考虑局部估计误差相关性的传感器选择融合  

Sensor selection-based fusion considering cross-correlation of local estimation errors

作　　者：朱洪艳[1] 陈硕[1] 韩崇昭[1] 

机构地区：[1]西安交通大学电子与信息工程学院,西安710049

出　　处：《控制与决策》2015年第2期241-245,共5页Control and Decision

基　　金：国家自然科学基金项目(61203220);国家973计划项目(2013CB329405)

摘　　要：在多传感信息融合系统中,受系统过程噪声和相关的量测噪声等因素影响,局部估计误差之间存在一定的相关性.针对考虑局部估计误差相关性情况下的传感器选择融合问题,构造了基于融合估计精度的优化指标;引入传感器子集的势约束,将传感器选择融合问题转化为一个组合优化问题;采用交叉熵优化方法,通过交替执行抽样和更新抽样分布参数两个步骤,获得了优化问题的解.In distributed information fusion systems, local estimation errors may be highly correlated arising from the common process noise and dependent measurement noises. The problem of estimation fusion based on sensor selection in the presence of the cross-correlation of local estimation errors is addressed. By introducing the objective function according to the fusion accuracy and the cardinality constraint of the selected subset, the sensor selection problem is turned into a combinatorial optimization one. The cross entropy optimization method is employed to solve it, which implements the sampling and updating the sample distribution alternately.

关 键 词：估计融合 互相关 传感器选择 相关系数 交叉熵 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]