基于关注势的战场态势热力图构建方法

doi:10.3969/j.issn.1001-506X.2021.01.15

摘要/Abstract

摘要：

面对高度复杂和多变的现代战场,如何快速直观地发现战场上的态势热点,降低认知负载是指挥员所面临的巨大挑战。针对战场时变条件下的态势热点发现问题,在分析热点形成机理的基础上,提出关注势理论,构建了符合人类认知特性的改进的Logistic时间衰减函数(improved Logistic time decay function, ILTDF),进而提出随时间衰减的加权核密度估计(weighted kernel density estimation decay over time, W-KDE-DOT)法以及基于关注势的战场态势热力图构建方法。实验结果表明,基于关注势理论的热力图构建方法,能够更准确地刻画出态势热点的时变特性,更符合战场态势热点发现客观规律,能够更好地为指挥决策人员准确把握战场态势热点提供支撑。

关键词: 态势感知, 关注势, 热力图, 加权核密度估计法, 时间衰减函数

Abstract:

In the face of highly complex and changeable modern battlefield, how to quickly and intuitively find the situation hot spots on the battlefield and reduce the cognitive load is a great challenge for commanders. Aiming at the problem of finding hot spots in battlefield situation under time-varying conditions, on the basis of analyzing the forming mechanism of hot spots, the theory of attention potential is put forward, and the improved logistic time decay function (ILTDF) in line with human cognitive characteristics is constructed. Then the weighted kernel density estimation decay over time (W-KDE-DOT) and the construction method of the heat map of the battlefield situation based on attention potential are proposed. The experimental results show that the heat map construction method based on the theory of attention potential can depict the time-varying characteristics of the situation hot spots more accurately. And the proposed method is more consistent with the objective law of battlefield situation hot spot discovery, and can provide support for commanders and decision-makers to accurately grasp the battlefield situation hot spot.

Key words: situation awareness, attention potential, heat map, weighted kernel density estimation (W-KDE) method, time decay function

中图分类号:

E917

董浩洋, 张东戈, 齐宁, 禹明刚, 牛彦杰. 基于关注势的战场态势热力图构建方法[J]. 系统工程与电子技术, 2021, 43(1): 121-129.

Haoyang DONG, Dongge ZHANG, Ning QI, Minggang YU, Yanjie NIU. Construction method of battlefield situation heat map based on attention trends[J]. Systems Engineering and Electronics, 2021, 43(1): 121-129.

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组	目标	坐标	各时间步通信频次(次/10 s)
组	目标	坐标	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
1	a	(320, 80)	14.3	14.3	14.3	14.3	14.3	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5
	b	(329, 136)	14.3	14.3	14.3	14.3	14.3	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5
	c	(280, 113)	14.3	14.3	14.3	14.3	14.3	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5
2	d	(100, 119)	14.6	14.3	14.6	14.6	13.9	14.6	14.3	14.6	14.6	13.9	14.6	14.3	14.6	14.6	13.9	14.6	14.3	14.6	14.6	14.6
2	e	(50, 143)	14.6	14.6	14.5	14.6	14.4	14.6	14.6	14.5	14.6	14.4	14.6	14.6	14.5	14.6	14.4	14.6	14.6	14.6	14.6	14.6
3	f	(66, 307)	14	14	14	5.5	5.5	5.6	5.2	5.5	5.3	5.5	5.6	5.5	5.6	5.5	14	14	14	5.5	5.6	5.5
	g	(88, 350)	14	14	14	5.5	5.5	5.4	5.5	5.6	5.6	5.5	5.4	5.5	5.4	5.1	14	14	14	5.5	5.6	5.5
	h	(36, 336)	14	14	14	5.5	5.4	5.7	5.5	5.4	5.4	5.7	5.4	5.5	5.4	5.7	14	14	14	5.5	5.4	5.5
其他目标			5	5.2	5.6	5.1	5.0	5.2	5	5.6	5.1	5.0	5.2	5.1	5.0	5.6	5.1	5.0	5.2	5.1	5.0	5.2

组	目标	坐标	各时间步影响因子函数值
组	目标	坐标	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
1	a	(320, 80)	14.3	14.3	14.3	14.3	14.3	14.0	14.0	13.9	13.9	13.8	13.6	13.2	12.6	11.7	10.2	8.4	5.0	5.0	5.0	5.0
	b	(329, 136)	14.3	14.3	14.3	14.3	14.3	14.0	14.0	13.9	13.9	13.8	13.6	13.2	12.6	11.7	10.2	8.4	5.0	5.0	5.0	5.0
	c	(280, 113)	14.3	14.3	14.3	14.3	14.3	14.0	14.0	13.9	13.9	13.8	13.6	13.2	12.6	11.7	10.2	8.4	5.0	5.0	5.0	5.0
2	d	(100, 119)	14.6	14.3	14.6	14.6	13.9	14.6	14.3	14.6	14.6	13.9	14.6	14.3	14.6	14.6	13.9	14.6	14.3	14.6	14.6	14.6
2	e	(50, 143)	14.6	14.6	14.5	14.6	14.4	14.6	14.6	14.5	14.6	14.4	14.6	14.6	14.5	14.6	14.4	14.6	14.6	14.6	14.6	14.6
3	f	(66, 307)	14.0	14.0	14.0	14.0	14.0	13.9	13.9	13.8	13.6	13.2	12.6	11.7	10.2	8.4	14.0	14.0	14.0	14.0	14.0	13.9
	g	(88, 350)	14.0	14.0	14.0	14.0	14.0	13.9	13.9	13.8	13.6	13.2	12.6	11.7	10.2	8.4	14.0	14.0	14.0	14.0	14.0	13.9
	h	(36, 336)	14.0	14.0	14.0	14.0	14.0	13.9	13.9	13.8	13.6	13.2	12.6	11.7	10.2	8.4	14.0	14.0	14.0	14.0	14.0	13.9

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