Clutter Subspace Characteristics-Aided Space-Time Adaptive Outlier Sample Selection Method

Sensors

Guisheng Liao¹  Dongning Fu¹  Jingwei Xu¹ 

[1] National Lab of Radar Signal Processing, School Electronic Engineering, Xidian University, Xi’an 710071, China;

关键词: space-time adaptive processing;    clutter subspace;    sample selecting;    airborne radar;   

DOI  :  10.3390/s21093108

来源: DOAJ

【 摘 要 】

For statistic space-time adaptive processing (STAP), a critical issue is estimating the clutter covariance matrix (CCM). However, sufficient training samples are difficult to obtain that satisfy the independent and identically distributed (IID) condition. It is because of the realistic heterogeneous environment faced by airborne radar. Moreover, one should eliminate contaminated training samples before CCM estimation. Aiming at the problems of the computational complexity and susceptibility to the outlier of the traditional generalized inner product (GIP) method, a clutter subspace-based training sampling selecting method is proposed combined with specific distribution in the space-time plane of clutter spectrum. Theoretical analysis and simulation results verified the proposed method and indicate that the proposed method is easy to construct CCM and has lower computational complexity and sensitivity to outliers.

【 授权许可】

Unknown