Welcome To WUJNS
武汉大学学报 英文版 | Wuhan University Journal of Natural Sciences
Wan Fang
Wuhan University
Latest Article
An Improved Underwater Confrontation Simulation Method of Naval Amphibious Operational Training System
LIU Yu, LI Dan, ZHENG Chundi
Unit 91976 of the Chinese PLA, Guangzhou 510430, Guangdong, China
This paper described an improved underwater confrontation simulation method of naval amphibious operational training system. The initial position of submarine forces on the enemy is generated automatically, and the attacking distance model of torpedoes is established based on the kinematics theory, which is more flexible and reasonable to judge the launch condition compared to traditional method. The two kinds of confrontation behavior models on the enemy submarine are created to depict its tactical action from the defensive to the offensive as well as the contrary, ensuring that operational style is simulated more comprehensively and properly. The existing motion trajectory estimation and collision detection algorithms on operational platforms are also improved to reduce the iteration error and further enhance the detection accuracy of target hit.
Key words:combat training system; military modeling and simulation; striking distance model; motion trajectory estimation; collision detection
CLC number:TP 391.4
[1]	Felix K, Chang O. China’s naval rise and the South China Sea: An operational assessment[J]. Orbis, 2012, 56(1):19-38.
[2]	Bakhyt M, Zhanar O, Madina A, et al. A model of virtual training application for simulation of technological processes[J]. Procedia Computer Science, 2015, 56:177-182.
[3]	Neil V H, Bodgan G, Venketesh N, et al. An overview of self-adaptive technologies within virtual reality training[J]. Computer Science Review, 2016, 22(11):65-68.
[4]	Christian D, Walter S, Martin K. Simulation-based mul-ti-objective system optimization of train traction systems [J]. Simulation Modeling Practice and Theory, 2017, 72: 104- 117.
[5]	Ngan S C. Evidential reasoning approach for multi-ple-criteria decision making: A simulation-based formulation[J]. Expert Systems with Applications, 2015, 42(9):4381-4396.
[6]	Tian Y L, Hu L, Jiao Y, et al. Evaluation of simulation- based training for aircraft carrier marshalling with learning cubic and Kirkpatrick’s models[J]. Chinese Journal of Aeronautics, 2015, 28(1):152-163.
[7]	Wang J, Lin Y I, Hou S Y. A data mining approach for training evaluation in simulation-based training[J]. Computers & Industrial Engineering, 2015, 80(2):171-180.
[8]	Hayri O, Philip W, Scott A, et al. A dynamic simula-tion/optimization model for scheduling restoration of de-graded military training lands[J]. Journal of Environmental Management, 2016, 171(4):144-157.
[9]	Richard A, James D, James K, et al. A real-time near shore wave and current prediction system[J]. Journal of Marine Systems, 2008, 69(1):37-58.
[10]	Tencer L, Reznakova M, Cheriet M. Summit-training: A hybrid semi-supervised technique and its application to classification tasks [J]. Applied Soft Computing, 2017, 50(1): 1-20.
Welcome To WUJNS

HOME | Aim and Scope | Editoral Board | Current Issue | Back Issue | Subscribe | Crosscheck | Polishing | Contact us Copyright © 1997-2019 All right reserved