利用球不变随机矢量(Spherically Invariant Random Vector,SIRV)描述非均匀杂波,建立了双基地多输入多输出(Multiple-Input Multiple-Qutput,MIMO)雷达距离扩展目标的信号检测模型,提出了距离扩展目标的两步广义似然比检测(Generalized...利用球不变随机矢量(Spherically Invariant Random Vector,SIRV)描述非均匀杂波,建立了双基地多输入多输出(Multiple-Input Multiple-Qutput,MIMO)雷达距离扩展目标的信号检测模型,提出了距离扩展目标的两步广义似然比检测(Generalized Likelihood Ratio Test,GLRT)算法.首先,根据目标散射系数的两种假设模型,分别推导确定型目标、高斯型目标GLRT检测器的解析表达式,然后利用固定点迭代算法估计杂波协方差矩阵,获得自适应GLRT(AD-GLRT和AG-GLRT)检测器.仿真实验表明:AD-GLRT和AG-GLRT检测器的检测性能均优于非均匀杂波背景、高斯杂波背景下点目标的检测性能,且两者的检测性能相当,并且虚拟阵元数、目标分布的距离单元数,以及信杂比越大,两者的检测性能越好.展开更多
The problem of adaptive radar detection in compound-Gaussian clutter without secondary data is considered in this paper.In most practical applications,the number of training data is limited.To overcome the lack of tra...The problem of adaptive radar detection in compound-Gaussian clutter without secondary data is considered in this paper.In most practical applications,the number of training data is limited.To overcome the lack of training data,an autoregressive(AR)-process-based covariance matrix estimator is proposed.Then,with the estimated covariance matrix the one-step generalized likelihood ratio test(GLRT) detector is designed without training data.Finally,detection performance of our proposed detector is assessed.展开更多
为了解决部分均匀环境中训练数据不足时的子空间信号检测难题,采用贝叶斯理论,将噪声协方差矩阵建模为逆威沙特分布,并采用广义似然比准则(generalized likelihood ratio test,GLRT)、Rao准则和Wald准则设计自适应检测器,结果表明3种准...为了解决部分均匀环境中训练数据不足时的子空间信号检测难题,采用贝叶斯理论,将噪声协方差矩阵建模为逆威沙特分布,并采用广义似然比准则(generalized likelihood ratio test,GLRT)、Rao准则和Wald准则设计自适应检测器,结果表明3种准则得到相同的结果。基于仿真及实测数据验证了所提检测器的有效性,并得出了影响检测性能的关键物理量。展开更多
传统的CFAR检测应用到光学卫星遥感图像舰船目标检测中时不能对黑极性目标进行判断,针对此提出改进的基于广义似然比检验(Generalized Likelihood Ratio Test,GLRT)的舰船目标检测算法。该算法采用滑动窗口检测形式,在假设背景和目标灰...传统的CFAR检测应用到光学卫星遥感图像舰船目标检测中时不能对黑极性目标进行判断,针对此提出改进的基于广义似然比检验(Generalized Likelihood Ratio Test,GLRT)的舰船目标检测算法。该算法采用滑动窗口检测形式,在假设背景和目标灰度均服从高斯分布的前提下,通过GLRT判断背景窗口与目标窗口是否同分布来检测目标,兼顾了目标黑白两种极性的情况。算法实现中对图像进行了分块检测,并通过形态学处理对检测结果进行了目标聚类。采用SPOT5与CBERS实测数据进行实验,验证了海背景服从高斯分布的假设。典型数据检测结果表明,该算法可以检测黑极性目标,且相比CFAR虚警率更低,大量数据计算ROC曲线的结果以及比CFAR检测少约40%的耗时进一步表明该算法性能更优。展开更多
Spectrum sensing is an essential ability to detect spectral holes in cognitive radio( CR) networks. The critical challenge to spectrum sensing in the wideband frequency range is how to sense quickly and accurately. Co...Spectrum sensing is an essential ability to detect spectral holes in cognitive radio( CR) networks. The critical challenge to spectrum sensing in the wideband frequency range is how to sense quickly and accurately. Compressive sensing( CS) theory can be employed to detect signals from a small set of non-adaptive,linear measurements without fully recovering the signal. However,the existing compressive detectors can only detect some known deterministic signals and it is not suitable for the time-varying amplitude signal,such as spectrum sensing signals in CR networks. First,a model of signal detect is proposed by utilizing compressive sampling without signal recovery,and then the generalized likelihood ratio test( GLRT) detection algorithm of the time-varying amplitude signal is derived in detail. Finally, the theoretical detection performance bound and the computation complexity are analyzed. The comparison between the theory and simulation results of signal detection performance over Rayleigh and Rician channel demonstrates the validity of the performance bound. Compared with the reconstructed spectrum sensing detection algorithm,the proposed algorithm greatly reduces the data volume and algorithm complexity for the signal with random amplitudes.展开更多
有色混响噪声背景以及水下动目标径向速度造成的回波和样本失配导致匹配滤波器对于线性调频LFM(linear frequency modulation)回波检测性能下降。基于自适应预白化处理的广义似然比GLRT(generalized likelihood ratio test)方法利用混...有色混响噪声背景以及水下动目标径向速度造成的回波和样本失配导致匹配滤波器对于线性调频LFM(linear frequency modulation)回波检测性能下降。基于自适应预白化处理的广义似然比GLRT(generalized likelihood ratio test)方法利用混响噪声背景的自回归AR(autoregressive)模型构建白化滤波器来抑制混响噪声,但回波和混响噪声的混叠会造成AR模型偏差。结合匹配滤波的回波定位特性和基于自适应预白化处理GLRT方法的混响噪声背景抑制特性,提出结合这两种方法的联合检测算法。仿真和实验数据测试表明联合检测算法对于水下动目标LFM回波检测性能优于单纯的零速样本匹配滤波和GLRT方法。展开更多
文摘利用球不变随机矢量(Spherically Invariant Random Vector,SIRV)描述非均匀杂波,建立了双基地多输入多输出(Multiple-Input Multiple-Qutput,MIMO)雷达距离扩展目标的信号检测模型,提出了距离扩展目标的两步广义似然比检测(Generalized Likelihood Ratio Test,GLRT)算法.首先,根据目标散射系数的两种假设模型,分别推导确定型目标、高斯型目标GLRT检测器的解析表达式,然后利用固定点迭代算法估计杂波协方差矩阵,获得自适应GLRT(AD-GLRT和AG-GLRT)检测器.仿真实验表明:AD-GLRT和AG-GLRT检测器的检测性能均优于非均匀杂波背景、高斯杂波背景下点目标的检测性能,且两者的检测性能相当,并且虚拟阵元数、目标分布的距离单元数,以及信杂比越大,两者的检测性能越好.
