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Sar polarimetric data analysis for identification of ships India Geospatial Forum – 14th International Conference February 07-09, 2012, Gurgaon S. Swarajya lakshmi ADRIN, Dept. of Space, Govt. of India 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 Polarization Combinations VV HH HV VH pq – p –transmit q -receive 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 Scattering Mechanisms T11= |hh+vv|2 T22 = |hh-vv|2 T33=2|hv|2 Polarimetric Signature Horizontal Polarization = 0º or 180º Vertical Polarization = 90º Pedestal Height Circular Polarization Elliptical Polarization Linear Polarization Vertical Polarization Linear Polarization Elliptical Polarization Circular Polarization = 0º -45º < < 0º and 0º < < +45º = -45º or +45º Materials & Methods Data Used: Radarsat 2 Acquisition Type Fine Quad Polarisation Product Type SLC Date 22-02-2009 Pixel Spacing 4.733m Swath 25km Approximate Resolution Range: 12m Azimuth: 8m Incidence Angle 20 – 41 degrees Software Used: POLSAR of ESA Methodology Steps Involved 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 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) 3 H Pi log3 Pi i 1 Where, Pi i 3 j 1 j ENTROPY 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 = 0 Isotropic odd bounce anisotropic even bounce = 45 Multiple = 90 Isotropic even bounce 3 1 2 cos1 v11 cos1 v12 cos1 v31 3 P i 1 i i , w here i cos1 vi1 , 0 900 ALPHA vi1 = first element of the ith eigenvector 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 2 3 , 2 3 0 A 1 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. 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 H-Alpha Scattering Plane Classified image depicting water and ships Anomalies in water identified as ships Classified Image Land Ships with typical signatures Class description 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 Polarimetric signatures Polarimetric signatures – ship Proportion (%) of pixels for each class of scattering Class 1 Ship 2 3 4 5 6 7 8 1 3 9 5 60 21 - 4 1 2 3 4 4 2 4 5 8 12 8 5 6 50 56 56 21 18 15 - 6 6 4 7 5 4 Proportion (%) of pixels for each class of scattering Derived Information on Ship Measurements 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. THANKS FOR YOUR KIND ATTENTION