| 基于模糊逻辑的改进自适应IMM跟踪算法 |
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| 引用本文： | 赵楚楚,王子微,丁冠华,孙进平.基于模糊逻辑的改进自适应IMM跟踪算法[J].信号处理,2021,37(5):724-734. |
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| 作者姓名： | 赵楚楚 王子微 丁冠华 孙进平 |
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| 作者单位： | 北京航空航天大学电子信息工程学院 |
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| 基金项目： | 国家自然科学基金（62073334） |
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| 摘 要： | 交互式多模型算法（IMM）和基于模糊控制的交互多模型算法（FIMM）是实际中常用的目标跟踪算法，然而其模型集合固定，当需要大量模型覆盖目标机动时，会导致计算量激增，且过多模型可能带来不必要的模型竞争，降低跟踪性能。针对这一缺陷，提出了一种基于模糊控制的改进自适应IMM算法（FAIMM），采用一种模型概率的非线性映射处理方法实时筛选模型子集，剔除无用模型，增加有用模型的权重，并通过模糊推理机制自动调整过程噪声水平，使得算法对不同的目标机动模式具有更强的自适应能力。仿真结果表明，提出的算法跟踪性能优于IMM算法以及FIMM算法，能够更好地匹配目标的机动模式。
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| 关 键 词： | 机动目标跟踪 自适应交互多模型算法 模糊控制系统 |
| 收稿时间： | 2020-10-12 |
Fuzzy-Logic Adaptive IMM Algorithm for Target Tracking |
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| Affiliation: | School of Electronic and Information Engineering, Beihang University |
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| Abstract: | The interacting multiple model algorithm(IMM) and fuzzy systems-based interacting multiple model algorithm(FIMM) are practical maneuvering target tracking algorithms with fixed model sets. When a large number of models are needed to cover all possible maneuver cases, it will lead to a surge in computation, and may even lead to unnecessary model competition,thus reducing the tracking performance. In view of this defect,an improved fuzzy-logic adaptive IMM algorithm(FAIMM) is proposed, which adopts a nonlinear mapping method of model probabilities to screen the subset of models in real time, eliminate useless models, and increase the weight of useful models.Besides,it can adjust the process noise level automatically through a fuzzy system, so that the algorithm has stronger adaptive ability to different target maneuvering modes. Simulation results show that the tracking performance of the proposed algorithm is better than that of IMM and FIMM, and can match the target maneuvering mode better. |
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