Design and representation of suboptimum methods for radar space-time adaptive processing (STAP) techniques using a canonical framework

Space-time adaptive processing (STAP) is a technique used by moving radars to detect slow moving targets. The goal is to reject interference and noise. However, rejection requires a great number of training samples and a large computational cost. To keep the task manageable, suboptimum STAP methods (SOMs) have been proposed by several authors. We have developed a framework to encompass all these methods in a canonical structure. In the appendices, some famous SOMs will be described using the canonical framework. The canonical framework can also be seen as a tool that can be used to design new techniques. This paper is a guideline for designing suboptimum STAP techniques using the framework. Choices that designers have to make are presented in regard with the impact of these choices