The Resource A field-wise wind retrieval algorithm for seawinds, by Stephen L. Richards

A field-wise wind retrieval algorithm for seawinds, by Stephen L. Richards

Label
A field-wise wind retrieval algorithm for seawinds
Title
A field-wise wind retrieval algorithm for seawinds
Statement of responsibility
by Stephen L. Richards
Creator
Subject
Genre
Language
eng
Summary
  • In the spring of 1999 NASA will launch the scatterometer SeaWinds, beginning a 3 year mission to measure the ocean winds. SeaWinds is different from previous spaceborne scatterometers in that it employs a rotating pencil-beam antenna as opposed to fixed fan-beam antennas. The scanning beam provides greater coverage but causes the wind retrieval accuracy to vary across the swath. This thesis develops a filed-wise wind retrieval algorithm to improve the overall wind retrieval accuracy for use with SeaWinds data
  • In order to test the field-wise wind retrieval algorithm, methods for simulating wind fields are developed. A realistic approach interpolates the NASA Scatterometer (NSCAT) estimates to fill a SeaWinds swath using optimal interpolation along with linear wind filed models
  • The two stages of the field-wise wind retrieval algorithm are filed-wise estimation and field-wise ambiguity selection. Field-wise estimation is implemented using a 22 parameter Karhunen-Loeve (KL) wind field model in conjunction with a maximum likelihood objective function. An augmented multi-start global optimization is developed which uses information from the point-wise estimates to aid in a global search of the objective function. The local minima in the objective function are located using the augmented multi-start search techniques and are stored as field-wise ambiguities
  • The ambiguity selection algorithm uses a field-wise median filter to select the field-wise ambiguity closest to the true wind in each region. Point-wise nudging is used to further improve the filed-wise estimate using information from the point-wise estimates. Combined, these two techniques select a good estimate of the wind 95% of the time
  • The overall performance of the field-wise wind retrieval algorithm is compared with the performance of the current point-wise techniques. Field-wise estimation techniques are shown to be potentially better than point-wise techniques. The field-wise estimates are also shown to be very useful tools in point-wise ambiguity selection since 95.8%-96.6% of the point-wise estimates closest to the field-wise estimates are the correct aliases
Cataloging source
UPB
Degree
M.S.
Dissertation year
1999
Granting institution
Brigham Young University. Dept. of Electrical and Computer Engineering
Illustrations
illustrations
Index
no index present
Literary form
non fiction
Nature of contents
bibliography
Label
A field-wise wind retrieval algorithm for seawinds, by Stephen L. Richards
Link
http://hdl.lib.byu.edu/1877/etd16
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. 129-131)
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Dimensions
28 cm.
Extent
xvii, 131 p.
Media category
unmediated
Media MARC source
rdamedia
Other physical details
ill.
System control number
(OCoLC)ocn370557447
Label
A field-wise wind retrieval algorithm for seawinds, by Stephen L. Richards
Link
http://hdl.lib.byu.edu/1877/etd16
Publication
Bibliography note
Includes bibliographical references (p. 129-131)
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Dimensions
28 cm.
Extent
xvii, 131 p.
Media category
unmediated
Media MARC source
rdamedia
Other physical details
ill.
System control number
(OCoLC)ocn370557447

Library Locations

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    • Harold B. Lee Library Brigham Young University, Provo, UT, 84602, US
      40.249156 -111.649242
    • BYU-SPECIAL-COLLECTIONSBorrow it
      UT, US
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