| 引用本文: | 韩明华,袁乃昌.多层神经网络在跟踪式卡尔曼滤波器中的应用.[J].国防科技大学学报,1997,19(5):18-24.[点击复制] |
| Han Minghua,Yuan Naichang.A Improved Tracking Karlman Filter Using a Multilayed Neural network[J].Journal of National University of Defense Technology,1997,19(5):18-24[点击复制] |
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| 多层神经网络在跟踪式卡尔曼滤波器中的应用 |
| 韩明华, 袁乃昌 |
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(国防科技大学 电子技术系 湖南 长沙 410073)
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| 摘要: |
| 本文将多层神经网络引入跟踪式卡尔曼滤波器，提高了估计的精确度。以前的跟踪式卡尔曼滤波器的估计精度与目标的运动状态有关，当目标的运动不能够用线性状态空间模型描述时，其估计精度将要下降。而多层网络的引入，改善了这一不足。多层神经网络经过训练以后，能够对卡尔曼滤波器的结果进行修正。仿真结果表明，多层神经网络的应用，使估计精度显著提高。 |
| 关键词: 目标跟踪，卡尔曼滤波，多层神经网络 |
| DOI： |
| 投稿日期：1997-03-22 |
| 基金项目:国家重点实验室基金资助项目 |
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| A Improved Tracking Karlman Filter Using a Multilayed Neural network |
| Han Minghua, Yuan Naichang |
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(Department of Electronic Technique，NUDT，Changsha，410073)
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| Abstract: |
| This paper present a method toimprove the estimation accuracy of a tracking Karlman filter (TKF) by using a multilayed neural network (MNN). Estimation accuracy of the TKF is degraded due to the uncertainties which cannot be expressed by the linear state-space model given priori.. The MNN capable of leaning an arbitrary so that realized a mapping from measurement to the corrections of estimation of TKF. Simullation results show that the estimation accuracy is much improved by using MNN. |
| Keywords: target tracking,Kalman filter,multilayed neural networ! |
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