摘要
多源信息融合经过近20年的发展已经取得了丰富的理论成果和应用成果,但是其理论框架尚未建立。近几年由Mahler提出的有限集合统计学(FISST)理论——随机集理论的特例,从概率论角度统一表述了信息融合技术的主要方面。该文对近十几年随机集信息融合技术的发展加以回顾,主要包括随机集理论的产生背景、基本的思想和理论框架,以及当前的应用领域。最后指出了随机集理论将来可能的发展方向。
The theory and method of multi-source information fusion have acquired plenty of the outcomes in the past 20 years. However the theoretical framework of information fusion is not established up to the present. Recently the finite set statistics （FISST） approach, a special random set method, has been proposed by Mahler. FISST provides a fully unified probabilistic foundation for the major aspects of multi-source information fusion. This paper reviews several main aspects of the random set information fusion research that include the background, the key ideas, the theoretical framework and the applications of FISST. Finally several possible future directions of FISST are discussed,
出处
《电子与信息学报》
EI
CSCD
北大核心
2006年第11期2199-2204,共6页
Journal of Electronics & Information Technology
基金
国家自然科学基金重点项目(60602049
60434020)资助课题
关键词
信息融合
随机集
有限集合统计学
多目标跟踪
贝叶斯滤波
Information fusion, Random sets, Finite set statistics, Multi-target tracking, Bayesian filtering
