Detection of distributed targets embedded in homogeneous compound Gaussian clutter with Inverse Gamma texture

The paper deals with detection of distributed targets embedded in compound Gaussian clutter, with Inverse Gamma texture. The proposed detectors are based on Lookup Tables containing threshold factors that maintain a Constant Probability of False Alarm (Pfa). The clutter parameters are estimated online to select the suitable factor to be used in the binary hypothesis test. We model the target energy as spread over a finite number of cells according to the Multiple Dominant scattering centers (MDS) model. Also, binary hypothesis tests are derived using the expression of the overall target energy. Detection Performances of the proposed detectors are analyzed through Monte Carlo simulations considering various clutter parameters and MDS models, and then compared to those of the Cell Averaging based on Lookup Tables (CA-LT) detector. Simulation results indicate that the target energy profile influences significantly the detection performances.