基于数据融合的目标检测方法综述

An overview of target detection methods based on data fusion

随着基于数据融合的目标检测在军事以及自然防护等领域广泛应用,越来越多的研究希望通过对检测融合系统进行优化或引入新的检测融合方法来更好地进行目标检测,从而推动相关领域的发展.基于数据融合的目标检测具有重要的学术意义和应用价值,为此,从先进的检测技术到优化创新的前沿论文等方面详细介绍基于数据融合的目标检测方法的最新研究进展.首先对融合定义、模式及其优缺点展开讨论,并总结目前该领域所面临的挑战;然后从传感器辅助方法、融合层次方法两个方面对相关研究方法进行详细的分类阐述,综述该领域的研究现状,并对所介绍的文献从检测性能、复杂程度、成本大小、检测目标(数量、动态、维度)等方面展开归纳总结;最后进行全文总结并对该领域的研究前景进行展望.

With the wide application of data fusion based on target detection in military and natural protection and other fields,relevant research scholars can detect target well by optimizing the detection fusion system or introducing new detection fusion methods,thus promoting the development of related fields.Target detection based on data fusion has important academic significance and application value.The latest research progress of target detection methods is introduced based on data fusion from advanced detection technology to cutting-edge papers of optimization and innovation.Firstly,the definitions,patterns,advantages and fusion disadvantages are discussed,and the challenges in the field are summarized.Then,a detailed classification of relevant research methods is made from the two aspects of the sensor-assisted method and of fusion-level method,which reviews the research status of this field,and summarizes and sorts out the introduced literature from the aspects of detection performance,complexity,cost size,and target(quantity,dynamic and dimension),etc.Finally,research prospects in this field are summarized.