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Threat assessment of targets serves as a critical reference for commanders in wartime decision-making. With the rapid development of unmanned systems and smart technologies, the future of warfare is progressing toward unmanned, multi-domain, and clustered operations. However, existing studies on target threat assessment fall short of effectively satisfying these demands of future warfare, demonstrating three main issues: 1) Majority of combat scenarios focus on singular settings, such as maritime air defense, air-to-air combat, and ground-based air defense, with scant research on multi-domain operations (land, low-altitude, and electromagnetic environments). 2) Research is mainly concentrated on individual entities or cluster targets, such as fighter aircraft, unmanned aerial vehicle swarms, and unmanned surface vessels, with inadequate investigation of clustered equipment integrating manned/unmanned ground combat vehicles and low-altitude manned/unmanned aircraft. 3) Current methodologies predominantly consider the state and characteristics of Blue Force targets, ignoring the influence of dynamic changes in Red Force equipment on the weighting of threat indicators for Blue Force targets.
To deal with these problems, we proposed a dynamic assessment method for threats to clustered targets in low-altitude, multi-domain battlefields based on hesitant fuzzy sets. First, we explored the laws governing low-altitude, multi-domain battlefields and the operational characteristics of clustered equipment that involves manned/unmanned air and ground elements. We analyzed five major influencing factors in the threat assessment of cluster targets, namely, operational cluster type, urgency, comprehensive strike capability, intelligent collaborative capability, and importance of the attack area, and determine an indicator system for threat assessment of clustered targets. Afterward, leveraging the Weber-Fechner law, we explored the relationship between changes in the Red Force's situation and the psychological pressure experienced by commanders and proposed a Weber-Fechner law-based weight determination method, which adjusted the weight values of the Red Force's comprehensive strike capability and the Blue Force's air power strike capability in conjunction with variations in the damage rate of the Red force's air defense capability. Finally, by combining the variable weight method under a hesitant fuzzy environment, a dynamic assessment model based on hesitant fuzzy sets for threats to cluster targets in low-altitude, multi-domain battlefields was constructed.
In a simulation, when the Red Force's air defense system sustains serious damage, the threat posed by the Blue Force's air power intensifies significantly. By utilizing the Weber-Fechner law-based weight adjustment method, the weight determination becomes more scientifically reasonable, effectively and promptly reflecting the psychological changes encountered by commanders when faced with the stimulation of the battlefield situation and reducing the subjectivity and arbitrariness related to weight optimization adjustments. Comparative analysis of the threat assessment results under constant and variable weights demonstrates that cluster targets with air power superiority exhibit more sensitive and timely adjustments in threat assessment results under variable weight conditions with a higher level of consistency.
These results further confirm the accuracy and effectiveness of the model, providing commanders with feasible and reliable decision support.
JIANG J X. Threats and countermeatures of unmanned aerial vehicle swarm to aerial defense [J]. National Defense Technology, 2019, 40(6): 108-113. (in Chinese)
XU T L, LIU F, XIAO Y J, et al. Operational application and technology development of foreign UAV swarm [J]. Journal of China Academy of Electronics and Information Technology, 2023, 18(10): 946-951. (in Chinese)
FENG W, CUI D H, LIU H X, et al. Influence of warhead parameters of munitions against USV group on combat effectiveness [J]. Acta Armamentarii, 2022, 43(S2): 26-31. (in Chinese)
