|Table of Contents|

Radar range-spread target detection with limited training data(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2018年06期
Page:
727-
Research Field:
Publishing date:

Info

Title:
Radar range-spread target detection with limited training data
Author(s):
Li Yan123Li Zhe123Chen Yang123Wang Jian4Hu Danhui5Wu Chi6
1.NARI Group Corporation,Nanjing 211106,China; 2.Wuhan NARI Limited LiabilityCompany of State Grid Electric Power Research Institute,Wuhan 430074,China; 3.Hubei Key Laboratory of Power Grid Lightning Risk Prevention,Wuhan 430074,China; 4.State Grid Corporation of China,Beijing 100031,China; 5.State Grid Hubei Electric Power Company,Wuhan 430074,China; 6.State Grid Sichuan Electric Power Company,Chengdu 610041,China
Keywords:
radars range-spread targets signal detection reduced-rank generalized likelihood ratio test
PACS:
TN957
DOI:
10.14177/j.cnki.32-1397n.2018.42.06.014
Abstract:
A reduced-rank generalized likelihood ratio test(R-GLRT)detector and a reduced-rank Wald(R-Wald)detector are proposed for radar range-spread target detection to reduce the requirement of training samples. The sampling covariance matrix is replaced by a characteristic matrix corresponding to the noise subspace,and the estimating error is reduced for low sample support. Simulation results show that the proposed reduced-rank detectors can work properly with low sample support,and the detection performance of the R-GLRT detector is better than that of the R-Wald detector; the detection performance of the proposed reduced-rank detectors is better than that of conventional adaptive detector with sufficient training data.

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Last Update: 2018-12-30