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融合式网络 花落波兰丰田公司
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《中国制造业信息化(学术版)》 2005年第1期62-62,共1页
波兰丰田汽车制造有限责任公司(TMMP)位于WaⅡbrzych城,是全球三大汽车制造厂之一的TMEM(欧洲丰田汽车工程与制造公司)的子公司.
关键词 波兰丰田汽车制造有限责任公司 融合式网络 智能以太网交换机 IP电话系统
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OPTIMAL DISTRIBUTED FUSION ALGORITHM WITH ONE-STEP OUT-OF-SEQUENCE ESTIMATES 被引量:3
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作者 Ge Quanbo Wen Chenglin 《Journal of Electronics(China)》 2008年第4期529-538,共10页
The transmission modes of multi-hop and broadcasting for Wireless Sensor Networks(WSN)often make random and unknown transmission delays appear,so multisensor data fusion based ondelayed systems attracts intense attent... The transmission modes of multi-hop and broadcasting for Wireless Sensor Networks(WSN)often make random and unknown transmission delays appear,so multisensor data fusion based ondelayed systems attracts intense attention from lots of researchers.The existing achievements for thedelayed fusion all focus on Out-Of-Sequence Measurements(OOSM)problem which has many dis-advantages such as high communication cost,low computational efficiency,huge computational com-plexity and storage requirement,bad real-time performance and so on.In order to overcome theseproblems occurred in the OOSM fusion,the Out-Of-Sequence Estimates(OOSE)are considered tosolve the delayed fusion for the first time.Different from OOSM which belongs to the centralized fusion,the OOSE scheme transmits local estimates from local sensors to the central processor and is thus thedistributed fusion;thereby,the OOSE fusion can not only avoid the problems suffered in the OOSMfusion but also make the design of fusion algorithm highly simple and easy.Accordingly,a novel optimallinear recursive prediction weighted fusion method is proposed for one-step OOSE problem in this letter.As a tradeoff,its fusion accuracy is slightly lower than that of the OOSM method because the currentOOSM fusion is a smooth estimate and OOSE gets a prediction estimate.But,the smooth result of theOOSE problem also has good fusion accuracy.Performance analysis and computer simulation show thatthe total performance of the proposed one-step OOSE fusion algorithm is better than the current one-step OOSM fusion in the practical tracking systems. 展开更多
关键词 Sensor networks Distributed fusion One-step delay Kalman filtering Out-Of-Sequence Measurements (OOSM) Out-Of-Sequence Estimates (OOSE)
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