自动目标识别的工程视角述评

郁文贤

doi:10.12000/JR22178

自动目标识别的工程视角述评

DOI: 10.12000/JR22178

郁文贤^,

上海交通大学电子信息与电气工程学院上海 200240

基金项目: 国家自然科学基金重点项目(61331015)

详细信息

作者简介:
郁文贤，博士，讲席教授，教育部长江学者特聘教授，主要研究方向为自动目标识别、智能信息处理、融合导航定位等

通讯作者:
郁文贤 wxyu@sjtu.edu.cn

责任主编：杜兰 Corresponding Editor: DU Lan
中图分类号: TN957
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- 文章访问数: 1441
- HTML全文浏览量: 629
- PDF下载量: 297
- 被引次数: 0
出版历程
- 收稿日期: 2022-08-02
- 修回日期: 2022-10-12
- 网络出版日期: 2022-10-19
- 刊出日期: 2022-10-28

Automatic Target Recognition from an Engineering Perspective（in English）

YU Wenxian^,

School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Funds: State Key Program of the National Natural Science Foundation of China (61331015)

More Information

Corresponding author: YU Wenxian, wxyu@sjtu.edu.cn

摘要

摘要:
自动目标识别(ATR)是一个和信号与信息处理、模式识别、人工智能等学科密切相关的特殊工程技术应用领域。由于ATR系统识别对象固有的不确定性，识别环境的复杂性，以及日益加剧的识别对抗性，使得ATR的发展一直面临着从理论到技术、到应用的系统性挑战。该文从工程视角出发，阐述了ATR的定义与内涵，简要回顾与分析了该领域发展动态，梳理了ATR的核心技术体系与系统开发模式，最后对未来的发展挑战做了分析。
- 自动目标识别 /
- 环境复杂性 /
- 识别对抗性 /
- 技术体系 /
- 工程应用
Abstract:
Automatic Target Recognition (ATR) is a special engineering application field which is closely related to signal and information processing, pattern recognition, artificial intelligence and other disciplines. Owing to the inherent uncertainty of ATR systems, the complexity of the recognition environment, and the increasingly adversarial nature of recognition, the development of ATR faces systematic challenges from theory to technology and applications. This paper presents the definition and connotation of ATR from an engineering perspective, briefly reviews and analyzes the developments in this field, explores the core technology system and system development model of ATR, and finally examines the future development challenges.
- Automatic Target Recognition (ATR) /
- Environmental complexity /
- Identification antagonism /
- Technology system /
- Engineering application

HTML全文

图 1 ATR的认知视角

Figure 1. Perspectives of ATR

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图 2 ATR在OODA中的功能描述(检测、跟踪、定位、识别、预测)

Figure 2. Functions of ATR in OODA (detection, tracking, locating, recognition, and prediction)

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图 3 ATR中任务与资源优化调度

Figure 3. Optimal task and resource scheduling in ATR

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图 4 多源融合层次化结构

Figure 4. Hierarchical structure of multi-source fusion

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图 5 ATR在线学习自演进架构^[8]

Figure 5. ATR online learning and self-evolving architecture^[8]

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图 6 MSTAR部分数据样本

Figure 6. Data samples of MSTAR

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图 7 OpenSARShip部分数据样本

Figure 7. Data samples of OpenSARShip

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图 8 ATR数据信息能力的核心技术构成示意图

Figure 8. Illustration of the core technologies of ATR competence regarding data information

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图 9 ATR信息认知能力的核心技术构成示意图

Figure 9. Illustration of the core technologies of ATR competence regarding information recognition

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图 10 ATR Core的核心技术构成示意图

Figure 10. Illustration of the key technologies of ATR Core

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图 11 ATR应用从封闭走向开放

Figure 11. ATR application: from close form to open form

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图 12 迭代演进开发模式演进流程

Figure 12. Process of iteratively-evolving development patterns

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图 13 雷达目标识别系统的迭代增长式工程开发模式

Figure 13. An iteratively incremental engineer development model for a radar target recognition system

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图 14 百度Apollo 6.0开放生态环境示意图

Figure 14. Illustration of Baidu Apollo 6.0 open ecological environment

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图 1 Perspectives of ATR

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图 2 Functions of ATR in OODA (detection, tracking, locating, recognition, and prediction)

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图 3 Optimal task and resource scheduling in ATR

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图 4 Hierarchical structure of multi-source fusion

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图 5 ATR online learning and self-evolving architecture

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图 6 Data samples of MSTAR

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图 7 Data samples of OpenSARShip

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图 8 Illustration of the core technologies of ATR competence regarding data information

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图 9 Illustration of the core technologies of ATR competence regarding information recognition

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图 10 Illustration of the key technologies of ATR Core

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图 11 ATR application: from close form to open form

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图 12 Process of iteratively-evolving development patterns

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图 13 An iteratively incremental engineer development model for a radar target recognition system

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图 14 Illustration of Baidu Apollo 6.0 open ecological environment

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