| 迭代无味卡尔曼滤波的目标跟踪算法 |
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| 引用本文： | 常国宾,许江宁,李安,常路宾.迭代无味卡尔曼滤波的目标跟踪算法[J].西安交通大学学报,2011,45(12):70-74. |
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| 作者姓名： | 常国宾 许江宁 李安 常路宾 |
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| 作者单位： | 海军工程大学电气与信息工程学院,430033,武汉 |
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| 基金项目： | 国家自然科学基金资助项目，东南大学微电子机械系统教育部重点实验室开放基金资助项目 |
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| 摘 要： | 针对目标跟踪迭代无味卡尔曼滤波(IUKF)算法中跟踪精度较差的问题,提出一种基于状态扩展技术的改进迭代无味卡尔曼滤波(IIUKF)算法.新算法首先将观测噪声扩展进状态,构造关于扩展状态的零噪声观测方程,然后在观测迭代过程中将最新的扩展状态后验估计代入更新公式,进行观测迭代更新.相比IUKF算法,IIUKF算法不仅形式上更为简洁,而且避免了IUKF算法中先验估计和观测噪声非统计正交的问题,滤波精度更高.数值仿真表明,IIUKF算法的跟踪误差比IUKF算法减小了20%以上.
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| 关 键 词： | 迭代扩展卡尔曼滤波 迭代无味卡尔曼滤波 统计正交 目标跟踪 |
A Target Tracking Method of Iterative Unscented Kalman Filter |
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| CHANG Guobin,XU Jiangning,LI An,CHANG Lubin.A Target Tracking Method of Iterative Unscented Kalman Filter[J].Journal of Xi'an Jiaotong University,2011,45(12):70-74. |
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| Authors: | CHANG Guobin XU Jiangning LI An CHANG Lubin |
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| Institution: | CHANG Guobin,XU Jiangning,LI An,CHANG Lubin(Institute of Electrical and Information Engineering,Navy University of Engineering,Wuhan 430033,China) |
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| Abstract: | An improved iterative unscented Kalman filter(IIUKF) is proposed to increase the target tracking accuracy of iterative unscented Kalman filter(IUKF) by using the state augmentation technique.The method augments measurement noises into states,and a measurement function of augmented state with zero measurement noise is constructed.Then the latest posterior estimate of the augmented state is substituted into a updating function to iteratively correct state estimation using measurements.Comparing analyses with ... |
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| Keywords: | iterated extended Kalman filter iterative unscented Kalman filter statistical orthogonal target tracking |
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