基金supported by the Fundamental Research Funds for the Central Universities under Grant No. E022050205
文摘The problem of adaptive radar detection in compound-Gaussian clutter without secondary data is considered in this paper.In most practical applications,the number of training data is limited.To overcome the lack of training data,an autoregressive(AR)-process-based covariance matrix estimator is proposed.Then,with the estimated covariance matrix the one-step generalized likelihood ratio test(GLRT) detector is designed without training data.Finally,detection performance of our proposed detector is assessed.
文摘为了解决部分均匀环境中训练数据不足时的子空间信号检测难题,采用贝叶斯理论,将噪声协方差矩阵建模为逆威沙特分布,并采用广义似然比准则(generalized likelihood ratio test,GLRT)、Rao准则和Wald准则设计自适应检测器,结果表明3种准则得到相同的结果。基于仿真及实测数据验证了所提检测器的有效性,并得出了影响检测性能的关键物理量。
文摘传统的CFAR检测应用到光学卫星遥感图像舰船目标检测中时不能对黑极性目标进行判断,针对此提出改进的基于广义似然比检验(Generalized Likelihood Ratio Test,GLRT)的舰船目标检测算法。该算法采用滑动窗口检测形式,在假设背景和目标灰度均服从高斯分布的前提下,通过GLRT判断背景窗口与目标窗口是否同分布来检测目标,兼顾了目标黑白两种极性的情况。算法实现中对图像进行了分块检测,并通过形态学处理对检测结果进行了目标聚类。采用SPOT5与CBERS实测数据进行实验,验证了海背景服从高斯分布的假设。典型数据检测结果表明,该算法可以检测黑极性目标,且相比CFAR虚警率更低,大量数据计算ROC曲线的结果以及比CFAR检测少约40%的耗时进一步表明该算法性能更优。
基金supported by the National Natural Science Foundation of China ( 61771126,61572254 )Foundation of Graduate Innovation Center in NUAA ( kfjj20170402)
文摘Spectrum sensing is an essential ability to detect spectral holes in cognitive radio( CR) networks. The critical challenge to spectrum sensing in the wideband frequency range is how to sense quickly and accurately. Compressive sensing( CS) theory can be employed to detect signals from a small set of non-adaptive,linear measurements without fully recovering the signal. However,the existing compressive detectors can only detect some known deterministic signals and it is not suitable for the time-varying amplitude signal,such as spectrum sensing signals in CR networks. First,a model of signal detect is proposed by utilizing compressive sampling without signal recovery,and then the generalized likelihood ratio test( GLRT) detection algorithm of the time-varying amplitude signal is derived in detail. Finally, the theoretical detection performance bound and the computation complexity are analyzed. The comparison between the theory and simulation results of signal detection performance over Rayleigh and Rician channel demonstrates the validity of the performance bound. Compared with the reconstructed spectrum sensing detection algorithm,the proposed algorithm greatly reduces the data volume and algorithm complexity for the signal with random amplitudes.
文摘有色混响噪声背景以及水下动目标径向速度造成的回波和样本失配导致匹配滤波器对于线性调频LFM(linear frequency modulation)回波检测性能下降。基于自适应预白化处理的广义似然比GLRT(generalized likelihood ratio test)方法利用混响噪声背景的自回归AR(autoregressive)模型构建白化滤波器来抑制混响噪声,但回波和混响噪声的混叠会造成AR模型偏差。结合匹配滤波的回波定位特性和基于自适应预白化处理GLRT方法的混响噪声背景抑制特性,提出结合这两种方法的联合检测算法。仿真和实验数据测试表明联合检测算法对于水下动目标LFM回波检测性能优于单纯的零速样本匹配滤波和GLRT方法。
