多传感器数据融合中的鲁棒检测技术

研究了多传感器数据融合中的鲁棒检测技术.检测问题中设计最优决策规则通常需要知道观测量的统计特性,在实际系统中对观测量的统计特性一般只知道一部分或完全不了解,此时可采用寻找最不利分布设计系统的决策规则.从数据融合的观点来看,鲁棒分布检测在信息的传输、系统的容错等方面优于鲁棒集中检测.最后研究了当N个传感器工作频率不同时的数据压缩方法. 

Robust Detection in Multisensor Data Fusion

Robust detection problem is presented in this paper. The design of optimal decision rules in detection problems requires the knowledge of the conditional probability distributions of the observations given by each hypothesis. In many applications, however, the probability distributions are not specified completely. In these cases, the problem could be solved to find least favorable distributions. In the view of data fusion, the decentralized detection is better in information transmission and fault tolerance properties of the system. Finally,the data compression for multisensor system is discussed when N sensors work at different sampling rate.