TY - JOUR
T1 - 知识辅助的空中目标综合识别
AU - Cui, Yi Han
AU - Liang, Yan
AU - Song, Qian Qian
AU - Zhang, Hui Xia
AU - Wang, Fan
N1 - Publisher Copyright:
© 2024 Chinese Institute of Electronics. All rights reserved.
PY - 2024/9/25
Y1 - 2024/9/25
N2 - With the increasing complexity of modern battlefield environment and the upgrading of aviation equipment 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 system of sensors. Whereas expert cognition, domain experience, attribute rules and other knowledge can instruct model construction 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 military combat knowledge map of typical aerial target features is constructed, and key feature parameters are extracted to establish a target identification framework model. Then data basic trust assignment and evidence conflict credibility are constructed 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 hierarchically realized through static reasoning and dynamic fusion. This study recognition accuracy is better than the existing algorithms in typical aerial target recognition tasks, demonstrating the effectiveness of the proposed algorithm.
AB - With the increasing complexity of modern battlefield environment and the upgrading of aviation equipment 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 system of sensors. Whereas expert cognition, domain experience, attribute rules and other knowledge can instruct model construction 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 military combat knowledge map of typical aerial target features is constructed, and key feature parameters are extracted to establish a target identification framework model. Then data basic trust assignment and evidence conflict credibility are constructed 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 hierarchically realized through static reasoning and dynamic fusion. This study recognition accuracy is better than the existing algorithms in typical aerial target recognition tasks, demonstrating the effectiveness of the proposed algorithm.
KW - aerial target
KW - belief rule-based classification key word
KW - multiple knowledge
KW - sequential fusion
KW - target identification fusion
UR - http://www.scopus.com/inward/record.url?scp=85207909727&partnerID=8YFLogxK
U2 - 10.12263/DZXB.20230440
DO - 10.12263/DZXB.20230440
M3 - 文章
AN - SCOPUS:85207909727
SN - 0372-2112
VL - 52
SP - 2961
EP - 2970
JO - Tien Tzu Hsueh Pao/Acta Electronica Sinica
JF - Tien Tzu Hsueh Pao/Acta Electronica Sinica
IS - 9
ER -