Pattern synthesis in 3-D opportunistic digital array radar(ODAR) becomes complex when a multitude of antennas are considered to be randomly distributed in a three dimensional space.In order to obtain an optimal patter...Pattern synthesis in 3-D opportunistic digital array radar(ODAR) becomes complex when a multitude of antennas are considered to be randomly distributed in a three dimensional space.In order to obtain an optimal pattern,several freedoms must be constrained.A new pattern synthesis approach based on the improved genetic algorithm(GA) using the least square fitness estimation(LSFE) method is proposed.Parameters optimized by this method include antenna locations,stimulus states and phase weights.The new algorithm demonstrates that the fitness variation tendency of GA can be effectively predicted after several "eras" by the LSFE method.It is shown that by comparing the variation of LSFE curve slope,the GA operator can be adaptively modified to avoid premature convergence of the algorithm.The validity of the algorithm is verified using computer implementation.展开更多
近年来,雷达前视成像技术由于具备广泛的应用价值越来越受到重视,超分辨卷积反演技术是实现前视成像的一种重要技术途径。然而,基于阵列体制的扫描雷达在大范围扫描时会产生天线方向图空变,导致超分辨性能下降。针对该问题,提出了一种...近年来,雷达前视成像技术由于具备广泛的应用价值越来越受到重视,超分辨卷积反演技术是实现前视成像的一种重要技术途径。然而,基于阵列体制的扫描雷达在大范围扫描时会产生天线方向图空变,导致超分辨性能下降。针对该问题,提出了一种适用于阵列扫描雷达的前视稀疏超分辨成像方法。首先,考虑并分析了天线方向图空变性的产生原因,导出了修正天线卷积矩阵,实现了对扫描过程的精准表征;其次,在目标稀疏假设的前提下,构建了相应的目标函数;最后,采用基于重加权策略的交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)方法求解目标函数,实现了稀疏目标有效重建。实验结果表明,所提方法能实现4倍左右的分辨率提升,能有效提升雷达对前视目标区域的探测感知能力。展开更多
A variety of faulty radar echoes may cause serious problems with radar data applications,especially radar data assimilation and quantitative precipitation estimates.In this study,＂test pattern＂ caused by test signal...A variety of faulty radar echoes may cause serious problems with radar data applications,especially radar data assimilation and quantitative precipitation estimates.In this study,＂test pattern＂ caused by test signal or radar hardware failures in CINRAD （China New Generation Weather Radar） SA and SB radar operational observations are investigated.In order to distinguish the test pattern from other types of radar echoes,such as precipitation,clear air and other non-meteorological echoes,five feature parameters including the effective reflectivity data percentage （Rz）,velocity RF （range folding） data percentage （RRF）,missing velocity data percentage （RM）,averaged along-azimuth reflectivity fluctuation （RNr,z） and averaged along-beam reflectivity fluctuation （RNa,z） are proposed.Based on the fuzzy logic method,a test pattern identification algorithm is developed,and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm.Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed.The statistical results show that the test pattern identification algorithm performs well,since the test pattern is recognized in most cases.Besides,the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.展开更多
This work develops a system to visualize the information for radar systems interfaces. It is a flexible, portable software system that allows to be used for radars that have different technologies and that is able to ...This work develops a system to visualize the information for radar systems interfaces. It is a flexible, portable software system that allows to be used for radars that have different technologies and that is able to be adapted to the specific needs of each application domain in an efficient way. Replacing the visualization and processing units on existing radar platforms by this new system, a practical and inexpensive improvement is achieved.展开更多
