复合高斯杂波下知识辅助的极化检测器
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摘要
针对复合高斯杂波中检测低慢小目标,信杂比较低,极化通道相互影响,传统算法性能急剧下降的问题,提出了基于知识辅助的极化检测器。首先将杂波建模为纹理分量为逆伽马分布的复合高斯模型,基于Rao检测准则,得到检验统计量,并推导出纹理分量的精确最大似然估计,然后使用先验信息得到杂波极化散射矩阵,代入检验统计量得到知识辅助的极化检测器。计算机仿真表明,与传统检测器相比,该检测器具有更优良的检测性能,同时仿真分析了先验信息失配对检测性能的影响。
When detecting the low slow and small targets in compound Gaussian clutter,the signal-to-noise ratio is low,the polarimetric channels are interacted and the performance of the traditional algorithm is seriously decreased. Aiming at this problem,a knowledge-aided detector based on polarization is proposed. Firstly,the clutter is modeled as a composite Gaussian model with texture component as inverse gamma distribution. Based on the Rao detection criterion,the test statistic is obtained and the exact maximum likelihood estimation of the texture component is deduced. Then,the clutter polarimetric scattering matrix is substituted into the test statistic to obtain the knowledge-assisted polarimetric adaptive detector. Computer simulation shows that the detector has better detection performance compared with the traditional detector,and the influence of the prior information mismatch on the detection performance is analyzed.
When detecting the low slow and small targets in compound Gaussian clutter,the signal-to-noise ratio is low,the polarimetric channels are interacted and the performance of the traditional algorithm is seriously decreased. Aiming at this problem,a knowledge-aided detector based on polarization is proposed. Firstly,the clutter is modeled as a composite Gaussian model with texture component as inverse gamma distribution. Based on the Rao detection criterion,the test statistic is obtained and the exact maximum likelihood estimation of the texture component is deduced. Then,the clutter polarimetric scattering matrix is substituted into the test statistic to obtain the knowledge-assisted polarimetric adaptive detector. Computer simulation shows that the detector has better detection performance compared with the traditional detector,and the influence of the prior information mismatch on the detection performance is analyzed.
引文
[1]魏耀,张靖,叶杰.低慢小目标探测时的气象干扰抑制方法研究[J].现代雷达,2016,38(7):36-39.
[2]DE MAIO A,RICCI G.A Polarimetric Adaptive Matched Filter[J].Signal Processing,2001,81(12):2583-2589.
[3]LIU J,ZHANG Z J,YANG Y,et al.A CFAR Adaptive Subspace Detector for First-Order or Second-Order Gaussian Signals Based on A Single Observation[J].IEEE Transactions on Signal Processing,2011,59(11):5126-5140.
[4]LEI S,ZHAO Z,NIE Z,et al.Adaptive Polarimetric Detection Method for Target in Partially Homogeneous Background[J].Signal Processing,2015,106:301-311.
[5]DE MAIOA.Rao Test for Adaptive Detection in Gaussian Interference With Unknown Covariance Matrix[J].IEEE Transactions on Signal Processing,2007,55(7):3577-3584.
[6]DE MAIO A,IOMMELLI S.Coincidence of the Rao Test,Wald test,and GLRT in Partially Homogeneous Environment[J].IEEE Signal Processing Letters,2008,15(8):385-388.
[7]KONG L,CUI G,YANG X,et al.Rao and Wald Tests Design of Polarimetric Multiple-Input Multiple-Output Radar in Compound-Gaussian Clutter[J].IET Signal Processing,2011,5(1):85-96.
[8]SHI B,HAO C,HOU C,et al.Parametric Rao test for Multichannel Adaptive Detection of Range-Spread Target in Partially Homogeneous Environments[J].Signal Processing,2015,108(21):421-429.
[9]LIU J,LIU W J,CHEN B,et al.Modified Rao Test for Multichannel Adaptive Signal Detection[J].IEEE Transactions on Signal Processing,2016,64(3):714-725.
[10]STEVEN M K.Fundamentals of Statistical Signal Processing Volume II:Detection Theory[M].Englewood Cliffs:Prentice-Hall NJ,1993.
[11]HARVILLE D A.Matrix Algebra From a Statistician's Perspective[M].New York:Springer,1997.
[12]NOVAK L M.,SECHTIN M B,Cardullo M J.Studies of Target Detection Algorithms That Use Polarimetric Radar Data[J].IEEE Transactions on Aerospace and Electronic Systems,1989,25(2):150-165.
[13]NOVAK L M,BURL M C,IRVING W W.Optimal Polarimetric Processing for Enhanced Target Detection[J].IEEE Transactions on Aerospace and Electronic Systems,1993,29(1):234-244.
[14]邹鲲,廖桂生,李军,等.非高斯杂波下知识辅助检测的认知方法[J].电子学报,2014,42(6):1047-1054.
[15]唐波,张玉,李科.基于先验知识及其定量评估的自适应杂波抑制研究[J].航空学报,2013,34(5):1174-1180.
[2]DE MAIO A,RICCI G.A Polarimetric Adaptive Matched Filter[J].Signal Processing,2001,81(12):2583-2589.
[3]LIU J,ZHANG Z J,YANG Y,et al.A CFAR Adaptive Subspace Detector for First-Order or Second-Order Gaussian Signals Based on A Single Observation[J].IEEE Transactions on Signal Processing,2011,59(11):5126-5140.
[4]LEI S,ZHAO Z,NIE Z,et al.Adaptive Polarimetric Detection Method for Target in Partially Homogeneous Background[J].Signal Processing,2015,106:301-311.
[5]DE MAIOA.Rao Test for Adaptive Detection in Gaussian Interference With Unknown Covariance Matrix[J].IEEE Transactions on Signal Processing,2007,55(7):3577-3584.
[6]DE MAIO A,IOMMELLI S.Coincidence of the Rao Test,Wald test,and GLRT in Partially Homogeneous Environment[J].IEEE Signal Processing Letters,2008,15(8):385-388.
[7]KONG L,CUI G,YANG X,et al.Rao and Wald Tests Design of Polarimetric Multiple-Input Multiple-Output Radar in Compound-Gaussian Clutter[J].IET Signal Processing,2011,5(1):85-96.
[8]SHI B,HAO C,HOU C,et al.Parametric Rao test for Multichannel Adaptive Detection of Range-Spread Target in Partially Homogeneous Environments[J].Signal Processing,2015,108(21):421-429.
[9]LIU J,LIU W J,CHEN B,et al.Modified Rao Test for Multichannel Adaptive Signal Detection[J].IEEE Transactions on Signal Processing,2016,64(3):714-725.
[10]STEVEN M K.Fundamentals of Statistical Signal Processing Volume II:Detection Theory[M].Englewood Cliffs:Prentice-Hall NJ,1993.
[11]HARVILLE D A.Matrix Algebra From a Statistician's Perspective[M].New York:Springer,1997.
[12]NOVAK L M.,SECHTIN M B,Cardullo M J.Studies of Target Detection Algorithms That Use Polarimetric Radar Data[J].IEEE Transactions on Aerospace and Electronic Systems,1989,25(2):150-165.
[13]NOVAK L M,BURL M C,IRVING W W.Optimal Polarimetric Processing for Enhanced Target Detection[J].IEEE Transactions on Aerospace and Electronic Systems,1993,29(1):234-244.
[14]邹鲲,廖桂生,李军,等.非高斯杂波下知识辅助检测的认知方法[J].电子学报,2014,42(6):1047-1054.
[15]唐波,张玉,李科.基于先验知识及其定量评估的自适应杂波抑制研究[J].航空学报,2013,34(5):1174-1180.