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] |
|
|
|
本文已被:浏览 7549次 下载 5656次 |
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 |
(国防科技大学 电子技术系 湖南 长沙 410073)
|
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 |
|
A Improved Tracking Karlman Filter Using a Multilayed Neural network |
Han Minghua, Yuan Naichang |
(Department of Electronic Technique,NUDT,Changsha,410073)
|
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! |
|
|