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| 复合K噪声下机动目标跟踪自适应UPF算法 | |
| 引用本文： | 刘望生,李亚安,王明环.复合K噪声下机动目标跟踪自适应UPF算法[J].电子学报,2012,40(6):1240-1245. |
| 作者姓名： | 刘望生 李亚安 王明环 |
| 作者单位： | 1. 浙江理工大学机械与自动控制学院,浙江杭州310012;西北工业大学航海学院,陕西西安710072 2. 浙江理工大学机械与自动控制学院,浙江杭州,310012 3. 浙江工业大学特种装备制造与先进加工技术教育部重点实验室,浙江杭州,310012 |
| 基金项目： | 国家自然科学基金，浙江省特种装备制作与先进加工技术重点实验室开放基金 |
| 摘 要： | 针对复合K噪声下机动目标跟踪系统具有强非线性非高斯的特点,提出了一种自适应无迹粒子滤波(Adaptive Unscented Particle Filter,AUPF)算法.该算法建立在常加速模型及其改进滤波算法基础上,并将无迹卡尔曼滤波(Unscented Kalman Filter,UKF)与强跟踪滤波(Strong Tracking Filter,STF)算法相结合作为提议分布,提高了系统跟踪一般机动和阶跃机动的能力.在给出复合K噪声模型的基础上,利用AUPF算法对几种典型机动目标进行了计算机仿真,并同无迹粒子滤波(Unscented Particle Filter,UPF)算法进行了比较.仿真结果表明,复合K噪声下AUPF算法能更有效地对各种机动目标进行跟踪,具有较高的跟踪精度. |
| 关 键 词： | 机动目标 常加速模型 AUPF算法 强跟踪滤波 复合K噪声 |
| 收稿时间： | 2011-02-16 |
An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment |
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| LIU Wang-sheng , LI Ya-an , WANG Ming-huan.An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment[J].Acta Electronica Sinica,2012,40(6):1240-1245. | |
| Authors: | LIU Wang-sheng LI Ya-an WANG Ming-huan |
| Affiliation: | 1.School of Mechanical Engineering and Antomation,Zhejiang Sci-Tech University,Hangzhou,Zhejiang 310018,China;2.College of Marine,Northwestern Polytechnical University,Xi′an,Shaanxi 710072,China;3.Key Laboratory of Special Purpose Equipment and Advanced Processing Technology,Ministry of Education,Zhejiang University of Technology,Hangzhou,Zhejiang 310012,China) |
| Abstract: | Aimed at the strong nonlinear and non-Gaussian characteristics of maneuvering target tracking system under compound K noise,an adaptive unscented particle filter(AUPF) algorithm is proposed.Based on constant acceleration(CA) model and its modified filtering algorithm,the algorithm adopts a new proposal distribution which combines unscented Kalman filter(UKF) and strong tracking filter(STF) and enhances the system performance for tracking general mobile and step mobile.The AUPF algorithm is applied to track several kinds of typical maneuvering targets based on the model of compound K noise.And the comparison with the unscented particle filter(UPF) algorithm is given.The simulation results show that AUPF algorithm has good track performance for tracking various maneuvering targets and has high tracking precision. |
| Keywords: | maneuvering target constant acceleration model AUPF algorithm strong tracking filter compound K noise |
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