Physics

Geology

Pattern recognition (psychology)

Gene

Radar imaging

Algorithm

Image (mathematics)

Similarity (geometry)

Optics

Inverse synthetic aperture radar

Automatic target recognition

Artificial intelligence

Chemistry

Scattering

Target acquisition

Computer science

Synthetic aperture radar

Computer vision

Radar

Biochemistry

Remote sensing

Robustness (evolution)

Telecommunications

IEEE Transactions on Geoscience and Remote Sensing

This paper proposes a robust synthetic aperture radar (SAR) automatic target recognition method based on the 3-D scattering center model. The 3-D scattering center model is established offline from the CAD model of the target using a forward method, which can efficiently predict the 2-D scattering centers as well as the scattering filed of the target at arbitrary poses. For the SAR images to be classified, the 2-D scattering centers are extracted based on the attributed scattering center model and matched with the predicted scattering center set using a neighbor matching algorithm. The selected model scattering centers are used to reconstruct an SAR image based on the 3-D scattering center model, which is compared with the test image to reach a robust similarity. The designed similarity measure comprehensively considers the image correlation between the test image and the model reconstructed image and the model redundancy as for describing the test image. As for target recognition, the model with the highest similarity is determined to the target type of the test SAR image when it is denied to be an outlier. Experiments are conducted on both the data simulated by an electromagnetic code and the data measured in the moving and stationary target acquisition recognition program under standard operating condition and various extended operating conditions to validate the effectiveness and robustness of the proposed method.

Target Reconstruction Based on 3-D Scattering Center Model for Robust SAR ATR