2016
DOI: 10.2528/pierb16020508
|View full text |Cite
|
Sign up to set email alerts
|

A Modified Ransac Method for Three-Dimensional Scattering Center Extraction at a Single Elevation

Abstract: In this paper, we focus on the 3D SC model reconstruction from data with wide azimuthal aperture at a single elevation. Since the existing method is difficult to implement for high-frequency signal or large-size target, we propose a modified RANSAC method for the extraction. In our approach, the 3D positions of the SCs are estimated from the 1D SCs via a modified RANSAC method. Then the scattering coefficients are refined via a linear least squares algorithm. The approach is robust with noise because the RANSA… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 18 publications
(27 reference statements)
0
1
0
Order By: Relevance
“…This computer algorithm has an unprecedented ability to calculate and deal with images. In the face of image calculation, the image can be analyzed in the form of a matrix, which is accurate and efficient (Zhai Qet al2016) [6] . The computational research of RANSAC algorithm has been applied in practical engineering, which adds a new research path to the computation of image processing in the world (Sheng Het al2016) [7] .…”
Section: State Of the Artmentioning
confidence: 99%
“…This computer algorithm has an unprecedented ability to calculate and deal with images. In the face of image calculation, the image can be analyzed in the form of a matrix, which is accurate and efficient (Zhai Qet al2016) [6] . The computational research of RANSAC algorithm has been applied in practical engineering, which adds a new research path to the computation of image processing in the world (Sheng Het al2016) [7] .…”
Section: State Of the Artmentioning
confidence: 99%