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The Application of Improving Space-time DS Evidence Theory in Distinguishing Vehicle

机译:改进节空DS证据理论在传播车辆中的应用

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In this paper, it takes advantage of evidence theory to fuse the data with multi-sensors and multi-measuring periods. It discusses three kinds of fusion structures: concentrated fusion, distributed fusion without feedback and distributed fusion with feedback. In the application of vehicle type distinguishing, through theoretical analysis and simulation results, the paper gets the conclusion that when the data provided by the sensors is not very accurate (even wrong), the distributed fusion without feedback can get the highest rate of correct result, the distributed fusion with feedback follows and the concentrated fusion is the worst.
机译:在本文中,它利用了证据理论,使数据与多传感器和多测量周期融合。它讨论了三种融合结构:集中融合,分布式融合,无反馈和具有反馈的分布式融合。在应用车型区分的过程中,通过理论分析和仿真结果,纸张得出结论,当传感器提供的数据不是非常准确的(甚至错)时,没有反馈的分布式融合可以获得最高率的正确结果,具有反馈的分布式融合遵循,浓缩融合是最糟糕的。

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