信息不完备条件下基于IOWA-TOPSIS的辐射源威胁评估

IOWA-TOPSIS Based Radiator Threat Assessment with Incomplete Information

针对信息不完备条件下的辐射源威胁评估问题,提出一种基于IOWA-TOPSIS的评估算法。首先,针对实际作战过程中易出现的敌方辐射源信息不完备情况,引入诱导有序加权平均(IOWA)空值估计算法,基于属性集的关联性预测缺失数据;然后,采用改进的基于指标相关性的指标权重确定(CRITIC)分析不同属性对评估过程的影响程度,客观分配权重;最后,通过逼近理想解排序(TOPSIS)算法度量不同辐射源威胁程度,并进行威胁等级排序。仿真实验结果表明,所提算法能有效实现辐射源威胁评估,相较于传统评估方法,结果更加客观、可靠。

Regarding the problem of radiator threat assessment under incomplete information,an assessment algorithm based on IOWA-TOPSIS is proposed.Firstly,in view of the incomplete information of enemy radiator which is easy to occur in actual combat,the Induced Ordered Weighted Averaging(IOWA) null value estimation algorithm is introduced to predict the missing data based on the correlation of attribute sets.Then,Criteria Importance Through Intercriteria Correlation(CRITIC) is used to analyze the influence degree of different attributes on the assessment process and assign weights objectively.Lastly,the threat degree of different radiator is measured by Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) algorithm, and the threat level is ranked.The simulation results show that the algorithm can effectively evaluate the threat of radiator,and the results are more objective and accurate than those of traditional assessment methods.