A pseudo-random coding side-lobe suppression method based on CLEAN algorithm is introduced.The CLEAN algorithm mainly processes pulse compression results of a pseudo-random coding,and estimates a target＇s distance by...A pseudo-random coding side-lobe suppression method based on CLEAN algorithm is introduced.The CLEAN algorithm mainly processes pulse compression results of a pseudo-random coding,and estimates a target＇s distance by a method named interpolation method,so that we can get an ideal pulse compression result of the target,and then use the adjusted ideal pulse compression side-lobe to cut the actual pulse compression result,so as to achieve the remarkable performance of side-lobe suppression for large targets,and let the adjacent small targets appear.The computer simulations by MATLAB with this method analyze the effect of side-lobe suppression in an ideal or noisy environment.It is proved that this method can effectively solve the problem due to the side-lobe of pseudo-random coding being too high,and can enhance the radar＇s multi-target detection ability.展开更多
In this article, a novel scattering center extraction method using genetic algorithm is proposed to deal with the ultra-wideband （UWB） localization image, which is called evolutionary programming （EP） CLEAN algori...In this article, a novel scattering center extraction method using genetic algorithm is proposed to deal with the ultra-wideband （UWB） localization image, which is called evolutionary programming （EP） CLEAN algorithm. Because of the UWB characters, the ideal point scattering model and EP method are used in the algorithm for optimizing the UWB localization images. After introducing the algorithm detail, the actual model is used to realize the EP CLEAN algorithm. Compared with the conventional localization imaging algorithm, this algorithm has advantages fitting the UWB characters such as accuracy, robustness, and better resolution, which are verified by the numerical simulations. Therefore the EP CLEAN algorithm could improve localization image performance to expand the UWB technique application.展开更多
嫦娥四号低频射电频谱仪(Low Frequency Radio Spectrometer,LFRS)放置在月球背面,观测条件得天独厚。然而,嫦娥四号平台存在约10-15W/(m2·Hz)的强干扰,并且干扰在每道时域数据中存在明显差异,大大削弱了低频射电频谱仪的观测灵敏...嫦娥四号低频射电频谱仪(Low Frequency Radio Spectrometer,LFRS)放置在月球背面,观测条件得天独厚。然而,嫦娥四号平台存在约10-15W/(m2·Hz)的强干扰,并且干扰在每道时域数据中存在明显差异,大大削弱了低频射电频谱仪的观测灵敏度。为此,从两组信号的相关性出发,提出基于CLEAN算法,借助互相关功率谱、傅里叶级数等工具,把低频射电频谱仪天线A,B和C的时域观测数据切分为强相关的CLEAN模型信号和部分相关的残余信号。其中,CLEAN模型信号主要由平台干扰信号和可能的低频强射电爆发组成;残余信号由接收机噪声、未扣除的平台干扰信号和常规低频射电信号组成。将该算法应用到实际数据中,结果表明,嫦娥四号低频射电频谱仪的未积分灵敏度可以提高约8个数量级,达到10-23W/(m2·Hz)。在此基础上,基于对平台干扰信号中确定成分和宽带随机成分的分类处理,借助低频射电爆发信号和平台干扰信号在功率谱上的不同表现,以及常规低频射电天文信号受月球自转调制等信息,将来科学分析工作的重点是进一步处理CLEAN模型信号和残余信号,以发现低频强射电天文爆发信号,对全天区进行粗略的成像。展开更多
文摘A pseudo-random coding side-lobe suppression method based on CLEAN algorithm is introduced.The CLEAN algorithm mainly processes pulse compression results of a pseudo-random coding,and estimates a target＇s distance by a method named interpolation method,so that we can get an ideal pulse compression result of the target,and then use the adjusted ideal pulse compression side-lobe to cut the actual pulse compression result,so as to achieve the remarkable performance of side-lobe suppression for large targets,and let the adjacent small targets appear.The computer simulations by MATLAB with this method analyze the effect of side-lobe suppression in an ideal or noisy environment.It is proved that this method can effectively solve the problem due to the side-lobe of pseudo-random coding being too high,and can enhance the radar＇s multi-target detection ability.
基金the National Natural Science Foundation of China （60331010, 60671055） 0pen Fund of Key Lab of 0ptical Communication and Light-Wave Technology （Beijing University of Posts and Telecommunications）, Ministry of Education, China.
文摘In this article, a novel scattering center extraction method using genetic algorithm is proposed to deal with the ultra-wideband （UWB） localization image, which is called evolutionary programming （EP） CLEAN algorithm. Because of the UWB characters, the ideal point scattering model and EP method are used in the algorithm for optimizing the UWB localization images. After introducing the algorithm detail, the actual model is used to realize the EP CLEAN algorithm. Compared with the conventional localization imaging algorithm, this algorithm has advantages fitting the UWB characters such as accuracy, robustness, and better resolution, which are verified by the numerical simulations. Therefore the EP CLEAN algorithm could improve localization image performance to expand the UWB technique application.
文摘嫦娥四号低频射电频谱仪(Low Frequency Radio Spectrometer,LFRS)放置在月球背面,观测条件得天独厚。然而,嫦娥四号平台存在约10-15W/(m2·Hz)的强干扰,并且干扰在每道时域数据中存在明显差异,大大削弱了低频射电频谱仪的观测灵敏度。为此,从两组信号的相关性出发,提出基于CLEAN算法,借助互相关功率谱、傅里叶级数等工具,把低频射电频谱仪天线A,B和C的时域观测数据切分为强相关的CLEAN模型信号和部分相关的残余信号。其中,CLEAN模型信号主要由平台干扰信号和可能的低频强射电爆发组成;残余信号由接收机噪声、未扣除的平台干扰信号和常规低频射电信号组成。将该算法应用到实际数据中,结果表明,嫦娥四号低频射电频谱仪的未积分灵敏度可以提高约8个数量级,达到10-23W/(m2·Hz)。在此基础上,基于对平台干扰信号中确定成分和宽带随机成分的分类处理,借助低频射电爆发信号和平台干扰信号在功率谱上的不同表现,以及常规低频射电天文信号受月球自转调制等信息,将来科学分析工作的重点是进一步处理CLEAN模型信号和残余信号,以发现低频强射电天文爆发信号,对全天区进行粗略的成像。
