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Sar polarimetric data analysis for identification of ships S. Swarajya lakshmi ADRIN, Dept. of Space, Govt. of India India Geospatial Forum – 14 th International.

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Presentation on theme: "Sar polarimetric data analysis for identification of ships S. Swarajya lakshmi ADRIN, Dept. of Space, Govt. of India India Geospatial Forum – 14 th International."— Presentation transcript:

1 Sar polarimetric data analysis for identification of ships S. Swarajya lakshmi ADRIN, Dept. of Space, Govt. of India India Geospatial Forum – 14 th International Conference February 07-09, 2012, Gurgaon

2 Objectives Exploitation of polarimetric SAR data for detection of ships Understanding the scattering mechanisms of ships through decomposition Feasibility for deriving additional information for identification and classification of ships

3 pq – p –transmit q -receive Polarization Combinations VV HH VH HV

4 Polarimetry : Information Content As compared to single-polarization SAR, polarimetric SAR provides additional information on: Type of scatterer: Trihedral, dihedral, dipole etc. Orientation of the scatterer about the radar line of sight Ellipticity: degree of scatterer symmetry Entropy: significance of the polarimetric information Therefore, enables better characterization of the target

5 T 11= |hh+vv| 2 T 22 = |hh-vv| 2 T 33 =2|hv| 2 Scattering Mechanisms

6 Pedestal Height Circular Polarization Elliptical Polarization Linear Polarization Vertical Polarization Horizontal Polarization  = 0º or 180º Vertical Polarization  = 90º Linear Polarization  = 0º Elliptical Polarization -45º <  < 0º and 0º <  < +45º Circular Polarization  = -45º or +45º Polarimetric Signature

7 Radarsat 2 Acquisition TypeFine Quad Polarisation Product TypeSLC Date Pixel Spacing4.733m Swath25km Approximate ResolutionRange: 12m Azimuth: 8m Incidence Angle20 – 41 degrees Materials & Methods Data Used: Software Used: POLSAR of ESA

8 Methodology

9 1.Input SLC data 2.Sinclair Matrix – Shh, Shv, Svh, Svv 3.Extracting Different Target Descriptors – Stokes matrix, Covariance Matrix, Cherence Matrix 4.Speckle Filtering 5.Polarimetric Parameter Extraction – Total Power, Entropy, Alpha, Anisotropy, Degree of Polarisation, Eigen Analysis parameters etc. 6.Extracting Polarimetric signatures 7.Polarimetric Synthesis 8.Polarimetric Decomposition and Classification 9.Separation of Land and Water 10.Identification of anomalies in water 11.Identification of ships 12.Further characterisation of ships with respect to polarimetric parameters Steps Involved

10 ENTROPY Eigen Values: Three eigen values of the 3x3 Coherency matrix λi represent the intensities of the three main scattering mechanisms Probabilities Pi of each scattering mechanism Entropy (H) This is a measure of the dominance of a given scattering mechanism within a resolution cell. Entropy ranging from 0 to 1, represents the randomness of a scattering medium from isotropic scattering (H=0) to totally random scattering (H=1) Where, Entropy

11 ALPHA If the Entropy is close to 0, the alpha angle provides the nature or type of the dominant scattering mechanism for that resolution cell. For example it will identify if the scattering is volume, surface or double bounce. anisotropic odd bounce anisotropic even bounce Isotropic even bounce Isotropic odd bounce  = 45   = 0   = 90  Multiple = first element of the i th eigenvector Alpha

12 Anisotropy (A) This is the measure of how homogeneous a target is relative to the radar look direction. For example, the Amazon forest is a very homogeneous target and would have a low anisotropy value. In contrast, row crops would have a high anisotropy value. A indicates the distribution of the two less significant eigenvalues Anisotropy becomes 0 if both scattering mechanisms are of an equal proportion; values of A > 0 indicates increasing amount of anisotropic scattering.

13 Target Decomposition Analysis methods whereby individual scattering components that have meaningful physical interpretation can be identified in the received signal. Scattering matrix is decomposed into sub-matrices so that Individual component have physical meaning => Surface scatterer, double bounce, volume scattering

14 H-Alpha Scattering Plane

15 Classified image depicting water and ships Land Ships with typical signatures Classified Image Anomalies in water identified as ships

16 Class description

17 Scattering Mechanisms with respect to the ships identified Turbulence of water Boundary between water & metallic ship body Ship structure Objects causing strong double bounce scattering

18 Polarimetric signatures

19 Polarimetric signatures – ship

20 Proportion (%) of pixels for each class of scattering Class Ship

21 Proportion (%) of pixels for each class of scattering

22 Derived Information on Ship Measurements

23 Conclusions &Way Forward  Typical scattering mechanisms were observed to be associated with the ships, which could be used towards automated detection and characterization of ships.  Potential of the polarimetric data cold be further explored with multi-parametric decomposition schemes and tested with a wide variety of ships.

24 THANKS FOR YOUR KIND ATTENTION


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