一种威胁指数加权的截击引导航线解算算法

doi:10.16182/j.issn1004731x.joss.22-0004

摘要/Abstract

摘要：

截击引导和威胁评估是指挥控制中不可分割的两部分，前者通过航线解算进而实施具体的指挥引导，后者通过计算确定威胁程度高低进而取得态势优势为指挥控制提供依据。以威胁指数为权重，将解算出的引导航线与之加权，提出了一种最优截击指标用以确定威胁程度最小的引导航线解算算法。仿真结果表明：该算法可有效解算出威胁最小的截击航线，且在不同态势、不同威胁权重取值等情况下均可靠。该算法为指挥控制中引导解算方法提供了新思路。

关键词: 指挥控制, 指挥引导, 引导解算, 威胁评估, 威胁指数

Abstract:

Interception guidance and threat assessment are two inseparable parts of command and control. The former implements specific command and guidance through guidance solutions, and the latter provides basis for threat assessment and situation advantage to command and control. Taking threat indexes as the weight, a kind of optimal interception route index is proposed to obtain the guidance solution with the least threat. Simulation results show that the proposed algorithm can effectively provide routing solutions for interception with the least threat, and is reliable under different situations, or with different weights of threat indexes. The algorithm provides a new idea for obtaining route solutions in the field of command and guidance.

Key words: command and control, command and guidance, guidance solution, threat assessment, threat index

中图分类号:

V249

刘书元. 一种威胁指数加权的截击引导航线解算算法[J]. 系统仿真学报, 2023, 35(5): 971-978.

Shuyuan Liu. An Algorithm for Obtaining Interception Guidance Routes Weighted by Threat Indexes[J]. Journal of System Simulation, 2023, 35(5): 971-978.

图/表 8

图1

图2

图3

表1

引导解算结果

参数	数值	参数	数值
$θ o$ /(°)	61	\| $w 1 w 2 ⃗$ \|/km	212
(n₁， n₂)	(-1， -1)	I( $θ o$ )/km	46
(φ₁， φ₂)/(°)	(65， 24)	L/km	277

表1

表2

表3

不同态势下引导解算结果

θ_o/(°)	(n₁， n₂)	(φ₁， φ₂)/(°)	\| $w 1 w 2 ⃗$ \|/km	I(θ_o)/km	L/km
21	(-1， 1)	(10， 29)	360	59	401
66	(1， -1)	(29， 23)	221	46	269
174	(-1， 1)	(35， 1)	42	22	83
52	(-1， -1)	(184， 44)	72	46	202
111	(-1， -1)	(153， 16)	129	37	231

表3

表4

不同威胁权重下引导解算结果

(α_a， α_d， α_v)	θ_o/(°)	(n₁, n₂)	(φ₁, φ₂)/(°)	\| $w 1 w 2 ⃗$ \|/km	I(θ_o)/km	L/km
(0.2， 0.6， 0.2)	68	(-1， -1)	(67， 15)	212	38	273
(0.6， 0.2， 0.2)	56	(-1, -1)	(64, 30)	214	58	281

表4

表5

不同距离威胁参数下引导解算结果

(d_R， d_M， d_KMax)/km	θ_o/(°)	(n₁， n₂)	(φ₁， φ₂)/(°)	\| $w 1 w 2 ⃗$ \|/km	I(θ_o)/km	L/km
(140， 90， 60)	56	(-1， -1)	(64， 30)	214	48	281
(100， 70， 40)	64	(-1， -1)	(66， 20)	212	44	275

表5

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态势	M₀=(x， y) km	v_m/(km/h)	K_m/(°)
1	(200， 250)	960	120
2	(250， -250)	1 000	20
3	(150， 150)	1 200	220
4	(-250， 250)	2 200	160
5	(-250， 200)	700	160

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