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Persymmetric Structured Covariance Matrix Estimation Based on Whitening for Airborne STAP

Quanxin MA, Xiaolin DU, Jianbo LI, Yang JING, Yuqing CHANG

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Summary :

The estimation problem of structured clutter covariance matrix (CCM) in space-time adaptive processing (STAP) for airborne radar systems is studied in this letter. By employing the prior knowledge and the persymmetric covariance structure, a new estimation algorithm is proposed based on the whitening ability of the covariance matrix. The proposed algorithm is robust to prior knowledge of different accuracy, and can whiten the observed interference data to obtain the optimal solution. In addition, the extended factored approach (EFA) is used in the optimization for dimensionality reduction, which reduces the computational burden. Simulation results show that the proposed algorithm can effectively improve STAP performance even under the condition of some errors in prior knowledge.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E106-A No.7 pp.1002-1006
Publication Date
2023/07/01
Publicized
2022/12/27
Online ISSN
1745-1337
DOI
10.1587/transfun.2022EAL2042
Type of Manuscript
LETTER
Category
Digital Signal Processing

Authors

Quanxin MA
  Yantai University
Xiaolin DU
  Yantai University
Jianbo LI
  Chongqing University of Posts and Telecommunications
Yang JING
  Yantai University
Yuqing CHANG
  Yantai University

Keyword