1. Beam-Space Reduced-Dimension 3D-STAP for Nonside-Looking Airborne Radar
- Author
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Zhongjun Yu, Kun Xing, Ning Cui, and Keqing Duan
- Subjects
Computational complexity theory ,Computer science ,Planar array ,Geotechnical Engineering and Engineering Geology ,Sample (graphics) ,law.invention ,Planar ,Dimension (vector space) ,law ,Range (statistics) ,Clutter ,Electrical and Electronic Engineering ,Radar ,Algorithm - Abstract
The space-time adaptive processing (STAP) technique has achieved good clutter suppression performance for a side-looking airborne radar; however, it suffers from severe performance degradation in nonside-looking airborne radar. This is because the clutter distribution varies considerably with range. The 3D STAP can provide better performance compared with the traditional STAP methods in such a nonstationary clutter environment, but it requires high computational complexity and sample support. In this letter, the characteristic of azimuth-elevation-Doppler 3-D beam pattern for the planar array is explored, and a novel reduced-dimension scheme combined with this characteristic is proposed. We further developed three basic reduced-dimension structures according to this scheme. Furthermore, we also prove that the first and third structures are just the direct extension of the traditional 2-D generalized multibeam and joint-domain localized methods. The second one is an original structure that performs local reduced-dimension processing with three orthogonal planar windows. Numerical results verify that the proposed structures have significant advantages in reducing computational load and training sample numbers compared with existing 3D STAP methods. In particular, the second structure shows the best comprehensive performance in the bad samples environment.
- Published
- 2022