A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homo...A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching- CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.展开更多
A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the cl...A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the clutter PDF in the reference window are estimated by the non-parametric density estimation. The target detector is defined as the mean square error （MSE） distance between the two PDFs. The CFAR detection in SAR images having multiplicative noise is achieved by adaptive kernel bandwidth proportional to the clutter level. In addition, for obtaining a threshold with respect to a given probability of false alarm （PFA）, an unsupervised null distribution fitting method with outlier rejection is proposed. The effectiveness of the proposed target detector is demonstrated by the experiment result using the RADATSAT-2 SAR image.展开更多
As traditional two-parameter constant false alarm rate （CFAR） target detec-tion algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images ...As traditional two-parameter constant false alarm rate （CFAR） target detec-tion algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images increases, small targets present more pixels in SAR images. So the target distribution is of much significance. Distribution-based CFAR detection algorithm is presented. We unite the pixels around the test cell, and estimate the distribution of test cell by them. Generalized Likelihood Ratio Test （GLRT） is used to deduce the detectors. The performance of the distribution-based CFAR （DBCFAR） detectors is analyzed theoretically. False alarms of DBCFAR detection are fewer than those of CFAR at the same detection rate. Finally experiments are done and the results show the performance of DBCFAR is out of conventional CFAR. False alarms of DBCFAR detection are concentrated while those of CFAR detection are dispersive.展开更多
基于数字射频存储(digital radio frequency memory,DRFM)技术的转发式干扰的存在性检测是对抗有源欺骗干扰的前提。干扰机的相位取样量化会导致干扰信号有谐波分量的寄生。在雷达距离/速度波门内同时存在目标信号和欺骗干扰信号的情形...基于数字射频存储(digital radio frequency memory,DRFM)技术的转发式干扰的存在性检测是对抗有源欺骗干扰的前提。干扰机的相位取样量化会导致干扰信号有谐波分量的寄生。在雷达距离/速度波门内同时存在目标信号和欺骗干扰信号的情形下,利用经验模态分解(empirical model decomposition,EMD)算法分离出干扰信号谐波分量,通过提取干扰谐波分量与目标回波在时频域上能量分布特征差异,提出了一种基于时频域熵特征的有源欺骗干扰检测方法。该方法不需要估计噪声参数,且具有恒虚警(constant false-alarm rate,CFAR)特性。蒙特卡罗仿真结果验证了该方法的有效性。展开更多
基金supported by the National Natural Science Foundation of China(61102158)the China Postdoctoral Science Foundation(2011M500667)
文摘A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching- CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.
基金supported by the National Natural Science Foundation of China (40871157 41171317)the Foundation of Advance Research of Science and Technology for Chinese National Defence(9140C620201902)
文摘A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the clutter PDF in the reference window are estimated by the non-parametric density estimation. The target detector is defined as the mean square error （MSE） distance between the two PDFs. The CFAR detection in SAR images having multiplicative noise is achieved by adaptive kernel bandwidth proportional to the clutter level. In addition, for obtaining a threshold with respect to a given probability of false alarm （PFA）, an unsupervised null distribution fitting method with outlier rejection is proposed. The effectiveness of the proposed target detector is demonstrated by the experiment result using the RADATSAT-2 SAR image.
文摘As traditional two-parameter constant false alarm rate （CFAR） target detec-tion algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images increases, small targets present more pixels in SAR images. So the target distribution is of much significance. Distribution-based CFAR detection algorithm is presented. We unite the pixels around the test cell, and estimate the distribution of test cell by them. Generalized Likelihood Ratio Test （GLRT） is used to deduce the detectors. The performance of the distribution-based CFAR （DBCFAR） detectors is analyzed theoretically. False alarms of DBCFAR detection are fewer than those of CFAR at the same detection rate. Finally experiments are done and the results show the performance of DBCFAR is out of conventional CFAR. False alarms of DBCFAR detection are concentrated while those of CFAR detection are dispersive.
文摘基于数字射频存储(digital radio frequency memory,DRFM)技术的转发式干扰的存在性检测是对抗有源欺骗干扰的前提。干扰机的相位取样量化会导致干扰信号有谐波分量的寄生。在雷达距离/速度波门内同时存在目标信号和欺骗干扰信号的情形下,利用经验模态分解(empirical model decomposition,EMD)算法分离出干扰信号谐波分量,通过提取干扰谐波分量与目标回波在时频域上能量分布特征差异,提出了一种基于时频域熵特征的有源欺骗干扰检测方法。该方法不需要估计噪声参数,且具有恒虚警(constant false-alarm rate,CFAR)特性。蒙特卡罗仿真结果验证了该方法的有效性。
