Knowledge-Aided Non-Homogeneity Detector for Airborne MIMO Radar STAP
Loading...
Date
2017-04
Authors
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Altmetrics
Abstract
The target detection performance decreases in airborne multiple-input multiple-output (MIMO) radar space-time adaptive processing (STAP) when the training samples contaminated by interference-targets (outliers) signals are used to estimate the covariance matrix. To address this problem, a knowledge-aided (KA) generalized inner product non-homogeneity detector (GIP NHD) is proposed for MIMO-STAP. Firstly, the clutter subspace knowledge is constructed by the system parameters of MIMO radar STAP. Secondly, the clutter basis vectors are utilized to compose the clutter covariance matrix offline. Then, the GIP NHD is integrated to realize the effective training samples selection, which eliminates the effect of the outliers in training samples on target detection. Simulation results demonstrate that in non-homogeneous clutter environment, the proposed KA-GIP NHD can eliminate the outliers more effectively and improve the target detection performance of MIMO radar STAP compared with the conventional GIP NHD, which is more valuable for practical engineering application.
Description
Citation
Radioengineering. 2017 vol. 26, č. 1, s. 345-352. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2017/17_01_0345_0352.pdf
http://www.radioeng.cz/fulltexts/2017/17_01_0345_0352.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en