Enhancing GMTI Performance in Non-Stationary Clutter Using 3D STAP

In side-looking ground moving target indication (GMTI) radar, the 2-dimensional (2D) space time (azimuth-Doppler) domain can adequately define a clutter spectrum which is accurate for all range gates. However, in applications where the array boresight is not perpendicular to the velocity vector (e.g. forward-looking radar), the azimuth-Doppler clutter spectrum exhibits a dependence on elevation angle-of-arrival, creating range-varying (but elevation-dependent) clutter statistics, or non-stationary clutter. Classical space time adaptive processing (STAP) algorithms suffer substantial performance losses in non-stationary clutter since classical STAP assumes clutter stationary along the range (training) dimension. Planar arrays are inherently able to observe the azimuth-Doppler clutter spectrum as a function of the elevation angle, a capability which linear arrays lack. The incorporation of the planar array´s vertical dimension into the joint azimuth-Doppler (2D) STAP domain has previously resulted in 3D STAP. This paper demonstrates the ability of 3D STAP to solve the non-stationary clutter problem by accounting for the elevation-dependent clutter statistics in a 3D covariance matrix. A forward-looking array is used to provide non-stationary clutter, and the performance of 2D and 3D versions of the adaptive matched filter (AMF) and joint domain localized (JDL) are used in a close-in sensing paradigm. The results show a >55 dB improvement in output SINR near the clutter null using 3D STAP algorithms in lieu of 2D STAP algorithms applied to the same (subarrayed) data.