Scattering Center Modeling Using Adaptive Segmental Compressive Sampling
Scattering Center Modeling Using Adaptive Segmental Compressive Sampling

In order to deal with aliasing distortions of Doppler frequencies shown in time-frequency representation (TFR) with aspect undersampling, an approach using adaptive segmental compressive sampling according to the aspect dependencies of the scattering centers is proposed. The random noise problem induced by compressive sampling is solved by employing a series of signal processing techniques of filtering, image transformation and Hough Transform. Three examples are presented to verify the effectiveness of this approach. The comparisons between the built models and the precise scattered fields computed by a well-validated full-wave numerical method are investigated, and the results show good agreements between each other.
In order to deal with aliasing distortions of Doppler frequencies shown in time-frequency representation (TFR) with aspect undersampling, an approach using adaptive segmental compressive sampling according to the aspect dependencies of the scattering centers is proposed. The random noise problem induced by compressive sampling is solved by employing a series of signal processing techniques of filtering, image transformation and Hough Transform. Three examples are presented to verify the effectiveness of this approach. The comparisons between the built models and the precise scattered fields computed by a well-validated full-wave numerical method are investigated, and the results show good agreements between each other.