面向复杂战场的异源探测器数据融合算法  

Complex Battlefields Heterogeneous Detectors Data Fusion Algorithm

作　　者：王湛岩 王德飞 刘虎 WANG Zhanyan;WANG Defei;LIU Hu(The Unit 63895 of PLA,Mengzhou 454750,China)

机构地区：[1]中国人民解放军63895部队,河南孟州454750

出　　处：《探测与控制学报》2025年第1期119-124,共6页Journal of Detection & Control

摘　　要：面对以集群化、智能化目标为主体的复杂战场,异源探测器可以从不同维度探测目标的相关信息,弥补单一传感器量测信息的片面性。基于军用探测器的特点,提出卡尔曼滤波算法多域扩展、异源数据的信息融合及两步分类方法。将集中式融合算法从同源数据融合拓展至异源数据融合,并分析算法在实战环境下的运用。利用仿真实例对算法进行检验,证明算法在满足实时性要求的同时,也提高了关联融合的精度与准确性,满足复杂战场环境下信息融合的要求。Facing the complex battlefield mainly of clusterization and intelligence targets,heterogeneous detectors can detect relevant information about targets from different dimensions,compensating for the one-sidedness of measurements from a single sensor.Based on the characteristics of military detectors,the article proposed innovative methods such as multi-domain extension of the Kalman filtering algorithm,multi-criteria fusion of heterogeneous data,and two-step classification.The centralized fusion algorithm was extended from homogeneous data fusion to heterogeneous data fusion,and the application of the algorithm in practical environments was analyzed.Finally,the algorithm was tested using simulation examples,proving that the algorithm not only met the real-time requirements but also improves the accuracy and precision of correlation fusion,meeting the requirements of information fusion in complex battlefield environments.

关 键 词：异源探测器 复杂战场环境 集中式关联融合算法 实战运用 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]