A modified generalized eigenvalue approach to space-time adaptive processing

Adaptive array processing algorithms have arisen to cope with dynamic environments. Space-time adaptive processors (STAP) work with both spatial and temporal degrees of freedom to estimate the signal parameters. Previous STAP techniques have focused on statistical methods based on estimating the covariance matrices. However, the estimates are often inaccurate, especially in non-homogeneous environments. A novel technique using data directly is proposed to detect targets in highly non-homogeneous environments. Results from real data are presented to demonstrate the efficacy of the algorithm.