Abstract: This paper suggests a method of temporal finite automata modeling for data association problem. A lot of data association algorithm is proposed, but there is no data association model for the performance evaluation. In order to support temporal observation for data association, timed sequence is introduced to finite automata, and temporal finite automata is defined to model data association problem. This method is applied to validate the veracity of multi-target track.

Key words: Data fusion, Data association, Temporal finite automata(TFA), Finite automata(FA), Modeling

摘要： 介绍了一种用时序自动机为数据关联问题建模的方法，对数据关联问题的研究方法做了新的尝试。目前有多种数据关联算法，对这些方法的分析和评价成为急于解决的问题。鉴于观测信息的时序性，该文以有限自动机(FA)为基础，将时间序列引入到有限自动机中，定义了时序有限自动机(TFA)，建立了数据关联(DA)的时序有限自动机模型，用于判断关联算法得到的航迹准确性。

关键词: 数据融合, 数据关联, 时序有限自动机, 有限自动机, 建模