WANG B, LI X J, XIONG Y. Challenges and countermeasures for unmanned combat vehicles in complex electromagnetic environments [J]. Environmental Technology, 2023, 41(10): 6-10. (in Chinese)
WANG Q P, LI J C, WANG H. The coming robot legion for battle [J]. Small Arms, 2022(08): 48-51. (in Chinese)
WANG B H, YANG X F, ZHANG Q F, et al. Review of multi-target threat assessment and attack optimizationin complex underwater battlefield environment [J]. Fire Control & Command Control, 2022, 47(8): 177-182. (in Chinese)
GAO G H, DING H Y, TENG Z W. Application of analytic hierachy process for the multi-targets of submarine threat-evaluation [J]. Command Control & Simulation, 2008, 30(5): 37-39. (in Chinese)
WANG B H, HUANG J G, ZHANG Q F. Underwater multi-target threat evaluation model based on analytic hierarchy process [J]. Ship Science and Technology, 2006, 28(6): 75-77. (in Chinese)
MA L, SONG G B, JI L C, et al. Evaluation of target threat based on least square gray correlation analysis method [J]. Tactical Missile Technology, 2010(1): 28-31. (in Chinese)
XU Z W, NING Z M, WEI M, et al. Evaluation of target threat based on AHP and GIA [J]. Science Mosaic, 2009(9): 16-18. (in Chinese)
ZHANG Y F, LIU J S, ZHANG S F. A multi-attribute threat assessment method based on analytical hierarchy process and entropy method [J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2019, 39(2): 163-165. (in Chinese)
ZHAO M, WANG M Y, YIN S B. Variable weight TOPSIS ballistic target threat assessment model based on subjective and objective combination weighting [J]. Military Operations Research and Assessment, 2023, 38(1): 27-33. (in Chinese)
HOU S Y, LI Y G, CHEN S J, et al. Multi-target threat assessment using subjective and objective integrated weighting method [J]. Telecommunication Engineering, 2019, 59(8): 956-961. (in Chinese)
JIN C, SUN J, WANG Y J, et al. Threat comprehensive assessment for air defense targets based on intuitionistic fuzzy TOPSIS and variable weight VIKOR [J]. Systems Engineering and Electronics, 2022, 44(1): 172-180. (in Chinese)
ZHAO M, WANG M Y, WANG J, et al. TOPSIS ballistic target threat assessment based on variable weight theory [J]. Journal of Information Engineering University, 2023, 24(1): 113-119. (in Chinese)
LI W, LU Y Q, FAN C L, et al. Threat assessment of aircluster based on battlefield situation variable weight [J]. Journal of Air Force Engineering University (Natural Science Edition), 2022, 23(3): 89-96. (in Chinese)
JIN L Q, XU Y. Method for uncertain multi-attribute decision making based on evidential reasoning and third-generation prospect theory [J]. Control and Decision, 2016, 31(1): 105-113. (in Chinese)
WANG G G, GUO L H, DUAN H. Wavelet neural network using multiple wavelet functions in target threat assessment [J]. The Scientific World Journal, 2013, 2013: 632437.
YAN D, CHEN M, WU Q X, et al. Determining safe flight area of UAVs based on variable weight threat assessment [J]. Scientia Sinica Informationis, 2021, 51(4): 663-677. (in Chinese)
SUN H W, YU S Z, JIANG Y, et al. Target threat assessment method for UAV swarm at sea [J]. Acta Armamentarii, 2022, 43(S2): 32-39. (in Chinese)
PU H P, WANG F S, ZHENG Z Q. TOPSIS method of command post threat assessment based on UAV raid [J]. Command Control & Simulation, 2022, 44(6): 29-34. (in Chinese)
WANG Q, GAN X S, YU H L, et al. SPA-IELM assessment method of time-sensitive-target threat degree for UAV air-to-ground attack [J]. Fire Control & Command Control, 2021, 46(7): 142-148. (in Chinese)
XU Y J, WANG Y C, MIU X D. Multi-attribute decision making method for air target threat evaluation based on intuitionistic fuzzy sets [J]. Journal of Systems Engineering and Electronics, 2012, 23(6): 891-897.
DEHAENE S. The neural basis of the Weber-Fechner law: A logarithmic mental number line [J]. Trends in Cognitive Sciences, 2003, 7(4): 145-147.
LI D Q, ZENG W Y, MA R. Variable weight synthesis under hesitant fuzzy environment and its application in group decision making [J]. Mathematics in Practice and Theory, 2020, 50(11): 191-198. (in Chinese)
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