递归时空信息融合技术及其在毫米波与红外目标识别中的应用
RECURSIVE TEMPORAL-SPATIAL INFORMATION FUSION TECHNIQUE AND ITS APPLICATIONS TO MMW AND INFRARED TARGET IDENTIFICATION
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摘要: 本文使用Dempster-Shafer技术讨论了递归时空信息融合的集中(或分配)算法。与Bayes算法相比,Dempster-Shafer技术具有较强的处理信息的不确定性的能力。集中算法是将所有信息汇集于中心处理器中进行处理;而分配算法则是依靠各分散的分处理器分担运算量,这样可增加计算能力。改进的算法可有效地应用于采用两种探测器的目标识别:毫米波辐射计、红外搜索和跟踪探测器。Abstract: Centralized/distributed recursive algorithms for temporal-spatial information integration are discussed by using the Dempster-shafer technique.Compared with the Bayesiar approach ,the Dempster-shafer technique has a strong capability of handling information uncertainties.All information is pooled into the central processor in the centralized integration algorithm.In contrast,the distributed algorithm shares the computation burden among the local processors,which increase the computational efficiency.The developed algorithms are applied to a target identification problem with two sensors:millimeter wave radiometer,infrared searching and tracking
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