| 双层无迹卡尔曼滤波 |
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| 引用本文： | 杨峰,郑丽涛,王家琦,潘泉.双层无迹卡尔曼滤波[J].自动化学报,2019,45(7):1386-1391. |
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| 作者姓名： | 杨峰 郑丽涛 王家琦 潘泉 |
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| 作者单位： | 1.西北工业大学自动化学院信息融合技术教育部重点实验室 西安 710129 |
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| 基金项目： | 西北工业大学创新创意种子基金zz2018149光电控制技术重点实验室和航空科学基金联合20165153034中国电子科技集团公司数据链技术重点实验室开放基金CLDL-20182203国家自然科学基金61374159陕西省自然基金2018MJ6048 |
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| 摘 要： | 针对无迹卡尔曼滤波（Unscented Kalman fllter，UKF）在强非线性系统中估计效果差的问题，提出了双层无迹卡尔曼滤波（Double layer unscented Kalman filter，DLUKF）算法，该算法用带权值的采样点表征先验分布，而后用内层UKF算法对每个采样点进行更新，最后引入外层UKF算法的更新机制得到估计值和估计协方差.仿真结果表明，相比于传统算法，所提的DLUKF算法可以在较低计算负载下获得较高滤波估计精度.
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| 关 键 词： | 状态估计 采样策略 无迹卡尔曼滤波 改进的无迹卡尔曼滤波 无迹粒子滤波 |
| 收稿时间： | 2018-05-26 |
Double Layer Unscented Kalman Filter |
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| Affiliation: | 1.Key Laboratory of Information Fusion Technology, Ministry of Education of China, School of Automation, Northwestern Polytechnical University, Xi'an 7101292.Science and Technology on Electro-optic Control Laboratory, Luoyang 4710093.CETC Key Laboratory of Data Link Technology, Xi'an 710000 |
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| Abstract: | The unscented Kalman filter (UKF) has the problem of the inaccurate estimation in strong nonlinear systems. To solve this problem, the double layer unscented Kalman filter (DLUKF) algorithm is proposed. In the proposed algorithm, the weighted sampling points are used to represent the prior distribution, and then the inner layer UKF algorithm is used to update each sampling point. Finally, the state estimations are obtained by the update mechanism of the outer layer UKF algorithm. Simulation results show that the proposed algorithm not only has a low computational complexity, but also has a very good estimation accuracy, compared with the existing filtering algorithms. |
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