| 采样滤波算法在单站无源定位中的应用 |
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| 引用本文： | 廖平,付忠,刘刚.采样滤波算法在单站无源定位中的应用[J].国际商务研究,2006,46(4):28-31. |
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| 作者姓名： | 廖平 付忠 刘刚 |
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| 作者单位： | [1]电子对抗国防科技重点实验室,成都610036 [2]二炮驻成都地区军事代表室,成都610031 |
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| 摘 要： | 讨论了用采样的方法近似非线性分布来解决无源定位中的非线性问题，提出了一种简单的正则粒子滤波，克服了标准粒子滤波用于单站无源定位中出现的粒子贫乏现象，将粒子滤波成功应用到无源定位中，计算机仿真表明该算法的定位精度较Unscented卡尔曼滤波（UKF）有一定的提高。
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| 关 键 词： | 无源定位 贝叶斯估计 unscented卡尔曼滤波 正则粒子滤波 |
| 收稿时间： | 2006/4/15 0:00:00 |
| 修稿时间： | 2006/7/20 0:00:00 |
Application of Sample Filtering Algorithm in Single Observer Passive Location |
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| LIAO Ping,FU Zhong,LIU Gang.Application of Sample Filtering Algorithm in Single Observer Passive Location[J].International Business Research,2006,46(4):28-31. |
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| Authors: | LIAO Ping FU Zhong LIU Gang |
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| Institution: | 1. National Key Lahoratory of Electronic Warfare, Chengdu 610036,China; 2. The Second Artillery Military Representative Office Resident in Chengdu Region, Chengdu 610031, China |
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| Abstract: | A sample filtering method to solve nonlinear problem in single observer passive location is discussed.A simple regularized particle filter is presented,which can overcome particle impoverishment phenomenon,and can be successfully introduced into single observe passive location.Simulations show that this algorithm can improve the location precision compared with UKF(unscented Kalman filter). |
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| Keywords: | passive location bayesian estimation unscented Kalman filter(UKF) regularized particle filter |
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