OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 37, Iss. 30 — Oct. 20, 1998
  • pp: 7019–7034

Adaptive filter solution for processing lidar returns: optical parameter estimation

Francesc Rocadenbosch, Gregori Vázquez, and Adolfo Comerón  »View Author Affiliations


Applied Optics, Vol. 37, Issue 30, pp. 7019-7034 (1998)
http://dx.doi.org/10.1364/AO.37.007019


View Full Text Article

Enhanced HTML    Acrobat PDF (827 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Joint estimation of extinction and backscatter simulated profiles from elastic-backscatter lidar return signals is tackled by means of an extended Kalman filter (EKF). First, we introduced the issue from a theoretical point of view by using both an EKF formulation and an appropriate atmospheric stochastic model; second, it is tested through extensive simulation and under simplified conditions; and, finally, a first real application is discussed. An atmospheric model including both temporal and spatial correlation features is introduced to describe approximate fluctuation statistics in the sought-after atmospheric optical parameters and hence to include a priori information in the algorithm. Provided that reasonable models are given for the filter, inversion errors are shown to depend strongly on the atmospheric condition (i.e., the visibility) and the signal-to-noise ratio along the exploration path in spite of modeling errors in the assumed statistical properties of the atmospheric optical parameters. This is of advantage in the performance of the Kalman filter because they are often the point of most concern in identification problems. In light of the adaptive behavior of the filter and the inversion results, the EKF approach promises a successful alternative to present-day nonmemory algorithms based on exponential-curve fitting or differential equation formulations such as Klett’s method.

© 1998 Optical Society of America

OCIS Codes
(010.0010) Atmospheric and oceanic optics : Atmospheric and oceanic optics
(010.1290) Atmospheric and oceanic optics : Atmospheric optics
(010.3640) Atmospheric and oceanic optics : Lidar

History
Original Manuscript: September 29, 1997
Revised Manuscript: April 8, 1998
Published: October 20, 1998

Citation
Francesc Rocadenbosch, Gregori Vázquez, and Adolfo Comerón, "Adaptive filter solution for processing lidar returns: optical parameter estimation," Appl. Opt. 37, 7019-7034 (1998)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-37-30-7019


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. R. T. H. Collis, P. B. Russell, “Laser measurement of particles and gases by elastic backscattering and differential absorption,” in Laser Monitoring of the Atmosphere, E. D. Hinkley, ed. (Springer-Verlag, New York, 1976), Chap. 4, pp. 91–102.
  2. R. M. Measures, “Laser-remote-sensor equations,” in Laser Remote Sensing: Fundamentals and Applications (Krieger, Malabar, Fla., 1992), Chap. 7, pp. 237–280.
  3. D. K. Killinger, N. Menyuk, “Laser sensing of the atmosphere,” Science 235, 37–45 (1987). [CrossRef] [PubMed]
  4. A. I. Carswell, “Lidar remote sensing of atmospheric aerosols,” in Propagation Engineering: Third in a Series, L. R. Bissonnette, W. B. Miller, eds., Proc. SPIE1312, 206–220 (1990). [CrossRef]
  5. G. J. Kunz, G. de Leeuw, “Inversion of lidar signals with the slope method,” Appl. Opt. 32, 3249–3256 (1993). [CrossRef] [PubMed]
  6. J. D. Klett, “Stable analytical inversion solution for processing lidar returns,” Appl. Opt. 20, 211–220 (1981). [CrossRef] [PubMed]
  7. R. J. Barlow, Statistics (Wiley, New York, 1989).
  8. J. J. More, “The Levenberg–Marquardt algorithm: implementation and theory,” in Numerical Analysis, Lecture Notes in Mathematics 630, G. A. Watson, ed. (Springer-Verlag, New York, 1977), pp. 105–116.
  9. J. D. Klett, “Lidar calibration and extinction coefficients,” Appl. Opt. 22, 514–515 (1983). [CrossRef] [PubMed]
  10. J. D. Klett, “Lidar inversion with variable backscatter/extinction ratios,” Appl. Opt. 24, 1638–1643 (1985). [CrossRef] [PubMed]
  11. G. J. Kunz, “Probing of the atmosphere with lidar,” in Proceedings of Remote Sensing of the Propagation Environment (AGARD-CP-502), 23, 1–11 (1992).
  12. R. E. Kalman, “A new approach to linear filtering and prediction problems,” J. Basic Eng. 82, 35–46 (1960). [CrossRef]
  13. H. W. Sorenson, Kalman Filtering Techniques. Advances in Control Systems. Theory and Applications (IEEE, New York, 1985), Vol. 3.
  14. R. G. Brown, P. Y. C. Hwang, Introduction to Random Signals and Applied Kalman Filtering (Wiley, New York, 1992).
  15. B. J. Rye, R. M. Hardesty, “Nonlinear Kalman filtering techniques for incoherent backscatter lidar: return power and log power estimation,” Appl. Opt. 28, 3908–3917 (1989). [CrossRef] [PubMed]
  16. D. G. Lainiotis, P. Papaparaskeva, G. Kothapalli, K. Plataniotis, “Adaptive filter applications to LIDAR: return power and log power estimation,” IEEE Trans. Geosci. Remote Sens. 34, 886–891 (1996). [CrossRef]
  17. R. J. McIntyre, “Multiplication noise in uniform avalanche photodiodes,” IEEE Trans. Electron Devices ED-13, 164–168 (1966). [CrossRef]
  18. P. S. Maybeck, Stochastic Models, Estimation and Control (Academic, New York, 1977), Vol. 1.
  19. W. B. Jones, Introduction to Optical Fiber Communication Systems (Holt, Rinehart & Winston, New York, 1988), Chap. 7, 8.
  20. A. Papoulis, Probability, Random Variables and Stochastic Processes (McGraw-Hill, New York, 1991).
  21. D. G. Lainiotis, “Partitioned estimation algorithms. I: Nonlinear estimation,” J. Inf. Sci. 7, 203–255 (1974). [CrossRef]
  22. D. G. Lainiotis, “Partitioning: a unifying framework for adaptive systems. I: Estimation,” Proc. IEEE 64, 1126–1143 (1976). [CrossRef]
  23. H. Koshmieder, “Theorie der Horizontalen Sichtweite,” Beitr. Phys. Freien Atmos. 12, 33–53 (1924).
  24. P. W. Kruse, L. D. McGlauchlin, R. B. McQuiston, Elements of Infrared Technology: Generation, Transmission and Detection (Wiley, New York, 1962).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited