Statistical Analysis of VHF-Band Tree Backscattering Using Forest Ground Truth Data and PO Scattering Model

Abstract

The paper analyzes statistical properties of the VHF-band radar backscattering from coniferous trees by incorporating forest ground truth data into a physical-optics model that assumes horizontally transmit and receive polarizations and dominant double-bounce scattering from vertical stems standing on undulating ground surface. The analysis shows that a statistically adequate model for the tree backscattering amplitude can be presented as a mixture of generalized gamma or lognormal distribution and the mixture model can be reduced to a single density model if the trees with trunk volumes exceeding an appropriate threshold are to be taken into account. The generalized gamma density is shown to provide appreciably better fit to the exceedance functions associated with the PO-model data than that for the lognormal density. The results can be used to design statistically adequate models of forest clutter for VHF SAR systems.

RCS CHARACTERIZATION OF STEALTH TARGET USING <I>X</I>² DISTRIBUTION AND LOGNORMAL DISTRIBUTION

“…Kolmogorov-Smirnov test [14,15] is adopted as a method of fitting goodness test to determine which distribution is better to describe this aircraft's RCS distribution. The test equation is shown in Eq.…”

Optimisation for stealth target detection based on stratospheric balloon‐borne netted radar system

“…Generally, the localisation techniques need to be combined with a non-parametric method for statistical modelling of stealth target detection, which using an approximation method to predict the real stealth target RCS data, such as method of moments, finite element method, geometrical optics (GO) and physical optics (PO) [14]. The fluctuation of stealth RCS might be better at a higher aspect angle because the Bistatic sensitivity can be improved by increasing the scattered field of stealth target at a higher altitude.…”

Radar cross section (RCS) statistical characterization using weibull distribution

“…Fluctuation of RCS is random without regular pattern. It is significant to characterize RCS by statistical terms such as mean, median, variance and distribution models [1][2][3][4][5][6][7][8]. There are some distribution models existing, such as the first generation distribution models, Swerling type 1-4 distribution and Marcum distribution, and the second generation models, chi-2 distribution, Rician distribution and lognormal distribution.…”

“…Antenna designs for a specific logo have been an interesting topic in recent years [1][2][3][4]. Here, two university logo antennas are studied by applying the slot-loading [1] and monopole-type [2] techniques, in which the latter design is optimized by…”