| 基于“当前”模型的IMM-UKF机动目标跟踪融合算法研究 |
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| 引用本文： | 崇阳,张科,吕梅柏.基于“当前”模型的IMM-UKF机动目标跟踪融合算法研究[J].西北工业大学学报,2011,29(6):919-926. |
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| 作者姓名： | 崇阳 张科 吕梅柏 |
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| 作者单位： | 西北工业大学航天学院,陕西西安,710072 |
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| 基金项目： | 航空科学基金(20110153003)资助 |
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| 摘 要： | 文章设计了一种基于“当前”统计模型的交互式多模型无迹卡尔曼滤波(IMM-UKF)融合算法.首先在交互式多模型算法框架内,计算“当前”统计模型的概率,自适应地调整“当前”统计模型中目标加速度,提高了“当前”统计模型的自适应性.其次,该算法结合了交互式多模型和无迹卡尔曼滤波算法,该算法具有交互式多模型具有对不同目标机动模式自适应跟踪的能力和无迹卡尔曼滤波滤波度高的优点.最后,采用分布式融合算法提高了系统抗干扰能力及对目标跟踪的有效性和跟踪精度.通过对三维机动目标进行仿真,结果表明文中所设计的IMM-UKF融合算法对于跟踪以多种机动策略实时机动的目标具有较好的跟踪性能,可以减小系统机动跟踪的误差均值和标准差.较之传统的交互式多模型算法,跟踪性能更加优越.
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| 关 键 词： | 无迹卡尔曼滤波 机动目标跟踪 交互式多模型 "当前"统计模型 |
Exploring a Better IMM-UKF Fusion Algorithm Based on Current Statistical Model in Target Tracking |
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| Chong Yang
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Zhang Ke
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Lu Meibai.Exploring a Better IMM-UKF Fusion Algorithm Based on Current Statistical Model in Target Tracking[J].Journal of Northwestern Polytechnical University,2011,29(6):919-926. |
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| Authors: | Chong Yang Zhang Ke Lu Meibai |
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| Affiliation: | Chong Yang,Zhang Ke,Lu Meibai(College of Astronautics,Northwestern Polytechnical University,Xi′an 710072,China) |
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| Abstract: | Aim.The introduction of the full paper reviews a number of relevant papers in the open literature and points out that there is an urgent need to explore;but,to our knowledge,there is no paper in the open literature that explores the effects of interacting multiple models and unscented Kalman filtering(IMM-UKF) fusion method.Sections 1,2 and 3 explain the result of our exploration,which is the design of our IMM-UKF fusion algorithm based on the current statistical model and which we believe is better than pr... |
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| Keywords: | algorithms analysis calculations convergence of numerical methods design effects efficiency errors iterative methods Kalman filtering models probability simulation stability targets tracking(position) trajectories interacting multiple models and unscented Kalman filtering(IMM-UKF) maneuvering target tracking |
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