Clutter Suppression Approach for End-Fire Array Airborne Radar Based on Adaptive Segmentation

Abstract

End-fire array antenna is a kind of special radar antenna with beam pointing perpendicular to the normal direction of the array. Because of its low profile and directional radiation characteristics, it is especially suitable for blind zone compensation of airborne radar. However, there are few publicly available pieces of literature on clutter suppression for end-fire array radar. In this paper, we firstly simulate and analyze the clutter spectrum characteristics for end-fire array airborne radar (EAAR), and then propose a clutter suppression method for EAAR based on adaptive segmentation. In the proposed method, the concept of Riemann mean distance of temporal covariance matrix is introduced to quantify the clutter nonstationarity, and in this way we realize adaptive segmentation of the clutter range-Doppler spectrum. Then the different clutter suppression methods including pulse Doppler (PD) processing, two-dimensional space-time adaptive processing (2D STAP), and three-dimensional STAP (3D STAP) are used to suppress clutter in different regions. The theoretical analysis and simulation results demonstrate that compared with 3D STAP, the proposed method not only guarantees clutter suppression performance, but also reduces the computational complexity to an extent.

Keywords

• End-fire array
• clutter suppression
• adaptive segmentation
• Riemann mean distance