The texture is modeled by the RSRG distribution as given in (7), in which [alpha] is the shape parameter controlling the deviation from Gaussian statistics and [gamma] is the scale parameter indicating the mean of the distribution.
Considering that: 1) the target energy is always totally unknown in the real applications; 2) the GLRT is computationally expensive, the OS-GLRT detector, therefore, is more applicable in the compound Gaussian clutter with RSRG texture.
Figure 4 plots the probability of detection versus SCR of the OS-GLRT detector with different shape parameter a of the RSRG texture.
In this paper, the range-spread target detection in the compound Gaussian distributed clutter with RSRG texture is studied.
It is more applicable for the range-spread target detection in the compound Gaussian distributed clutter with RSRG texture, especially in the heterogeneous region.
The RSRG texture model is proposed in [25] as a particular case of the square root of generalized inverse Gaussian distribution.