Estimation of Boundary Conditions from Different Experimental Data Using the LTSN Method and Tikhonov Regularization

Mario R. Retamoso, Haroldo F. de Campos Velho and Marco T. Vilhena

Chapter 33 in Integral Methods in Science and Engineering, 2002, pp 209-214 from Springer

Abstract: Abstract The development of inversion methodologies for radiative transfer problems has been an important research topic in many branches of science and engineering [1]. A general methodology for estimating many optical properties in natural waters has been established by using a technique for parameter or function estimation from in situ radiometric measurements. The algorithm is formulated as a constrained nonlinear optimization problem, in which the direct problem is iteratively solved for successive approximations of the unknown parameters. Iteration proceeds until an objective-function, representing the least-squares fit of model results and experimental data, converges to a specified small value. A regularization term is added to the objective function. This implicit algorithm has been applied to identify many properties in inverse hydrological optics (see [2] and [3]). A survey of these results can be found in [4].

Keywords: Nonlinear Optimization Problem; Good Reconstruction; Single Scattering Albedo; Discrete Ordinate; Polar Grid (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-0111-3_33

Ordering information: This item can be ordered from
http://www.springer.com/9781461201113

DOI: 10.1007/978-1-4612-0111-3_33

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().