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Related Concept Videos

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Spherical coordinate systems are preferred over Cartesian, polar, or cylindrical coordinates for systems with spherical symmetry. For example, to describe the surface of a sphere, Cartesian coordinates require all three coordinates. On the other hand, the spherical coordinate system requires only one parameter: the sphere's radius. As a result, the complicated mathematical calculations become simple. Spherical coordinates are used in science and engineering applications like electric and...
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Polar and Cylindrical Coordinates01:22

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Vectors are usually described in terms of their components in a coordinate system. Even in everyday life, we naturally invoke the concept of orthogonal projections in a rectangular coordinate system. For example, if someone gives you directions for a particular location, you will be told to go a few km in a direction like east, west, north, or south, along with the angle in which you are supposed to move. In a rectangular (Cartesian) xy-coordinate system in a plane, a point in a plane is...
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Viscous forces, like friction, are intermolecular forces that resist the relative motion of molecules over each other. When a solid body moves through a liquid, viscous forces drag it in the opposite direction. The force's magnitude depends on the solid's shape and size, as well as its speed and the liquid's coefficient of viscosity, density and temperature.
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Related Experiment Video

Updated: Apr 3, 2026

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Three-Component Decomposition Based on Stokes Vector for Compact Polarimetric SAR.

Hanning Wang1, Zhimin Zhou2, John Turnbull3

  • 1School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China. wanghanning2012@gmail.com.

Sensors (Basel, Switzerland)
|September 23, 2015
PubMed
Summary
This summary is machine-generated.

A new algorithm decomposes compact polarimetric SAR images using a three-component scattering model. This method, constrained by depolarization, accurately processes scattering components in SAR data.

Keywords:
CTLRDCPStokes vectorcompact polarimetric SARthree-component decomposition

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Area of Science:

  • Remote Sensing
  • Electromagnetics
  • Signal Processing

Background:

  • Compact polarimetric Synthetic Aperture Radar (CP-SAR) data offers enhanced information compared to traditional SAR.
  • Decomposition algorithms are crucial for interpreting complex scattering mechanisms in CP-SAR images.
  • Existing methods may have limitations in accurately separating scattering components.

Purpose of the Study:

  • To propose a novel three-component decomposition algorithm for CP-SAR images.
  • To establish scattering models for Circular Transmit Linear Receive (CTLR) and Dual Circular Polarization (DCP) modes.
  • To validate the algorithm's performance using real-world SAR datasets.

Main Methods:

  • Developed a three-component scattering model by relating the covariance matrix to the Stokes vector.
  • Derived explicit decomposition results with volume scattering contribution as a free parameter.
  • Constrained the free parameter using the degree of depolarization to ensure non-negative scattering component weights.
  • Investigated methods for estimating the free parameter.

Main Results:

  • Successfully established three-component scattering models for CTLR and DCP modes.
  • Derived an explicit expression for decomposition results.
  • Validated the algorithm's feasibility and effectiveness using AIRSAR (San Francisco) and RADARSAT-2 (Flevoland) data.

Conclusions:

  • The proposed three-component decomposition algorithm is effective for processing CP-SAR images.
  • The method provides a robust way to analyze scattering mechanisms by constraining volume scattering.
  • The validated results demonstrate the algorithm's practical applicability in remote sensing applications.