摘要
应用证据理论 (D -S方法 ) ,解在多传感器条件下的数据融合问题。具体方法是根据多个传感器对目标类型判断的基本概率分配函数 ,不断添加新的传感器数据 ,更新信任函数和似然函数 ,最终判断目标类型。并且将D -S方法与其它数据融合方法 (如Bayes方法 )进行了比较 ,说明了D -S方法的优越性和先进性。
How to use Dempster-Shafer (D-S) method to solve multi-sensor data fusion problems is analyzed in this paper. Based on basic probability assignment of target type decided by multiple sensors, new sensor data are added continually, and believe function and plausibility function are update, finally the destination of decision of target type is arrived. By comparing the D-S method with other data fusion methods (such as Bayes method), we can see that the D-S method is feasible and advanced.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2001年第3期98-101,共4页
Systems Engineering and Electronics
关键词
传感器
证据理论
数据融合
Data processing Bayes theorem Sensor Target recognition
