利用微动信息矩阵的弹道目标特征提取算法  

Employing Micro-motion Information Matrix for Feature Extraction of Ballistic Targets

作　　者：李靖卿 冯存前[1,2] 贺思三[1] 赵双[1] 

机构地区：[1]空军工程大学防空反导学院,陕西西安710051 [2]信息感知技术协同创新中心,陕西西安710077

出　　处：《信号处理》2016年第4期488-495,共8页Journal of Signal Processing

基　　金：国家自然科学基金资助项目(61372166);陕西省自然科学基础研究计划资助项目(2014JM8308)

摘　　要：为满足反导作战的现实需求及解决强噪声环境下弹道目标特征提取问题,提出了一种新的基于宽/窄带混合体制雷达的弹道目标特征提取算法。该算法分析了宽/窄带信号对应的微动特征,运用Viterbi算法分离并提取出各散射中心的微动曲线。在此基础上,根据宽/窄带微动特征的相关性,结合改进自相关法和最小二乘估计方法,构建并解算出目标最强散射中心对应的微动信息矩阵。最后利用散射中心关联和一致性匹配融合方法,构建多元方程组并求解,得到目标的微动特征和结构参数。仿真结果表明:当信噪比为0 d B时,该算法估计得到的目标微动特征和结构参数的均方根误差的量级均为10-2。Aiming at the realistic requirement of anti-missile operation and the feature extraction of ballistic target under strong noise,a novel algorithm for feature extraction of ballistic target based on hybrid-scheme radar combining narrow-band apparatus with wide-band apparatus is proposed. The micro-motion features relative to the narrow-band echo and wide-band echo are analyzed,and then the micro-motion curve of each scattering center is successively extracted by the Viterbi algorithm. Based on the relevance of micro-motion features corresponding to narrow-band echo and wide-band echo,the micromotion information matrix is constructed and calculated by the improved autocorrelation method and the least squares estimation（ LSE）. Ultimately,Combined with data association of scattering center and consistency matching fusion,the micromotion features and structure parameters of one target is extracted by constructing and solving the multivariable equation.The simulation results validate that the root-mean-square errors（ RMSE） of the extracted micro-motion features and structural parameters reach 10^（-2）when the signal noise ratio（ SNR） is 0 d B.

关 键 词：微动 信息矩阵 混合体制雷达 关联 特征提取 

分 类 号：TN95[电子电信—信号与信息处理]