Heterogeneous sensors data fusion method based on peak picking in probability density space  

作　　者：赵志超 Rao Bin Xiao Shunping Wang Xuesong 

机构地区：[1]College of Electronic Science and Engineering,National University of Defense Technology,Changsha 410073,P.R.China

出　　处：《High Technology Letters》2012年第2期139-144,共6页高技术通讯（英文版）

基　　金：Supported by the National Natural Science Foundation of China （No. 60736006 and 60875019）

摘　　要：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.

关 键 词：data fusion probabilistic grids joint probability density matrix LOCALIZATION sensor network 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP751[自动化与计算机技术—控制科学与工程]