2741–2758 (1999).

[Crossref]

R. Collis, “Lidar: a new atmospheric probe,” Q. J. R. Meteorol. Soc. 92(392), 220–230 (1966).

[Crossref]

F. Rocadenbosch, M. N. Reba, M. Sicard, and A. Comerón, “Practical analytical backscatter error bars for elastic one-component lidar inversion algorithm,” Appl. Opt. 49(17), 3380–3393 (2010).

[Crossref]
[PubMed]

F. Rocadenbosch, C. Soriano, A. Comerón, and J. M. Baldasano, “Lidar inversion of atmospheric backscatter and extinction-to-backscatter ratios by use of a Kalman filter,” Appl. Opt. 38(15), 3175–3189 (1999).

[Crossref]
[PubMed]

G. Evensen, “The ensemble Kalman filter: Theoretical formulation and practical implementation,” Ocean Dyn. 53(4), 343–367 (2003).

[Crossref]

G. Evensen, “Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics,” J. Geophys. Res. 99(C5), 143–162 (1994).

[Crossref]

R. N. Miller, M. Ghil, and F. Gauthiez, “Advanced data assimilation in strongly nonlinear dynamical systems,” J. Atmos. Sci. 51(8), 1037–1056 (1994).

[Crossref]

R. N. Miller, M. Ghil, and F. Gauthiez, “Advanced data assimilation in strongly nonlinear dynamical systems,” J. Atmos. Sci. 51(8), 1037–1056 (1994).

[Crossref]

W. Gong, F. Mao, and J. Li, “OFLID: Simple method of overlap factor calculation with laser intensity distribution for biaxial lidar,” Opt. Commun. 284(12), 2966–2971 (2011).

[Crossref]

F. Mao, W. Gong, and Z. Zhu, “Simple multiscale algorithm for layer detection with lidar,” Appl. Opt. 50(36), 6591–6598 (2011).

[Crossref]
[PubMed]

W. Gong, J. Li, F. Mao, and J. Zhang, “Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition,” Chin. Opt. Lett. 9(5), 050101–050104 (2011).

[Crossref]

R. E. Kalman, “A new approach to linear filtering and prediction problems,” J. Basic Eng. 82(1), 35–45 (1960).

[Crossref]

W. Gong, J. Li, F. Mao, and J. Zhang, “Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition,” Chin. Opt. Lett. 9(5), 050101–050104 (2011).

[Crossref]

W. Gong, F. Mao, and J. Li, “OFLID: Simple method of overlap factor calculation with laser intensity distribution for biaxial lidar,” Opt. Commun. 284(12), 2966–2971 (2011).

[Crossref]

W. Gong, F. Mao, and J. Li, “OFLID: Simple method of overlap factor calculation with laser intensity distribution for biaxial lidar,” Opt. Commun. 284(12), 2966–2971 (2011).

[Crossref]

W. Gong, J. Li, F. Mao, and J. Zhang, “Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition,” Chin. Opt. Lett. 9(5), 050101–050104 (2011).

[Crossref]

F. Mao, W. Gong, and Z. Zhu, “Simple multiscale algorithm for layer detection with lidar,” Appl. Opt. 50(36), 6591–6598 (2011).

[Crossref]
[PubMed]

R. N. Miller, M. Ghil, and F. Gauthiez, “Advanced data assimilation in strongly nonlinear dynamical systems,” J. Atmos. Sci. 51(8), 1037–1056 (1994).

[Crossref]

P. Sakov and P. R. Oke, “A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters,” Tellus, Ser. A, Dyn. Meterol. Oceanogr. 60(2), 361–371 (2008).

[Crossref]

F. Rocadenbosch, M. N. Reba, M. Sicard, and A. Comerón, “Practical analytical backscatter error bars for elastic one-component lidar inversion algorithm,” Appl. Opt. 49(17), 3380–3393 (2010).

[Crossref]
[PubMed]

F. Rocadenbosch, C. Soriano, A. Comerón, and J. M. Baldasano, “Lidar inversion of atmospheric backscatter and extinction-to-backscatter ratios by use of a Kalman filter,” Appl. Opt. 38(15), 3175–3189 (1999).

[Crossref]
[PubMed]

P. Sakov and P. R. Oke, “A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters,” Tellus, Ser. A, Dyn. Meterol. Oceanogr. 60(2), 361–371 (2008).

[Crossref]

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[Crossref]
[PubMed]

F. Rocadenbosch, C. Soriano, A. Comerón, and J. M. Baldasano, “Lidar inversion of atmospheric backscatter and extinction-to-backscatter ratios by use of a Kalman filter,” Appl. Opt. 38(15), 3175–3189 (1999).

[Crossref]
[PubMed]

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[Crossref]
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[Crossref]
[PubMed]

F. Rocadenbosch, M. N. Reba, M. Sicard, and A. Comerón, “Practical analytical backscatter error bars for elastic one-component lidar inversion algorithm,” Appl. Opt. 49(17), 3380–3393 (2010).

[Crossref]
[PubMed]

F. Mao, W. Gong, and Z. Zhu, “Simple multiscale algorithm for layer detection with lidar,” Appl. Opt. 50(36), 6591–6598 (2011).

[Crossref]
[PubMed]

R. N. Miller, M. Ghil, and F. Gauthiez, “Advanced data assimilation in strongly nonlinear dynamical systems,” J. Atmos. Sci. 51(8), 1037–1056 (1994).

[Crossref]

R. E. Kalman, “A new approach to linear filtering and prediction problems,” J. Basic Eng. 82(1), 35–45 (1960).

[Crossref]

G. Evensen, “Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics,” J. Geophys. Res. 99(C5), 143–162 (1994).

[Crossref]

J. L. Anderson and S. L. Anderson, “A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts,” Mon. Weather Rev. 127(12), 2741–2758 (1999).

[Crossref]

G. Evensen, “The ensemble Kalman filter: Theoretical formulation and practical implementation,” Ocean Dyn. 53(4), 343–367 (2003).

[Crossref]

H. T. Fang and D. S. Huang, “Noise reduction in lidar signal based on discrete wavelet transform,” Opt. Commun. 233(1-3), 67–76 (2004).

[Crossref]

W. Gong, F. Mao, and J. Li, “OFLID: Simple method of overlap factor calculation with laser intensity distribution for biaxial lidar,” Opt. Commun. 284(12), 2966–2971 (2011).

[Crossref]

R. Collis, “Lidar: a new atmospheric probe,” Q. J. R. Meteorol. Soc. 92(392), 220–230 (1966).

[Crossref]

P. Sakov and P. R. Oke, “A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters,” Tellus, Ser. A, Dyn. Meterol. Oceanogr. 60(2), 361–371 (2008).

[Crossref]

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