Synthetic damage effect assessment through evidential reasoning approach and neural fuzzy inference: Application in ship target

The damage effect assessment of anti-ship missiles combines system science and weapon science, which can provide reference for the assessment of battlefield damage situation. In order to solve the difficulty of heterogeneous data aggregation and the difficulty in constructing the mapping between factors and damage effect, this paper analyzes the specific damage process of the anti-ship missile to the ship, and proposes a synthetic Evidential Reasoning (ER) – Adaptive Neural Fuzzy Inference System (ANFIS) to assess the damage effect. To solve the problem of fuzziness and uncertainty of criteria in the assessment process, the belief structure model is used to transform qualitative and quantitative information into a unified mathematical structure, and ER algorithm is used to fuse the information of lower-level criteria. In order to solve the problem of fuzziness and uncertainty of the information contained in the first-level variables, and the strong non-linear characteristics of the mapping between first-level variables and damage effect, the ANFIS with self-adaptation and self-learning is constructed. The map between the three first-level variables and damage effect is established, and the interaction process of the various factors in the damage effect assessment are clear. Sensitivity analysis shows that assessment model has good stability. The result analysis and comparative analysis show that the process proposed in this paper can effectively assess the damage effect of anti-ship missiles, and all criteria data are objective and comparable.     

面向有效载荷的准实时在轨健康评估系统

卫星遥测数据通常有2种手段获得，一种是卫星经过地面测控站下传的实时遥测和延时遥测;另一种手段是通过数传分系统下传的全球遥测。全球遥测作为监视卫星载荷健康状态的主要手段，存在数据量大、文件数量较多、人工处理和判读工作量大等问题。针对该情况，提出准实时在轨健康监视系统的设计方案。该系统具备遥测源码定时获取、有效载荷遥测数据提取和解析、遥测数据存储、遥测数据自动判读和特征统计、超限报警、曲线显示和数据输出等功能，可对卫星有效载荷的健康状态进行准实时、自动化的监视和评估。