The multi-sensor multi-target localization and data fusion problem is discussed, and a new data fusion method called joint probability density matrix （JPDM） has been proposed, which can associate with and fuse measu...The multi-sensor multi-target localization and data fusion problem is discussed, and a new data fusion method called joint probability density matrix （JPDM） has been proposed, which can associate with and fuse measurements from spatially distributed heterogeneous sensors to produce good estimates of the targets. Based on probabilistic grids representation, the uncertainty regions of all the measurements are numerically combined in a general framework. The NP-hard multi-sensor data fusion problem has been converted to a peak picking problem in the grids map. Unlike most of the existing data fusion methods, the JPDM method does not need association processing, and will not lead to combinatorial explosion. Its convergence to the CRB with a diminishing grid size has been proved. Simulation results are presented to illustrate the effectiveness of the proposed technique.展开更多
According to the different equipment, different system and heterogeneous database have be information ＂isolated island＂ problem, and the data of equipments can be updated in real time on the business node. The paper...According to the different equipment, different system and heterogeneous database have be information ＂isolated island＂ problem, and the data of equipments can be updated in real time on the business node. The paper proposes a program of data synchronization platform based on J2EE （JMS） and XML, and detailed analysis and description of the workflow system, its frame structure and the key technology. Practice shows that this scheme has the advantages of convenient and real-time etc..展开更多
基金Supported by the National Natural Science Foundation of China （No. 60736006 and 60875019）
文摘The multi-sensor multi-target localization and data fusion problem is discussed, and a new data fusion method called joint probability density matrix （JPDM） has been proposed, which can associate with and fuse measurements from spatially distributed heterogeneous sensors to produce good estimates of the targets. Based on probabilistic grids representation, the uncertainty regions of all the measurements are numerically combined in a general framework. The NP-hard multi-sensor data fusion problem has been converted to a peak picking problem in the grids map. Unlike most of the existing data fusion methods, the JPDM method does not need association processing, and will not lead to combinatorial explosion. Its convergence to the CRB with a diminishing grid size has been proved. Simulation results are presented to illustrate the effectiveness of the proposed technique.
文摘According to the different equipment, different system and heterogeneous database have be information ＂isolated island＂ problem, and the data of equipments can be updated in real time on the business node. The paper proposes a program of data synchronization platform based on J2EE （JMS） and XML, and detailed analysis and description of the workflow system, its frame structure and the key technology. Practice shows that this scheme has the advantages of convenient and real-time etc..
