You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
13 August 1999Probabilistic backscatter coefficient generating function
A probabilistic backscatter coefficient generating function (CGF) is introduced which produces realistic backscatter coefficient values for various terrain types over all incidence angles. The CGF was developed in direct support of a multi-layer 3-D clutter modeling effort which successfully incorporated probabilistic clutter reflectivity characteristics and measured terrain elevation data to enhance clutter suppression and improve Signal-to-Clutter Ratio performance in radar applications. This probabilistic clutter modeling approach is in sharp contrast to traditional 2-D modeling techniques which typically include deterministic backscatter characteristics and assume constant terrain features within regions of interest. The functional form and parametric representation of the CGF were empirically determined by comparison with published backscatter data for nine different terrain 'types,' including, soil and rock, shrubs, trees, short vegetation, grasses, dry snow, wet snow, road surfaces, and urban areas. The statistical properties of the output, i.e., the mean and standard deviation, match published measured values to the number of significant figures reported. Likewise, the CGF output frequency of occurrence closely matches measured terrain data frequency of occurrence; a Chi-Square test fails to reject the method at a 0.05 level of significance, indicating a high level of confidence in the results. As developed, the CGF provides a computationally efficient means for incorporating probabilistic clutter characteristics into both simple and complex radar models by accurately reflecting the probabilistic scattering behavior associated with real terrain.
The alert did not successfully save. Please try again later.
Michael A. Temple, Kelce S. Wilson, "Probabilistic backscatter coefficient generating function," Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); https://doi.org/10.1117/12.357679