弹道中段目标雷达综合识别研究  

Integrated Target Recognition of Ballistic Midcourse Target

作　　者：张平定[1] 孙佳佳[2] 童创明[2,3] 季明阳 张鸣鸣[4] 

机构地区：[1]西安外事学院,西安710077 [2]空军工程大学防空反导学院,西安710051 [3]毫米波国家重点实验室,南京210096 [4]中国人民解放军驻航宇救生装备有限公司军事代表室,襄阳441000

出　　处：《微波学报》2015年第2期20-23,44,共5页Journal of Microwaves

基　　金：国家自然科学基金(61372033);航空科学基金(20130196005)

摘　　要：中段是弹道导弹防御的主要阶段,也是目标构成最为复杂的阶段。数量众多的轻、重诱饵和弹体碎片使得基于单一特征、单次观测的目标识别并不能给出令人信服的识别结果。因此本文根据弹道中段目标的微动和结构特性,首先利用BP神经网络得到基于单一特征的各待识别目标的基本概率赋值,然后利用D-S证据理论实现当前观测周期多特征的融合识别,最后利用D-S证据理论实现当前观测周期与以往观测周期在时间域的序贯融合识别。仿真结果证明了本文方法的有效性。Ballistic midcourse is the main stage for ballistic missile defense and it is also the stage that has the most complex targets. Many heavy,light decoys and body debris in midcourse make it hard to get convincing recognition result based on single feature or one measurement. Based on the micro-motion and structure features of midcourse target,Basic Probability Assignment Function( BPAF) of each single feature is got via BP neural network firstly. Then,multi-feature fusion at current moment is done with D-S evidence theory. Finally,recognition results from different moments are fused with D-S evidence theory again to get the final results. Simulation results show the effectiveness of this method.

关 键 词：弹道中段 目标识别 BP神经网络 D-S证据理论 

分 类 号：TJ761.3[兵器科学与技术—武器系统与运用工程] TP391.4[自动化与计算机技术—计算机应用技术]