Abstract: Aiming at the target recognition problem of multisensor with multiple characteristic indexes, a new fusion method was proposed combining Fisher discrimination and principle component. The method merged the number of discrimination functions to reduce the workload of recognition, and utilized the theory of Fisher discrimination to recognize targets. It is very suitable for the recognition of multitargets, very simple to compute, and can be performed on computer easily. The applied example proves that the method is effective.

Key words: multi-sensors, data fusion, principle component analysis, Fisher discrimination

摘要： 针对具有多个特征指标的多传感器目标识别问题，提出了一种Fisher判别和主成分相结合的信息融合方法。该方法利用主成分分析法融合判别函数的个数，减少识别工作量，基于Fisher判别理论进行目标的识别。该方法特别适用于多个目标的识别，计算简单，易于计算机上实现。应用实例验证了算法的有效性。

关键词: 多传感器, 数据融合, 主成分分析, Fisher判别