Multiple-Surveillance Data Fusion Based on DS Reasoning and MMF

摘要：

The targets tracking in air traffic control field represents a challenge for both measurement to track association and the positional estimation algorithm. In order to solve a complicated situation due to tracking environment, a tracking filter and a data fusion algorithm are applied in this study. By applying Dempster-Shafer evidence theory based on probabilistic combination rule and multiple-model filtering algorithm utilizing information mixing, we show how to combine sensory information to acquire more reliable surveillance situation awareness. Simulation results indicate that this method has a high tracking accuracy.

关键词： Data Fusion Dempster-Shafer(DS) Theory Multiple-Model Filler

作者: Liu Jing Yang Xiaojia

作者单位: The Second Institute of CAAC Chengdu, Sichuan, P.R. China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

会议地点: 成都

会议语种:英文

页码: 225-228

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）