Knowledge-based wideband radar target detection in the heterogeneous environment

被引：7
作者：
Hong, Ling [1 ,2 ]
Dai, Fengzhou [3 ]
Wang, Xili [1 ,2 ]
机构：
[1] Shannxi Normal Univ, Key Lab Modern Teaching Technol, Minist Educ, 620 West Changan Ave, Xian 710119, Shaanxi, Peoples R China
[2] Shannxi Normal Univ, Sch Comp Sci, Xian, Shaanxi, Peoples R China
[3] Xidian Univ, Natl Lab Radar Signal Proc, Xian, Shaanxi, Peoples R China
来源：
SIGNAL PROCESSING | 2018年 / 144卷
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Knowledge based; Wideband radar; Target detection; Steering vector dispersion; Heterogeneous clutter; RANGE-SPREAD TARGETS; MULTICHANNEL ADAPTIVE DETECTION; COVARIANCE-MATRIX ESTIMATION; PARAMETRIC RAO TEST; DISTRIBUTED TARGETS; CLUTTER;
D O I：
10.1016/j.sigpro.2017.10.002
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we address wideband radar target detection in the heterogeneous environment. Firstly, a linear model of the wideband radar target return with the steering vector dispersion is established. Secondly, the heterogeneous clutter is modeled as a two-dimensional wide-sense stationary (WSS) process with inverse complex Wishart distributed random covariance matrices in the time-space and frequency domain. Then, several generalized likelihood ratio test (GLRT) based detectors are designed, some of which integrate the prior knowledge of the clutter covariance matrix with the Bayesian approach, while the others are with the heuristic approach. Finally, the performance of the detectors is evaluated by simulations, and the results show that the detectors based on the Bayesian approach outperform the other detectors. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码：169 / 179
页数：11
相关论文
共 43 条
[1]  
Anderson T. W., 2013, INTRO MULTIVARIATE S
[2]  
[Anonymous], 2011, Complex-Valued Matrix Derivatives: With Applications in Signal Processing and Communications
[3]  
[Anonymous], 1997, JACOBIANS MATRIX TRA
[4]   Exploiting multiple a priori spectral models for adaptive radar detection [J].
Aubry, Augusto ;
Carotenuto, Vincenzo ;
De Maio, Antonio ;
Foglia, Goffredo .
IET RADAR SONAR AND NAVIGATION, 2014, 8 (07) :695-707
[5]   Radar Detection of Distributed Targets in Homogeneous Interference Whose Inverse Covariance Structure is Defined via Unitary Invariant Functions [J].
Aubry, Augusto ;
De Maio, Antonio ;
Pallotta, Luca ;
Farina, Alfonso .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2013, 61 (20) :4949-4961
[6]   Maximum Likelihood Estimation of a Structured Covariance Matrix With a Condition Number Constraint [J].
Aubry, Augusto ;
De Maio, Antonio ;
Pallotta, Luca ;
Farina, Alfonso .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2012, 60 (06) :3004-3021
[7]   Adaptive Detection of Distributed Targets in Compound-Gaussian Noise Without Secondary Data: A Bayesian Approach [J].
Bandiera, Francesco ;
Besson, Olivier ;
Ricci, Giuseppe .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2011, 59 (12) :5698-5708
[8]   Knowledge-Aided Covariance Matrix Estimation and Adaptive Detection in Compound-Gaussian Noise [J].
Bandiera, Francesco ;
Besson, Olivier ;
Ricci, Giuseppe .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2010, 58 (10) :5390-5396
[9]   Improved clutter mitigation performance using knowledge-aided space time adaptive processing [J].
Bergin, Jameson S. ;
Teixeira, Christopher M. ;
Techau, Paul M. ;
Guerci, Joseph R. .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2006, 42 (03) :997-1009
[10]   Covariance matrix estimation with heterogeneous samples [J].
Besson, Olivier ;
Bidon, Stephanie ;
Tourneret, Jearl-Yves .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2008, 56 (03) :909-920
12345