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复杂战场环境下的任务驱动智能目标识别方法综述

罗志军 王健瑞 殷佳伟

空天防御2026,Vol.9Issue(1):1-11,11.
空天防御2026,Vol.9Issue(1):1-11,11.

复杂战场环境下的任务驱动智能目标识别方法综述

A Survey of Task-Driven Intelligent Target Recognition Methods in Complex Battlefield Environments

罗志军 1王健瑞 2殷佳伟2

作者信息

  • 1. 上海航天技术研究院,上海 201109
  • 2. 上海机电工程研究所,上海 201109||自动目标识别重点实验室(上海),上海 201109
  • 折叠

摘要

Abstract

Complex battlefield environments are characterised by diverse target types,intricate task constraints,and highly dynamic environmental conditions,thereby imposing requirements on intelligent target recognition that go beyond conventional optimisation of perceptual accuracy.In these environments,recognition results are not only used to describe target attributes but also directly affect the reliability of task planning and decision-making.However,most current target recognition research mainly concentrates on static scenarios and perception-based metrics,which do not adequately capture the practical significance of recognition results in task execution.To address this gap,a task-driven paradigm for target recognition has gradually emerged in recent years,in which task-related information is explicitly incorporated into model design,training,and evaluation,thereby enabling recognition results to support task deployment and system-level decision-making better.Following this research trend,this paper presents a systematic survey of task-driven intelligent target recognition methods from a methodological perspective.Firstly,the fundamental concepts of task-driven target recognition were analysed,and its key differences from traditional perception-driven approaches were clarified with respect to output representations,optimisation objectives,and system role positioning.Then,from the perspective of task-related information modelling,existing methods were systematically reviewed with respect to semantic and attribute representations,target state and behaviour modelling,and uncertainty and risk representation.After that,task-constraint modelling during training and optimisation,as well as the collaborative interfaces between recognition outputs and task-execution and decision modules,were further discussed.Finally,using the typical demands of complex battlefield environments as a key context,the paper summarized the major challenges in task-driven target recognition,including adapting to dynamic environments,managing unknown targets,ensuring trustworthy uncertainty representation,and coordinating at the system level.It also outlines potential directions for future research.

关键词

任务驱动目标识别/复杂战场环境/任务相关信息建模/不确定性与风险表达/深度学习

Key words

task-driven target recognition/complex battlefield environments/task-related information modelling/uncertainty and risk representation/deep learning

分类

信息技术与安全科学

引用本文复制引用

罗志军,王健瑞,殷佳伟..复杂战场环境下的任务驱动智能目标识别方法综述[J].空天防御,2026,9(1):1-11,11.

基金项目

ATR重点实验室基金资助项目(JKWATR-230102) (JKWATR-230102)

空天防御

2096-4641

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