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一种高分辨率雷达海上目标自适应检测器
  • ISSN号:ISSN-16722337 CN341264/TN
  • 期刊名称:雷达科学与技术
  • 时间:2013.10.24
  • 页码:516-521
  • 分类:V271.4[航空宇航科学与技术—飞行器设计;航空宇航科学技术] TP391.9[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]海军航空工程学院,山东烟台264001
  • 相关基金:国家自然科学基金(61102166)
  • 相关项目:非高斯背景下距离扩展目标多层次信号自适应智能检测技术研究
中文摘要:

针对目前多计算机生成兵力(ComputerGeneratedForce,CGF)协同反潜中无法充分利用战场信息实现CGF搜潜策略优化的问题,在CGF间可有效实现信息交互的前提下,将信息融合技术引入到反潜作战仿真中;利用BP(BackPropagation)人工神经网络获取证据信息的基本置信分配,通过改进的D-S(Dempster—Shafer)证据理论对反潜CGF获取的信息进行综合,以此改进反潜CGF的移动策略。仿真实验表明,在反潜CGF搜潜过程中引入人工神经网络和信息融合技术,可有效提高CGF搜潜的成功率。

英文摘要:

Since the Computer Generated Force (CGF) can not take full advantage of battlefield information to optimize CGF submarine search strategy in the cooperative anti-submarine con~bat, the information fusion technology was introduced into the anti-submarine warfare simulation based on the effective interaction of the information between CGF. The basic confidence assignment of the evidence information was obtained using Back Propagation (BP) artificial neural network, and the information from antisubmarine CGF was synthesized by using the improved DS evidence theory. And thus the anti-submarine CGF mobile strategy was improved. Simulation results show that the introduction of artificial neural network and information fusion technology in antisubmarine CGF submarine search process can improve the anti-submarine efficiency.

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