An Innovative subarray partitioning method for clutter suppression by space-time adaptive processing based on the ant colony optimisation

As an effective reduced-dimension space-time adaptive processing (STAP) approach, subarray technique is widely used in practice. It is known that, the choice of subarray layout has a strong impact on the performance of subarray level signal processing algorithms. However, the design of subarray partitioning is a difficult problem both in theory and practice. It is extremely valuable to do some research on subarray partition for the huge array radar, especially for those airborne and spaceborne radars with restrict constraint on the cost and space. For these radars, the clutter suppression is an important metric. In this study, the clutter suppressing method by STAP at subarray level is analysed, and the corresponding design of subarray partition is studied. At first, applying the graph theory, a subarray partition strategy is abstracted into a path inside a directed acyclic graph structure. Then, a method based on the ant colony optimisation method is proposed to optimise subarray partition for clutter suppression in STAP. By properly designing the initial and heuristic information, the new method is relatively robust and the complexity is fairly low. Numerical results are presented to verify the effectiveness of the proposed method.