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Attributed scattering centers for SAR ATR.

L C Potter1, R L Moses

  • 1Dept. of Electr. Eng., Ohio State Univ., Columbus, OH.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
PubMed
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This study introduces a new framework for radar target recognition using parametric models of scattering centers. This approach enhances feature extraction for more accurate automatic target recognition (ATR) of man-made objects.

Area of Science:

  • Radar engineering
  • Electromagnetics
  • Signal processing

Background:

  • High-frequency radar measurements of man-made targets primarily consist of returns from isolated scattering centers.
  • Characterizing these scattering centers offers a concise and physically meaningful signal representation for automatic target recognition (ATR).

Purpose of the Study:

  • To present a novel framework for feature extraction based on parametric models of radar returns.
  • To leverage the geometrical theory of diffraction for modeling scattering behavior.

Main Methods:

  • Developing statistically robust estimation methods for model parameters to extract high-resolution attributes like location, geometry, and polarization response.
  • Performing statistical analysis of the scattering model to quantify feature uncertainty.

Related Experiment Videos

  • Implementing a least-squares algorithm for feature estimation.
  • Developing a model order selection algorithm and an M-ary generalized likelihood ratio test for polarimetric response classification.

    • Main Results:

    • The framework provides high-resolution attributes for scattering centers, including location, geometry, and polarization response.
    • Statistical analysis quantifies feature uncertainty.
    • A least-squares algorithm is presented for efficient feature estimation.
    • Error bounds for simplified models are derived, and a model order selection algorithm is provided.

    Conclusions:

    • The proposed framework offers a parsimonious and physically relevant signal representation for ATR.
    • The methods enable robust feature extraction and uncertainty quantification for radar scattering centers.
    • The approach is suitable for classifying polarimetric responses in complex clutter environments.