基于多源冲突数据聚类的态势估计方法

传统调和式态势估计方法在面对多源冲突数据时融合效果不佳。为此,提出一种基于冲突数据聚类的非调和式态势估计方法。首先利用迭代自组织数据聚类方法(ISODATA)对多源冲突数据进行聚类,然后利用频度和可信度对数据簇的重要性进行评估,最后得到态势估计结果。仿真结果表明,与传统态势估计方法相比,所提方法在融合多源冲突数据时能够得到可信度较高的态势估计结果。

Situation Assessment Method Based on Clustering of Multi Source Conflict Data

The estimating results of traditional harmonic situation assessment methods will degrade when fusing multi-source conflict data. To this end,a new method of non-harmonic situation assessment is proposed based on conflicting data clustering in this paper. First,an iterative self-organizing data clustering method (ISODATA)is used to cluster the multi-source conflict data. Then, the importance of the data clusters is evaluated by its frequency and reliability. Finally the situation assessment results are achieved. The simulation results show that,compared with the traditional D-S evidences reasoning method,the proposed method can obtain higher confidence fusion results from multi-source conflict data.