| 正则化粒子滤波在水下目标跟踪中的应用 |
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| 引用本文： | 刘敏,陈恩庆,杨守义. 正则化粒子滤波在水下目标跟踪中的应用[J]. 电视技术, 2012, 36(9): 108-111 |
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| 作者姓名： | 刘敏 陈恩庆 杨守义 |
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| 作者单位： | 郑州大学信息工程学院,河南郑州,450001 |
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| 基金项目： | 国家自然科学基金，教育部博士点基金，河南省青年骨干教师项目 |
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| 摘 要： | 针对传统卡尔曼滤波(KF)及扩展卡尔曼滤波(EKF)在非线性目标跟踪模型中,跟踪精度较差的问题,本文给出了一种基于正则化粒子滤波(RPF)的水下目标跟踪算法。文中在一种模拟水下目标跟踪环境的非线性动态模型中对所提出的算法进行了仿真试验,并将其跟踪性能与扩展卡尔曼滤波和标准粒子滤波算法(PF)进行了比较。仿真结果表明,PF算法比EKF算法滤波精度更高,RPF的跟踪性能优于PF和RPF,而且随着粒子数的增加,PF和RPF的跟踪性能也不断提高。
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| 关 键 词： | 水下目标跟踪 非线性 扩展卡尔曼滤波 粒子滤波 正则化粒子滤波 |
| 收稿时间： | 2011-11-28 |
| 修稿时间： | 2011-11-28 |
Application of Regularization Particle Filtering in Underwater Target Tracking |
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| Liumin,ChenEnqing and Yang Shouyi. Application of Regularization Particle Filtering in Underwater Target Tracking[J]. Ideo Engineering, 2012, 36(9): 108-111 |
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| Authors: | Liumin ChenEnqing Yang Shouyi |
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| Affiliation: | Information Engineering School, Zhengzhou University,Information Engineering School of Zhengzhou University,Information Engineering School, Zhengzhou University |
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| Abstract: | In this paper, An underwater target tracking algorithm based on the regularization particle filtering is put forward to solve the problem that the tracking precision of the traditional kalman filter (KF) and the extended kalman filtering (EKF)is poor in nonlinear target tracking model. And an experiment is done to compare the algorithm with EKF and the standard particle filtering (PF) on their tracking performance in a nonlinear dynamic model which simulates the underwater target tracking environment. The simulation results show that the filtering performance of PF is more accurate than EKF algorithm; but they are both poorer than RPF on tracking performance, and with increase of the number of particles, the tracking performance of PF and RPF become better. |
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| Keywords: | the underwater target tracking nonlinear the extended kalman filtering particle filtering regularization particle filtering |
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