In this paper, it is proved the ability of quantity reconstruction, amplitudes and coordinates of metallic strip local scattering sources from the backscattering pattern. They are performed as the results of numerical...In this paper, it is proved the ability of quantity reconstruction, amplitudes and coordinates of metallic strip local scattering sources from the backscattering pattern. They are performed as the results of numerical solution for the infinite perfect conducting strip in case of E-polarization of the incident plane electromagnetic wave. In this case it is necessary to fulfill the following conditions. The local sources amplitudes should be the same order, in transverse and longitudinal directions the local sources should be separated into distances more than apparatus resolution, and the object maximum size does not have to be more than approximately 50λ. It was shown the limit and ability of the further development of the offered method.展开更多
Radar Cross Section (RCS) is one of the most considerable parameters for ship stealth design. As modern ships are larger than their predecessors, RCS must be managed at each design stage for its reduction. For predict...Radar Cross Section (RCS) is one of the most considerable parameters for ship stealth design. As modern ships are larger than their predecessors, RCS must be managed at each design stage for its reduction. For predicting RCS of ship, Radar Cross Section Analysis Program (RACSAN) based on Kirchhoff approximation in high frequency range has been developed. This program can present RCS including multi-bounce effect in exterior and interior structure by combination of geometric optics (GO) and physical optics (PO) methods, coating effect by using Fresnel reflection coefficient, and response time pattern for detected target. In this paper, RCS calculations of ship model with above effects are simulated by using this developed program and RCS results are discussed.展开更多
人体呼吸系统相关疾病常常伴随着呼吸深度和节律的异常,因此呼吸信号监测和呼吸模式识别在医疗健康领域中尤其是对于睡眠监测、疾病预断具有重要意义。其中,非接触式的脉冲式超宽带雷达(Impulse Radio Ultra-Wideband,IR-UWB)因具有良...人体呼吸系统相关疾病常常伴随着呼吸深度和节律的异常,因此呼吸信号监测和呼吸模式识别在医疗健康领域中尤其是对于睡眠监测、疾病预断具有重要意义。其中,非接触式的脉冲式超宽带雷达(Impulse Radio Ultra-Wideband,IR-UWB)因具有良好的距离分辨率和穿透能力以及全天候全天时、安全无创的检测优势,正逐步成为睡眠健康监护领域中最关键的感知技术之一。然而受睡眠监测特定的室内场景影响,复杂的测量环境给呼吸模式特征的准确提取带来了限制和挑战,传统的雷达呼吸模式识别算法主要关注一维呼吸时、频域特征,而IR-UWB雷达目标回波信息分散在多个距离门内,使用一维特征识别准确率较低。为此,本文针对IR-UWB雷达中人体呼吸在时间上慢速起伏运动、在距离上是扩展目标的信号模型特点,提出了一种引入时距信息的IR-UWB雷达多域特征融合呼吸模式识别方法。算法在提取一维呼吸信号波形时、频域特征的基础上更进一步挖掘雷达二维时距图像中潜在的呼吸模式形态特征,通过多域特征融合实现呼吸模式的非接触式检测和识别。在图像处理上,针对图像受呼吸异常节律影响呈现局部粘连特性导致呼吸周期提取难的问题,提出一种通过相位矩阵图像处理来检测雷达图像中的呼吸时距条带从而获取图像特征的方法。实验结果表明,利用该算法提取的多域特征对六种呼吸模式进行机器学习的分类识别,可以实现96.3%的识别准确率。展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.61071164)
文摘Pattern synthesis in 3-D opportunistic digital array radar(ODAR) becomes complex when a multitude of antennas are considered to be randomly distributed in a three dimensional space.In order to obtain an optimal pattern,several freedoms must be constrained.A new pattern synthesis approach based on the improved genetic algorithm(GA) using the least square fitness estimation(LSFE) method is proposed.Parameters optimized by this method include antenna locations,stimulus states and phase weights.The new algorithm demonstrates that the fitness variation tendency of GA can be effectively predicted after several "eras" by the LSFE method.It is shown that by comparing the variation of LSFE curve slope,the GA operator can be adaptively modified to avoid premature convergence of the algorithm.The validity of the algorithm is verified using computer implementation.
