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BP和D-S结合的多传感器协同目标识别推理机制
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TP391

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国防科技重点实验室基金资助项目(9140XXXXXX110)


A Study of Reasoning Mechanism on Multiple Sensors Cooperation with Target Identification Based on BP Neural Network and D-S Evidence Theory
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    摘要:

    针对多传感器协同目标识别的基本概率赋值在实际应用中存在容易导致决策可信度低等难以解决的问题,提出一种基于BP神经网络和D-S证据理论的多传感器协同目标识别的推理机制。简述了BP神经网络理论和D-S证据理论,构建了目标识别推理框架,推理了算法可行性,进行了实例仿真,通过信息融合,不确定性的基本概率赋值下降到0.000 8,表明该推理机制的有效性。

    Abstract:

    Aimed at the problem that the basic probability assignment of multiple sensors cooperation with target identification in practical application is liable to cause low decision-making reliability, a reasoning mechanism of multiple sensors cooperation with target identification based on BP neural network and D-S evidence theory is presented. Firstly, BP neural network theory and D-S evidence theory are summarized simply. And then, target identification reasoning frame is built, and the algorithm's feasibility is reasoned. At last, an actual example is simulated, and by information fusing the basic probability assignment of uncertainty drops to 0.0008, the analysis and the simulation show that the reasoning mechanism is effective.

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苏伟,李为民,赵永. BP和D-S结合的多传感器协同目标识别推理机制[J].空军工程大学学报,2014,(2):29-32

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  • 在线发布日期: 2015-11-17
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