Open AccessReduced‐dimension space‐time adaptive processing for airborne radar with co‐prime array
Author(s) -
Wang Xiaoye,
Yang Zhaocheng,
Huang Jianjun
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0170
Subject(s) - space time adaptive processing , dimension (graph theory) , covariance matrix , radar , computer science , algorithm , interference (communication) , matrix (chemical analysis) , prime (order theory) , computational complexity theory , convergence (economics) , transformation matrix , adaptive filter , control theory (sociology) , mathematics , radar engineering details , artificial intelligence , telecommunications , radar imaging , physics , channel (broadcasting) , materials science , economic growth , composite material , control (management) , kinematics , classical mechanics , combinatorics , pure mathematics , economics
Space‐time adaptive processing (STAP) for airborne radar with co‐prime arrays is shown to have excellent superiority compared to traditional STAP with uniform linear array radar. However, high arithmetic computational complexity and large amount of training data are required in this approach. This motivates the authors to present a new approach which is relatively low computational load and fast convergence with satisfactory performance. Specifically, a reduced‐dimension transformation in Doppler domain is incorporated into the existing approach. The reduced‐dimension interference covariance matrix and target steering vector are then achieved by performing the reduced‐dimension process, and hence two reduced‐dimension STAP filters are designed using the derived interference covariance matrix and target‐steering vector. Numerical simulations are carried out to reveal the superiority of the proposed approach.