| 相似采样粒子滤波在混合系统估计中的应用 |
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| 引用本文： | 邹卫军,陈益,薄煜明. 相似采样粒子滤波在混合系统估计中的应用[J]. 电光与控制, 2009, 16(11) |
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| 作者姓名： | 邹卫军 陈益 薄煜明 |
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| 作者单位： | 南京理工大学自动化学院,南京,210094 |
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| 摘 要： | 结合粒子滤波和Kalman滤波的边缘粒子滤波(MPF)是一种新的混合线性/非线性系统的状态估计方法,但是粒子滤波在计算上的复杂使得MPF难以兼顾系统实时性和精度的要求.针对此问题,提出一种基于相似采样粒子滤波算法的MPF滤波框架.算法从系统观测值中采样粒子,并通过一个计算相邻时刻粒子转移概率的步骤,提高了粒子使用率,使得算法能以少量粒子实现对非线性状态量的估计,进而提高Kalman滤波的精度和实时性.给出了算法原理分析和实现流程.以混合坐标系下的目标跟踪为对象,利用蒙特卡罗仿真研究了ILLH_MPF算法的应用,并与常规MPF方法进行了对比.
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| 关 键 词： | 混合线性/非线性 粒子滤波 相似性采样 MPF滤波 蒙特卡罗仿真 |
Application of Likelihood-Sampling Particle Filter in the Mixed Estimation of Linear/Nonlinear System |
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| ZOU Weijun,CHEN Yi,BO Yuming. Application of Likelihood-Sampling Particle Filter in the Mixed Estimation of Linear/Nonlinear System[J]. Electronics Optics & Control, 2009, 16(11) |
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| Authors: | ZOU Weijun CHEN Yi BO Yuming |
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| Affiliation: | ZOU Weijun,CHEN Yi,BO Yuming(College of Automation,Nanjing University of Science , Technology,Nanjing 210094,China) |
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| Abstract: | The Marginalized Particle Filter(MPF),which combines Particle Filter(PF) with Kalman filter,is an effective algorithm for the estimation of mixed linear/nonlinear system,but the computational complexity of PF make it difficult to meet the requirement of real-time and precision in estimation.A likelihood-sampling PF was introduced to join in the MPF algorithm.The ILLH_MPF algorithm sampled the particles from the observation,and increased the utilization factor of particles by calculating the transition proba... |
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| Keywords: | mixed linear/nonlinear Particle Filter likelihood-sampling Marginalized Particle Filter Monte-Carlo simulation |
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