Robust CFAR detection in nonhomogeneous correlated interference

Among the few adaptive filtering algorithms which have an embedded constant false alarm rate (CFAR) performance feature, the generalized likelihood ratio (GLR) test algorithm has been found to be robust in the non-Gaussian interference. The detection performance of the GLR algorithm is examined in nonhomogeneous/nonstationary interference environments which cause the non-identically distributed secondary (training) data. For two common types of nonhomogeneity, i.e. the signal contamination and interference edge, the symptotic detection performance is derived and compared to the simulation. The GLR performance loss due to the nonhomogeneity is also evaluated.<
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