A Target Group Value Assessment Method Driven by Observable Information in Non-transparent Scenarios

XUE Yuyang; WANG Tao

doi:10.12382/bgxb.2025.0966

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A Target Group Value Assessment Method Driven by Observable Information in Non-transparent Scenarios

更新时间：2026-04-15

- A Target Group Value Assessment Method Driven by Observable Information in Non-transparent Scenarios
- Acta Armamentarii (2026)
- 作者机构：
  
  1. 中山大学智能工程学院,广东,深圳,518107
  2. 南方海洋科学与工程广东省实验室,广东,珠海,519082
  3. 中山大学人工智能研究院群体智能研究中心,广东,广州,510275
- 作者简介：
- 基金信息：
- DOI：10.12382/bgxb.2025.0966
  CLC： E91
- Received：29 October 2025，
  
  Online First：15 April 2026，
- 稿件说明：
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薛羽阳，王涛. 非透明场景下基于指标关联特征的地面目标群价值评估方法[J/OL]. 兵工学报, 2026(2026-04-15). https://doi.org/10.12382/bgxb.2025.0966.

XUE Y Y, WANG T. A target group value assessment method driven by observable information in non-transparent scenarios[J/OL]. Acta Armamentarii, 2026(2026-04-15). https://doi.org/10.12382/bgxb.2025.0966. (in Chinese)
薛羽阳，王涛. 非透明场景下基于指标关联特征的地面目标群价值评估方法[J/OL]. 兵工学报, 2026(2026-04-15). https://doi.org/10.12382/bgxb.2025.0966. DOI：

XUE Y Y, WANG T. A target group value assessment method driven by observable information in non-transparent scenarios[J/OL]. Acta Armamentarii, 2026(2026-04-15). https://doi.org/10.12382/bgxb.2025.0966. (in Chinese) DOI：

摘要

非透明场景中，目标群体内部结构的不可知性显著增加了地面目标价值评估的复杂性与不确定性。针对这一问题，提出一种基于指标关联特征的地面目标群价值评估方法。通过围绕群体层与个体层构建的双维度指标体系，并基于多源可观测信息设计指标量化模型，有效表征目标群体的协同能力与分布态势，以及个体成员的实时状态和功能。在层次分析法获得专家主观权重的基础上，引入动态关联-层级校准机制，采用互信息关联度、皮尔逊互补性和主成分预测性关联度等关联特征进行指标关联分析，并结合信息熵理论实现权重的自适应融合。仿真结果表明，该方法能够在非透明场景中下获得均衡、可解释的目标价值评估结果，评估模型且具有良好的实时性与鲁棒性。

Abstract

In non-transparent scenarios

the unknown internal structure of target groups significantly increases the complexity and uncertainty of ground target value assessment. To address this issue

this paper proposes a ground target group value assessment method based on indicator association features. A dual-level indicator system is constructed at both the group and individual levels

and indicator quantification models are designed based on multi-source observable information to effectively represent the cooperative capability and distribution patterns of the target group

as well as the real-time status and functionality of individual members. Building on expert subjective weights obtained via the Analytic Hierarchy Process (AHP)

a dynamic correlation-hierarchicalcalibration(DCHC) mechanism is introduced. Indicator correlation analysis is performed using association features

including mutual information correlation

Pearson complementarity

and principal component predictive correlation

and adaptive weight fusion is achieved through information entropy theory. Simulation results demonstrate that the proposed method can provide balanced and interpretable target value assessments in non-transparent scenarios

with good real-time performance and robustness.

关键词

Keywords

references

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