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WE3.L09 - EVALUATION OF SYSTEM POLARIZATION QUALITY FOR POLARIMETRIC SAR IMAGERY AND TARGET DECOMPOSITION
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WE3.L09 - EVALUATION OF SYSTEM POLARIZATION QUALITY FOR POLARIMETRIC SAR IMAGERY AND TARGET DECOMPOSITION

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  • The idea is to consolidate the interacting distortions and, more importantly, isolate the system characteristics from specific targets.
  • Combine the distortions and simplify the system equation into its vector form (D is a 4x4 matrix, and S is a 4-element vector) View the system as linear transformation Evaluate the bias in the whole target space
  • Considering the natural, reciprocal targets, the vector of target response is represented as its feature vector. A4 is a 4x3 adapter matrix
  • It becomes easier to analyze the impact of different distortions. Next, we can visualize the relation between the MNE and a specific distortion.
  • We can view the contours as the projection of possible measurement errors in terms of the distortion. Both the phase and the magnitude need to be carefully calibrated.
  • With this distortion structure, there is a linear relation between MNE and the isolation level.
  • The residue Faraday angles should be less than 3 deg.
  • Polarimetric decomposition methods provide valuable tools to understand the scattering mechanisms of the targets. How would the decomposition methods alter the metrics? Or in other words, what is the specific needs for the error budgets for a given decomposition method? Even though the MNE is invariant to orthogonal basis change, the error budget will be different if the decomposition bases are not orthogonal. This evaluation framework cannot be applied to covariance matrix based decompositions where the decomposition bases undefined.
  • From now on, we will check the decomposition errors which vary with the decomposition methods. A tight upper bound: targets corresponding to the maximum error exist in natural scene. Over the whole image, the relative strength of the three decomposition channels keeps intact. Viewed as composition image, the target scene has little perceivable difference. Quantifying individual channel
  • Large biases appear in both double bounce and helix scattering channels. Double bounce: actually oriented di-plane.
  • For the covariance derived decomposition, we have to resort to the typical targets, like those representing the canonical scattering mechnisms.
  • Given these different behaviors in response to polarization distortions, we are thinking whether the MNE can be used as a baseline even for polarimetric decompositions.
  • We take the targets from the E-SAR image for the three canonical scattering mechanisms, and set a wide practical polarization artifacts, then simulate the decomposition errors and check them against the MNE metric.
  • The MNE seems form a good baseline for the quality assessment, for PolSAR imagery and its decompositions. For Krogager decomposition, we may need more attention on the phase terms of the cross-talk terms. For Freeman-Durden decomposition, the interpretation may be problematic if the evaluated MNE is higher. But we can find a general boundary of -25 dB to -20 dB as the requirement of polarization quality.
  • We feel this study prompts the use of this metric for requirement analysis and quantified quality asssement.
  • Transcript

    • 1. EVALUATION OF SYSTEM POLARIZATION QUALITY FOR POLARIMETRIC SAR IMAGERY AND TARGET DECOMPOSITION Yanting Wang, Thomas L. Ainsworth and Jong-Sen Lee Naval Research Laboratory
    • 2. Objectives
      • PolSAR observations
        • Subject to polarization distortions
      • How good the polarization purity needs to be?
        • Evaluate the various effects of polarization distortions
        • Quantify the polarization quality of the PolSAR system for polarimetric imagery
      Faraday Rotation Cross-talk Channel Imbalance
    • 3. Overview of Polarization Distortion
      • The apparent errors on the measurements depend on the distortion type and the targets
      Channel Imbalance Cross-talk Observations Surface Channel Double bounce Channel Cross-pol Channel To investigate the impact of polarization quality is not trivial task in a practical system.
    • 4. Polarization Distortion Model
      • Distortions act as a linear transformation over the target polarimetric response
      • The measurement error vector
      • Its norm can be used to evaluate the error budget on the observations
      [ D ]:: The distortion matrix We like to evaluate the error vector over the whole vector space { vec ( S t ) }.
    • 5. Polarization Quality Metric
      • Take its maximum to decouple the system characteristics from targets
      • Adjust for natural targets which are reciprocal.
      [ A 4 ]:: “adapter” translates reciprocal scattering to general response MNE : Maximum Normalized Error
    • 6. Polarization Quality Metric
      • The MNE forms an appealing metric
        • Advantage: it is defined over the system polarization distortions ( ) only
        • It caps the error budget in the whole target space
      • The metric is polarization invariant
        • Induced matrix norm is invariant to unitary transformation
    • 7. Typical Distortion – channel imbalance
      • Channel imbalance includes two parts: gain mismatch and phase mismatch
    • 8. Typical Distortion – cross-talk
      • Cross-talk also involves both the isolation level and the phase shifts.
      Assume
    • 9. Typical Distortion – Faraday rotation
      • Low frequency spaceborne radar observations are also subject to propagation distortions
    • 10. Polarimetric Decompositions
      • Normalized error for decompositions
      • The maximum normalized error can be applied to evaluate the decomposition errors given a known set of decomposition bases
      In case of orthogonal decomposition bases, or effectively orthogonal polarization basis change, the maximum decomposition error is same as the MNE. Pauli based decomposition falls into this category.
    • 11. Example Scene
      • E-SAR L-band Image
      Applied with a known distortion: 1) Double bounce scattering 2) Volume scattering 3) Surface scattering
    • 12. Pauli Based Decomposition
      • The MNE is shown as a tight upper bound.
    • 13. Krogager Based Decomposition
      • The decomposition is more affected by this distortion configuration
        • Helix scattering and double bounce scattering are not orthogonal.
        • It is sensitive to the cross-talk phase terms.
      Decomposition Error: -8.4 dB
    • 14. Krogager Based Decomposition
      • Individual decomposition channels
    • 15. Freeman-Durden Decomposition
      • High polarization distortions more likely violate the model assumption
      Flip of surface scattering and double bounce scattering after the random volume component removed
    • 16. Freeman-Durden Decomposition
      • Individual decomposition channels
    • 17. Eigen-based Decomposition
      • Eigen-based decomposition is more resilient to this distortion configuration
    • 18. MNE as Evaluation Baseline
      • Simulation Settings
    • 19. MNE as Evaluation Baseline
      • Decomposition errors versus MNE over the selected canonical scattering mechanism
    • 20. MNE as Evaluation Baseline
      • The metric provides a convenient tool to connect PolSAR image quality with interacting polarization distortions.
      • Reference table for the MNE metric as evaluated at various polarization distortions
    • 21.
      • Questions and Comments?
    • 22. Generalize to Arbitrary Polarization Mode
      • The MNE definition can be further generalized to other polarization modes such as dual-pol mode
      Dual-pol mode Observations Dual-pol mode MNE Receiving at H/V
    • 23. Decomposition Error Profiles
    • 24. Decomposition Error Profiles

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