With the increasing complexity of modern battlefield environment and the upgrading of aviation equip-ment technology,massive multi-source heterogeneous sensor data inevitably appear inconsistent and incomplete problems.Traditional multi-sensor fusion method ignores sensor features correlation,and forms a closed data-driven recognition sys-tem of sensors.Whereas expert cognition,domain experience,attribute rules and other knowledge can instruct model con-struction and inference recognition of comprehensive target recognition in the form of expert experience,rule constraints and so on,this paper presents a method of knowledge assisted integrated identification of aerial targets.First of all,a mili-tary combat knowledge map of typical aerial target features is constructed,and key feature parameters are extracted to estab-lish a target identification framework model.Then data basic trust assignment and evidence conflict credibility are construct-ed at recognition and decision recognition level respectively.Besides,time-domain fusion rules for high-conflict evidence is formulated to adjust timing fusion weights by using historical data.Finally,type recognition of multi-sensor is hierarchical-ly realized through static reasoning and dynamic fusion.This study recognition accuracy is better than the existing algo-rithms in typical aerial target recognition tasks,demonstrating the effectiveness of the proposed algorithm.
关键词
目标综合识别/时序融合/空中目标/知识辅助/置信规则分类
Key words
target identification fusion/sequential fusion/aerial target/multiple knowledge/belief rule-based classi-fication key word
维普
万方数据