A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of...A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.展开更多
Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotio...Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.展开更多
On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high ...On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.展开更多
Based on the high frequency （HF） integrated radar cross section （RCS） calculation approach, a technique of detecting major scattering source is developed by using an appropriate arithmetic for scattering distribut...Based on the high frequency （HF） integrated radar cross section （RCS） calculation approach, a technique of detecting major scattering source is developed by using an appropriate arithmetic for scattering distribution and scattering source detection. For the perfect adaptability to targets and the HF of the HF integrated RCS calculation platform, this technique is suitable to solve large complex targets and has lower requirement to the target modeling. A comparison with the result of 2-D radar imaging confirms the accuracy and reliability of this technique in recognition of the major scattering source on complex targets. This technique provides the foundation for rapid integrated evaluation of the scattering performance and 3-D scattering model reconstruction of large complex targets.展开更多
Based on the analysis of impulse response properties, a scattering model of ultra wideband （UWB） radar targets is developed to estimate the target parameters exactly. With this model, two algorithms of multiple sign...Based on the analysis of impulse response properties, a scattering model of ultra wideband （UWB） radar targets is developed to estimate the target parameters exactly. With this model, two algorithms of multiple signal classification （MUSIC）, and matrix pencil （MP）, are introduced to calculate the scattering center parameters of targets and their performances are compared. The simulation experiments show that there are no differences in the estimation precision of MUSIC and MP methods when the signal-to-noise ratio （SNR） is larger than 13 dB. However, the MP method has a better performance than that of MUSIC method when the SNR is smaller than 13 dB. Besides, the time consuming of MP method is less than that of MUSIC method. Therefore, the MP algorithm is preferred for the parametric estimation of UWB radar targets.展开更多
散射中心是描述雷达目标高频散射机理的重要特征,准确提取雷达目标散射中心参数对解析雷达目标有着极其重要的研究意义。为了提高散射中心参数计算速度,通常将整幅合成孔径雷达(synthetic aperture radar,SAR)图像分解为多个包含散射中...散射中心是描述雷达目标高频散射机理的重要特征,准确提取雷达目标散射中心参数对解析雷达目标有着极其重要的研究意义。为了提高散射中心参数计算速度,通常将整幅合成孔径雷达(synthetic aperture radar,SAR)图像分解为多个包含散射中心的小区域,对每个小区域分别进行特征提取和参数计算。根据雷达目标散射中心的特点,提出了一种基于局部密度聚类的雷达目标散射中心区域分割技术。首先,对雷达图像进行Frost滤波、基于水平集方法(level set method,LSM)的图像分割和面积滤波的一系列图像预处理获得目标感兴趣(region of interest,ROI)区域,然后对预处理后的图像利用局部密度聚类算法检测散射中心并进行区域分割。实验中,采用模拟数据和真实数据对所提方法和传统图像分割算法展开数值实验,实验结果验证了所提方法在雷达目标散射中心区域分割的有效性和优越性。展开更多
现有基于深度神经网络的高距离分辨(High Range Resolution,HRR)雷达目标识别方法是纯数据驱动模型,是1个飞行事故记录器结构,特征不具可解释性,在方位缺失情况下特征泛化性差,模型识别率急剧下降.对此,本文设计了一种物理可解释自编码...现有基于深度神经网络的高距离分辨(High Range Resolution,HRR)雷达目标识别方法是纯数据驱动模型,是1个飞行事故记录器结构,特征不具可解释性,在方位缺失情况下特征泛化性差,模型识别率急剧下降.对此,本文设计了一种物理可解释自编码模型(Physical Interpretable Auto-Encoder Model,PIAEM),解码网络结合雷达目标的散射点模型,利用编码网络挖掘雷达数据具有明确物理含义的散射中心特征,从成像角度描述目标的物理结构特性,如尺寸、轮廓等,在方位缺失情况下具有稳健的物理特性.设计了基于最小重构误差的分类准则,实现雷达目标识别.基于实测高距离分辨雷达回波数据的实验结果表明,本文方法提取的特征具有明确物理含义,且在方位缺失4/5的情况下,PIAEM比现有基于传统目标识别方法的准确率提升了10.27%,验证了本文方法具有方位稳健识别性能.展开更多
文摘A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation for Young Scientists of China (61101182)
文摘Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.
文摘On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.
基金supported by the National Natural Science Foundation of China (Grant No.90305026)
文摘Based on the high frequency （HF） integrated radar cross section （RCS） calculation approach, a technique of detecting major scattering source is developed by using an appropriate arithmetic for scattering distribution and scattering source detection. For the perfect adaptability to targets and the HF of the HF integrated RCS calculation platform, this technique is suitable to solve large complex targets and has lower requirement to the target modeling. A comparison with the result of 2-D radar imaging confirms the accuracy and reliability of this technique in recognition of the major scattering source on complex targets. This technique provides the foundation for rapid integrated evaluation of the scattering performance and 3-D scattering model reconstruction of large complex targets.
基金supported by the Aerospace Science and Technology Foundation of China(2007CH080004).
文摘Based on the analysis of impulse response properties, a scattering model of ultra wideband （UWB） radar targets is developed to estimate the target parameters exactly. With this model, two algorithms of multiple signal classification （MUSIC）, and matrix pencil （MP）, are introduced to calculate the scattering center parameters of targets and their performances are compared. The simulation experiments show that there are no differences in the estimation precision of MUSIC and MP methods when the signal-to-noise ratio （SNR） is larger than 13 dB. However, the MP method has a better performance than that of MUSIC method when the SNR is smaller than 13 dB. Besides, the time consuming of MP method is less than that of MUSIC method. Therefore, the MP algorithm is preferred for the parametric estimation of UWB radar targets.
文摘散射中心是描述雷达目标高频散射机理的重要特征,准确提取雷达目标散射中心参数对解析雷达目标有着极其重要的研究意义。为了提高散射中心参数计算速度,通常将整幅合成孔径雷达(synthetic aperture radar,SAR)图像分解为多个包含散射中心的小区域,对每个小区域分别进行特征提取和参数计算。根据雷达目标散射中心的特点,提出了一种基于局部密度聚类的雷达目标散射中心区域分割技术。首先,对雷达图像进行Frost滤波、基于水平集方法(level set method,LSM)的图像分割和面积滤波的一系列图像预处理获得目标感兴趣(region of interest,ROI)区域,然后对预处理后的图像利用局部密度聚类算法检测散射中心并进行区域分割。实验中,采用模拟数据和真实数据对所提方法和传统图像分割算法展开数值实验,实验结果验证了所提方法在雷达目标散射中心区域分割的有效性和优越性。
