YANG Jin-yuan1, HUANG Xin-han1, WANG Min1. Objective algorithm on getting general belief model of sensors[J]. 2009, 28(12): 51-53+56. DOI: 10.13873/j.1000-97872009.12.015.
传感器的广义信度模型客观获取算法
摘要
在运用Dezert-Smarandache理论(D-SmT)进行多源信息融合过程中
传感器的广义基本信度赋值(GBBA)数学模型的获取较困难
且存在主观性的问题。运用粗糙集理论
提出一种新的客观算法。通过分析传感器采集的大量客观数据之间的依赖关系
利用粗糙集理论的分类思想和协调决策等概念
按照一定规则离散化的传感器数据形成决策表
引入规则强度
计算证据的基本信度赋值
建立D-SmT广义基本信度模型
存入数据库中以备需要时查询。以P2-DX机器人为实验平台
以移动机器人本体上应用最广泛的声纳传感器为例
与声纳测量的基本特性相向对比
验证了方法的正确性和有效性。
Abstract
During the multi-source information fusion with Dezert-Smarandache theory(D-SmT)
the problem of the subjectivity exists in getting the mathematical model of general basic belief assignment(GBBA).A new objective method is obtained which is integrated with rough ret(RS)theory.The dependency degree among data attributions is identified by analyzing the massive data collected by the sensors.With the concept of classification and coordinated decision system
the data is discreted to inform decision tables.The concept of rule intensity is adopted to build GBBA model which would be stored in database to be queried when necessary.P2-DX robot is used as a platform and sonar sensors on the mobile robot are introduced as example.The correctness and validity of the developed method are verified according to sonar’s electrical characteristic.