文摘近年来,雷达前视成像技术由于具备广泛的应用价值越来越受到重视,超分辨卷积反演技术是实现前视成像的一种重要技术途径。然而,基于阵列体制的扫描雷达在大范围扫描时会产生天线方向图空变,导致超分辨性能下降。针对该问题,提出了一种适用于阵列扫描雷达的前视稀疏超分辨成像方法。首先,考虑并分析了天线方向图空变性的产生原因,导出了修正天线卷积矩阵,实现了对扫描过程的精准表征;其次,在目标稀疏假设的前提下,构建了相应的目标函数;最后,采用基于重加权策略的交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)方法求解目标函数,实现了稀疏目标有效重建。实验结果表明,所提方法能实现4倍左右的分辨率提升,能有效提升雷达对前视目标区域的探测感知能力。
基金supported by the National Key Program for Developing Basic Sciences under Grant 2012CB417202the National Natural Science Foundation of China under Grant No. 41175038, No. 41305088 and No. 41075023+4 种基金the Meteorological Special Project "Radar network observation technology and QC"the CMA Key project "Radar Operational Software Engineering"the Chinese Academy of Meteorological Sciences Basic ScientificOperational Projects "Observation and retrieval methods of micro-physics and dynamic parameters of cloud and precipitation with multi-wavelength Remote Sensing"Project of the State Key Laboratory of Severe Weather grant 2012LASW-B04
文摘A variety of faulty radar echoes may cause serious problems with radar data applications,especially radar data assimilation and quantitative precipitation estimates.In this study,＂test pattern＂ caused by test signal or radar hardware failures in CINRAD （China New Generation Weather Radar） SA and SB radar operational observations are investigated.In order to distinguish the test pattern from other types of radar echoes,such as precipitation,clear air and other non-meteorological echoes,five feature parameters including the effective reflectivity data percentage （Rz）,velocity RF （range folding） data percentage （RRF）,missing velocity data percentage （RM）,averaged along-azimuth reflectivity fluctuation （RNr,z） and averaged along-beam reflectivity fluctuation （RNa,z） are proposed.Based on the fuzzy logic method,a test pattern identification algorithm is developed,and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm.Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed.The statistical results show that the test pattern identification algorithm performs well,since the test pattern is recognized in most cases.Besides,the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.
文摘This work develops a system to visualize the information for radar systems interfaces. It is a flexible, portable software system that allows to be used for radars that have different technologies and that is able to be adapted to the specific needs of each application domain in an efficient way. Replacing the visualization and processing units on existing radar platforms by this new system, a practical and inexpensive improvement is achieved.
文摘In this paper, it is proved the ability of quantity reconstruction, amplitudes and coordinates of metallic strip local scattering sources from the backscattering pattern. They are performed as the results of numerical solution for the infinite perfect conducting strip in case of E-polarization of the incident plane electromagnetic wave. In this case it is necessary to fulfill the following conditions. The local sources amplitudes should be the same order, in transverse and longitudinal directions the local sources should be separated into distances more than apparatus resolution, and the object maximum size does not have to be more than approximately 50λ. It was shown the limit and ability of the further development of the offered method.
文摘Radar Cross Section (RCS) is one of the most considerable parameters for ship stealth design. As modern ships are larger than their predecessors, RCS must be managed at each design stage for its reduction. For predicting RCS of ship, Radar Cross Section Analysis Program (RACSAN) based on Kirchhoff approximation in high frequency range has been developed. This program can present RCS including multi-bounce effect in exterior and interior structure by combination of geometric optics (GO) and physical optics (PO) methods, coating effect by using Fresnel reflection coefficient, and response time pattern for detected target. In this paper, RCS calculations of ship model with above effects are simulated by using this developed program and RCS results are discussed.
文摘人体呼吸系统相关疾病常常伴随着呼吸深度和节律的异常,因此呼吸信号监测和呼吸模式识别在医疗健康领域中尤其是对于睡眠监测、疾病预断具有重要意义。其中,非接触式的脉冲式超宽带雷达(Impulse Radio Ultra-Wideband,IR-UWB)因具有良好的距离分辨率和穿透能力以及全天候全天时、安全无创的检测优势,正逐步成为睡眠健康监护领域中最关键的感知技术之一。然而受睡眠监测特定的室内场景影响,复杂的测量环境给呼吸模式特征的准确提取带来了限制和挑战,传统的雷达呼吸模式识别算法主要关注一维呼吸时、频域特征,而IR-UWB雷达目标回波信息分散在多个距离门内,使用一维特征识别准确率较低。为此,本文针对IR-UWB雷达中人体呼吸在时间上慢速起伏运动、在距离上是扩展目标的信号模型特点,提出了一种引入时距信息的IR-UWB雷达多域特征融合呼吸模式识别方法。算法在提取一维呼吸信号波形时、频域特征的基础上更进一步挖掘雷达二维时距图像中潜在的呼吸模式形态特征,通过多域特征融合实现呼吸模式的非接触式检测和识别。在图像处理上,针对图像受呼吸异常节律影响呈现局部粘连特性导致呼吸周期提取难的问题,提出一种通过相位矩阵图像处理来检测雷达图像中的呼吸时距条带从而获取图像特征的方法。实验结果表明,利用该算法提取的多域特征对六种呼吸模式进行机器学习的分类识别,可以实现96.3%的识别准确率。
