| 一种高精度自适应粒子滤波算法 |
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| 引用本文： | 曹洁,李伟.一种高精度自适应粒子滤波算法[J].兰州理工大学学报,2011,37(3):83-88. |
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| 作者姓名： | 曹洁 李伟 |
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| 作者单位： | 1. 兰州理工大学计算机与通信学院,甘肃兰州,730050
2. 兰州理工大学计算机与通信学院,甘肃兰州,730050;中国人民解放军91666部队,浙江舟山,316000 |
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| 基金项目： | 甘肃省自然科学基金(1010RJZA046); 甘肃省教育厅研究生导师基金(0914ZTB003) |
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| 摘 要： | 针对非线性非高斯系统的状态估计问题,提出一种新的高精度自适应粒子滤波算法.该算法采用有限差分扩展卡尔曼滤波器产生优选的建议分布函数,融入最新量测信息,有效克服了粒子退化问题;考虑到预测误差对粒子采样效率的影响,引入系统估计和预测提供的新息差值,通过新息差值在线自适应调整采样粒子数,较好地保证了粒子采样的高效性.理论分析...
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| 关 键 词： | 有限差分 扩展卡尔曼滤波 粒子滤波 重要性函数 |
Investigation of a high-precision algorithm for adaptive particle filtering |
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| CAO Jie,LI Wei.Investigation of a high-precision algorithm for adaptive particle filtering[J].Journal of Lanzhou University of Technology,2011,37(3):83-88. |
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| Authors: | CAO Jie LI Wei |
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| Institution: | CAO Jie1,LI Wei1,2(1.College of Computer and Communication,Lanzhou Univ.of Tech.,Lanzhou 730050,China,2.PLA Troops of 91666,Zhoushan316000,China) |
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| Abstract: | A new improved particle filtering algorithm was proposed for state estimation of non-Gaussian nonlinear systems.In this algorithm finite-difference extended Kalman filter was adopted to produce an optimized proposal distribution function and the updated measurement messages could be merged in,so that the particle degradation would be avoided effectively.Taking account of the influence of predicted errors on particle sampling efficiency,a deviation value of updated message between system estimation and predi... |
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| Keywords: | finite-difference extended Kalman filtering particle filtering importance function |
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