| 基于神经网络的混合双滤波器自适应目标跟踪算法 |
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| 引用本文： | 樊国创,戴亚平,许向阳.基于神经网络的混合双滤波器自适应目标跟踪算法[J].火力与指挥控制,2009,34(2). |
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| 作者姓名： | 樊国创 戴亚平 许向阳 |
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| 作者单位： | 北京理工大学信息科学技术学院,北京,100081 |
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| 摘 要： | 在分析近期基于神经网络数据融合的目标跟踪算法的基础上,结合一种新的自适应滤波模型(NAF)和速度估计自适应跟踪算法(AVE),提出了基于神经网络混合双滤波器的机动目标自适应跟踪算法(NHDF).该算法通过在线自动调节网络输出进行过程噪声方差融合,降低了现有算法因系统方差的调整不当而带来的精度损失.理论分析及仿真结果证明,与"当前"统计模型、速度自适应模型和新的自适应模型算法相比,该算法具有跟踪精度高,自适应能力强的优点.
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| 关 键 词： | 神经网络 卡尔曼滤波 自适应 目标跟踪 |
Neural Network-based Hybrid Double Filters for Adaptive Target Tracking |
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| FAN Guo-chuang,DAI Ya-ping,XU Xiang-yang.Neural Network-based Hybrid Double Filters for Adaptive Target Tracking[J].Fire Control & Command Control,2009,34(2). |
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| Authors: | FAN Guo-chuang DAI Ya-ping XU Xiang-yang |
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| Institution: | School of Information Science and Technology;Beijing Institute of Technology;Beijing 100081;China |
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| Abstract: | An recent algorithm of target tracking based on neural network data fusion is analyzed,and the algorithm of neural network-based hybrid double filters for adaptive target tracking(NHDF) is proposed,combined with a new adaptive filtering algorithm and adaptive velocity estimation algorithms.In the NHDF algorithm,the fusion of system noise covariance is conducted by regulating the output of neural network online.And the precision of filtering is improved consequently.The results of theoretical analyse and sim... |
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| Keywords: | neural network kalman filter adaptiveness target tracking |
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