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

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.