多视角微多普勒融合的进动目标特征提取  

Feature Extraction of Precession Targets Based on Multi-aspect Micro-Doppler Fusion

作　　者：赵双[1] 鲁卫红[1] 冯存前[1] 贺思三[1] 李靖卿 

机构地区：[1]空军工程大学防空反导学院,陕西西安710051

出　　处：《信号处理》2016年第3期296-303,共8页Journal of Signal Processing

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

摘　　要：微动特征是弹道目标识别的重要特征之一。针对锥体目标模型,提出了一种基于多视角窄带雷达网的微动参数提取方法。在详细分析锥体目标等效散射中心微多普勒变化规律的基础上,利用各散射中心之间的微多普勒相关性,结合频率补偿的方法,实现了回波多普勒谱中各散射中心对应的微多普勒曲线的匹配识别。在此基础上,构建多视角联合方程组,提取出锥体目标的进动角、底面半径、锥体高度等参数。仿真结果证明了该方法的有效性与适应性。Micro-motion feature is one of the crucial features used for ballistic target recognition. Aiming at the model of cone-shaped target,a novel algorithm based on the multi-aspect narrowband radar network is proposed to extract the micromotion parameters in this paper. Firstly,on the basis of analyzing the micro-Doppler change rule of the equivalent scattering centers on the precession cone-shaped target in detail,the micro-Doppler curve of each scattering center in echo Doppler spectrum is matched and identified by utilizing the correlation of the micro-Doppler among three scattering centers combined with the frequency compensation method. Then based on this,the multi-aspect associated systems of equations are established,and parameters including the precession angle,radius of undersurface and height of the cone-shaped target are extracted jointly. Finally,the simulation results are given for validating the effectiveness and adaptability of the proposed algorithms.

关 键 词：进动特征 窄带雷达 频率补偿 多视角 

分 类 号：TN957[电子电信—信号与信息处理]