Journal of Computer Applications ›› 2013, Vol. 33 ›› Issue (04): 1179-1182.DOI: 10.3724/SP.J.1087.2013.01179

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Threat modeling and assessment of unmanned aerial vehicle under complicated meteorological conditions

WU Zhongjie,ZHANG Yaozhong,WANG Qiang   

  1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an Shaanxi 710129, China
  • Received:2012-10-25 Revised:2012-11-24 Online:2013-04-01 Published:2013-04-23
  • Contact: WU Zhongjie
  • Supported by:

    the Aeronautical Science Foundation of China under Grant

无人机复杂气象威胁建模及评估方法

吴忠杰,张耀中,王强   

  1. 西北工业大学 电子信息学院,西安 710129
  • 通讯作者: 吴忠杰
  • 作者简介:吴忠杰(1986-),男,四川绵阳人,硕士研究生,主要研究方向:无人飞行器任务规划、复杂系统建模;张耀中(1974-),男,河南舞阳人,副教授,博士,主要研究方向:先进火力指挥控制原理、复杂系统建模、智能化指挥与控制工程;王强(1984-),男,湖北宜昌人,博士研究生,主要研究方向:无人飞行器任务规划、复杂系统建模。
  • 基金资助:

    航空科学基金资助项目(2011ZC53024)

Abstract: To study the effect of meteorological conditions on Unmanned Aerial Vehicle (UAV), an algorithm of multi-level fuzzy comprehensive evaluation method based on threat value was proposed. This algorithm improved a two-level weight value determination and the comprehensive evaluation model, which can get the comprehensive threat index after being calculated. The simulation results show that this algorithm can assess the degree of weather threat accurately and have faster operation speed, smaller error and lower complexity. The efficiency and validity have also been improved.

Key words: weather, threat modeling, fuzzy comprehensive evaluation, Unmanned Aerial Vehicle (UAV), Back-Propagation (BP) neural network

摘要: 为评价无人机执行任务时气象因素的威胁程度,在建立气象评价指标体系和量化各种气象等级基础上,提出一种基于威胁强度的多级模糊综合评判方法。该方法改进了两级权重确定模型和综合评估模型,并经过计算得到综合威胁指数。通过实例验证,结果表明该方法能够准确评估气象对无人机的威胁程度,与传统模糊评判方法和BP评估方法相比,具有速度更快、误差更小和复杂度更低的特点,提高了评估效率和有效性。

关键词: 气象, 威胁建模, 模糊评价, 无人机, BP神经网络

CLC Number: