| 摘要: |
| 非协同目标识别技术是识别领域研究的新课题，它通过处理侦测到的目标
物理特征来实现对目标身份的识别。该技术可提供更全面、更完善的战场目标信息，有助于
作战人员及时掌握战场态势、减少友军误伤。从目标识别的基础理论开始，介绍了几种适合
非协同目标识别的融合方法及其改进措施，总结了目前非协同目标识别技术研究的主要进展
，即采用基于统计推理的数据融合技术，对多个传感器侦测的目标特征信息进行处理，实现
了对属性、类型、型号、作战意图及威胁程度等目标信息的判定和分析。同时，指出国外一
些使用数据融合技术的武器装备已具备对多个非协同目标的识别能力和战场信息感知能力。
最后，提出了今后的研究方向。 |
| 关键词: 非协同目标识别 数据融合 贝叶斯推理 Dempster-Shafer证据
理论 DSmT理论 神经网络 |
| DOI： |
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| 基金项目: |
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| Research progress on non-cooperative target identification technology |
| LIANG Feng |
| () |
| Abstract: |
| The technology of noncooperative target identification(NCTI) is a new
topic in the target identification field, and the identity is indentified by pr
ocessing the detected physical characteristics of a target. Through NCTI, more c
omprehensive and thorough information of targets in battlefield can be offered.
It will help fighting men to grasp the battlefield situation in time, and contri
bute to reduce incidents of friendly fire. Starting with the theory of target id
entification,this paper introduces several data fusion methods and their improve
ments for NCTI.The current research progress is thro
ugh using data fusion technology based on statistical inference, the property,
type, model, operational intent and the degree of threat of target can be distin
guished and analysed by means of processing the target′s feature information fr
om multiple sensors. It is pointed out that some foreign weapons and equipment,
which use data fusion t
echnology, have had the capabilities of identifying several noncooperative tar
gets and battlefield information awareness.Finally,future research direction is
presented. |
| Key words: non-cooperative target identification(NCTI) data fusion Bayesian inference De
mpster-Shafer evidence theory Dezert-Smarandache theory neural network |
