基于滤波器组的船舶静电场跟踪  

Ship Static Electric Field Tracking Based on Filter Bank

作　　者：颜冰[1] 孙宝全[1,2] 张伽伟 YAN Bing;SUN Baoquan;ZHANG Jiawei(College of Weapon Engineering, Naval University of Engineering, Wuhan 430033, Hubei,China;Unit 92941 of PLA, Huludao 125000, Liaoning, China)

机构地区：[1]海军工程大学兵器工程学院,湖北武汉430033 [2]92941部队,辽宁葫芦岛125000

出　　处：《兵工学报》2019年第7期1468-1475,共8页Acta Armamentarii

基　　金：国家自然科学基金青年基金项目(51509252)

摘　　要：针对船舶静电场跟踪中先验信息缺失的问题,引入滤波器组方法,提出了一种新的船舶静电场跟踪算法。建立船舶静电场跟踪的状态空间模型,用水平电偶极子对船舶静电场进行建模;以渐进更新扩展卡尔曼滤波为基本滤波单元,采用一组滤波器对目标进行跟踪;根据电场计算公式设计滤波初值,并利用最大似然法确定可靠的跟踪轨迹。仿真和海上电偶极子跟踪实验表明,滤波器组方法能够有效地解决先验信息缺失条件下的船舶静电场跟踪问题,最大似然选择法能够筛选出正确的跟踪轨迹,在跟踪过程中滤波算法对方位信息更加敏感。A new filter algorithm based on filter bank is proposed to solve the problem on lack of prior information in ship static electric field tracking. A state space model of ship static electric field tracking is established, the static electric field of ship is modeled by using a horizontal electric dipole, and a set of filters is used to track a target by taking a progressive update extended Kalman filter as a basic unit. An initial value selection method is designed according to the electric field calculation formula, and the reliable tracking trajectory is selected by using the maximum likelihood method. Simulation and sea electric dipole tracking experiment show that the filter bank method can be used to effectively solve the problem of lack of prior information in ship electric field tracking, the maximum likelihood selection method can be used to select the correct tracking trajectory, and the algorithm is more sensitive to the azimuth information.

关 键 词：船舶静电场 渐进更新扩展卡尔曼滤波 状态空间模型 电偶极子 滤波器组 

分 类 号：TJ610.2[兵器科学与技术—武器系统与运用工程]