| 一种基于粒子滤波的联合跟踪与分类算法 |
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| 引用本文： | 申屠晗,郭云飞,薛安克. 一种基于粒子滤波的联合跟踪与分类算法[J]. 机电工程, 2010, 27(3): 41-44 |
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| 作者姓名： | 申屠晗 郭云飞 薛安克 |
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| 作者单位： | 杭州电子科技大学,信息与控制研究所,浙江,杭州,310018 |
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| 基金项目： | 国家自然科学基金资助项目(60805013) |
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| 摘 要： | 针对纯运动学信息联合跟踪与分类问题,提出了一种基于混合无味粒子滤波的联合跟踪与分类算法。在传统粒子滤波联合跟踪与分类算法的基础上,通过采用无味变换,利用多个无味卡尔曼滤波器给出更高质量的粒子建议分布,提高整个算法的性能。理论分析和仿真结果都表明,与传统粒子滤波联合跟踪与分类算法相比,该算法无论在跟踪精度还是在分类正确率上都有明显的提高。
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| 关 键 词： | 联合跟踪与分类 贝叶斯估计 混合无味粒子滤波 无味变换 |
A joint tracking and classification algorithm based on particle filtering |
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| SHEN Tu-han,GUO Yun-fei,XUE An-ke. A joint tracking and classification algorithm based on particle filtering[J]. Mechanical & Electrical Engineering Magazine, 2010, 27(3): 41-44 |
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| Authors: | SHEN Tu-han GUO Yun-fei XUE An-ke |
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| Affiliation: | Institute of Information and Control;Hangzhou Dianzi University;Hangzhou 310018;China |
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| Abstract: | In order to cope with the joint tracking and classification(JTC) problem,a new mixture unscented particle joint tracking and classification algorithm(MUPF-JTC) was proposed.Based on traditional mixture unscented particle joint tracking and classification algorithm(MPF-JTC),by adopting the methods of unscented transform(UT),several unscented Kalman filters(UKF) were designed in order to get higher quality particle distributions.Mathematical analysis and simulation results confirm that the MUPF-JTC algorithm ... |
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| Keywords: | joint tracking and classification（JTC ） Bayesian estimation mixture unscented particle joint tracking and classification algorithm（MUPF-JTC） unscented transform（UT） |
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