Space-Time Adaptive Processing (STAP) refers to a class of signal processing techniques used to process the returns of an antenna array radar system. It enhances the ability of radar to detect targets that might otherwise be obscured by clutter or jamming.
The output of STAP is a linear combination or weighted sum of the input signal samples. The ?adaptive? in STAP refers to the fact that STAP weights are computed to reflect the actual noise, clutter and jamming environment in which the radar finds itself. The ?space? in STAP refers to the fact that the STAP weights (applied to the signal samples at each of the elements of the antenna array) at one instant of time define an antenna pattern in space. If there are jammers in the field of view, STAP will adapt the radar antenna pattern by placing nulls in the direction of those jammers thus rejecting jammer power. The ?time? in STAP refers to the fact that the STAP weights applied to the signal samples at one antenna element over the entire dwell define a system impulse response and hence a system frequency response.
STAP refers to an extension of adaptive antenna signal processing methods that operate on a set of radar returns gathered from multiple elements of an antenna array over a specified time interval. Because the signal returns are composed of range, pulse, and antenna-element samples, a three-dimensional (3-D) cube naturally represents STAP data. In most STAP implementations, there are three phases of computation, one for each dimension of the data cube (range, pulse and channel). Space-Time Adaptive Processing is an important but computationally demanding technique for mitigating clutter. High computational requirements coupled with need for future growth and expansion have led to a major investigation of the suitability of massively parallel processors for this application domain.