Neural Network Data Fusion for Maneuvering Targets Tracking
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摘要: 利用神经网络方法解决雷达/红外双模制导中的数据融合问题.红外数据经过异步数据融合处理与经过卡尔曼滤波处理后的雷达数据同步,共同作为神经网络的输入,神经网络作为同步融合中心,输出为目标的最优融合估计.研究结果表明这种方法可以在融合中心不知道协方差信息的情况下进行数据融合.Abstract: A neural network data fusion approach for radar/infrared dual mode guidance was presented.By taking a neural network consisting of one neuron for each component of the measurement vector as the fusion center, the infrared measurements were fused first to keep synchronous with the radar measurements processed by Kalman filter. The processed data were then transmitted to the central neural network where a fused estimation of target was formed. The goal of this pager was to propose a method for computing the fused estimation in the absence of covariance information. Simulation result was demonstrated the effectiveness of this method.
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Key words:
- Kalman filtering /
- neural networks /
- radar guidance /
- infrared guidance /
- data fusion
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