摘要
文章给出了一个新的应用遗传算法技术的分级多传感器数据融合算法，各个传感器信息之间的关系用一种较新的模糊算子确定，与传统的集合论的并、交操作相比，它能更好地模仿人的推理。此外，遗传算法能近似最优地确定模糊算子的参数，使算法在信息源的可靠性、信息的冗余度／互补性以及进行融合的分级结构不确定的情况下，以近似最优的方式对传感器数据进行融合。
The paper describes a novel hierarchical multisensor data fusion algorithm adopting genetic algorithm. The relations of sensors are determined by means of fuzzy set operator that is better in mimicking the human reasoning process than the union and the intersection employed by traditional set theories. The parameters of the operator are found by genetic algorithms nearly optimally. The distinctive feature of the algorithm is its capability of fusing data in a near optimal manner when no information about .the reliability of the information sources, the degree of redundancy/ complementarity of the information sources, and the structure of the hierarchy is available.
出处
《微电子学与计算机》
CSCD
北大核心
1999年第2期22-27,共6页
Microelectronics & Computer
基金
电科院基金
