| 神经网络的单滤波器目标跟踪算法 |
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| 引用本文： | 阮怀林,王树亮.神经网络的单滤波器目标跟踪算法[J].火力与指挥控制,2011,36(10):107-110. |
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| 作者姓名： | 阮怀林 王树亮 |
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| 作者单位： | 解放军电子工程学院,合肥,230037 |
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| 摘 要： | 当前统计模型及其自适应滤波(CSMAF)算法是机动目标跟踪中的一种有效方法.但该方法对目标机动加速度极限值有依赖,并且对弱机动目标跟踪的精度不高.为解决这一问题,利用一种改进的加速度方差自适应调整公式克服了对加速度极限值的依赖,同时利用神经网络对滤波参数信息进行融合,自适应调整过程噪声.仿真结果表明,该方法有很好的机动...
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| 关 键 词： | 自适应滤波 当前统计模型 机动目标 神经网络 |
A Single Filter Tracking Algorithm Based on Neural Network |
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| RUAN Huai-lin,WANG Shu-liang.A Single Filter Tracking Algorithm Based on Neural Network[J].Fire Control & Command Control,2011,36(10):107-110. |
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| Authors: | RUAN Huai-lin WANG Shu-liang |
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| Institution: | RUAN Huai-lin,WANG Shu-liang(Electronic Engineering Institute of PLA,Hefei 230037,China) |
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| Abstract: | The Current Statistical Model and Adaptive Filtering(CSMAF) algorithm is one of the most effective methods for tracking the maneuvering targets.However,its performance suffers from the shortcoming of its heavy dependence on the choice of limit acceleration.Also,it has a lower precision in tracking the weak maneuvering target.For solving this problem,one improved self-adaptive formula for acceleration variance is proposed to overcome the dependence on the limit acceleration.At the same time,the neural networ... |
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| Keywords: | adaptive filtering current statistical model maneuvering targets neural network |
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