基于可信度的多源定位数据融合方法  

Credibility Based Data Fusion Algorithm for Multi-Positioning System

作　　者：尹露[1] 邓中亮[1] 席岳[1] 

机构地区：[1]北京邮电大学电子工程学院,北京100876

出　　处：《北京邮电大学学报》2014年第4期34-38,共5页Journal of Beijing University of Posts and Telecommunications

基　　金：国家高技术研究发展计划项目(2012AA120801)

摘　　要：建立了一种适合城市环境的多源定位系统自适应联邦卡尔曼滤波模型.首先通过估计各子系统定位结果的测量噪声,得到子系统可信度并分配信任因子;然后对各子系统的定位结果进行联邦卡尔曼滤波,并根据信任因子对各子滤波器进行信息分配,以获得最优滤波估计.为了更加客观方便地评价滤波效果,提出一种新的滤波性能评价方法.仿真结果表明了算法的有效性及滤波评价方法的优越性.An adaptive federated Kalman filter model for multi-positioning system used in urban was pro- posed. Firstly, the credibility of subsystems was evaluated by estimating the position errors and the credi- ble factors was obtained. Secondly, the information sharing factors of federated Kalman filter were as- signed by credible factors to adaptive filtering. To assess the filtering effect, a new assessment method was proposed. Simulation demonstrates the effectiveness of the filtering algorithm and assessment method.

关 键 词：数据融合 联邦卡尔曼滤波 滤波器-激励-参数函数 最优滤波比 信任因子 

分 类 号：TN967.2[电子电信—信号与信息处理]