| 基于机动检测的参数自适应跟踪算法 |
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| 引用本文： | 张娜,王锐,蔡炯.基于机动检测的参数自适应跟踪算法[J].信号处理,2022,38(2):367-374. |
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| 作者姓名： | 张娜 王锐 蔡炯 |
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| 作者单位： | 北京理工大学信息与电子学院，北京 100081 |
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| 基金项目： | 国家自然科学基金31727901 |
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| 摘 要： | 在机动目标跟踪中,传统当前统计模型卡尔曼滤波算法对弱/无机动目标跟踪精度不高,对突发机动跟踪精度显著下降,且跟踪性能受限于先验参数.针对上述问题,本文提出一种基于机动检测的参数自适应机动目标跟踪算法,算法利用新息的概率分布特性构建双阈值检测门限,依据检测结果进行参数自适应调整.首先,利用加速度预测误差方差信息,自适应调...
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| 关 键 词： | 当前统计模型 自适应参数 机动检测 目标跟踪 |
| 收稿时间： | 2021-03-02 |
Parameter Adaptive Tracking Algorithm Based on Maneuver Detection |
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| Affiliation: | Department of Information and Electronics，Beijing Institute of Technology，Beijing 100081，China |
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| Abstract: | In maneuvering target tracking， the traditional current statistical model Kalman filter algorithm has low tracking accuracy for weak / inorganic maneuvering target， significantly reduces the tracking accuracy for sudden maneuvering， and the tracking performance is limited by prior parameters. To solve the above problems， this paper proposes a parameter adaptive maneuvering target tracking algorithm based on maneuvering detection. The algorithm uses the probability distribution characteristics of residual to construct double threshold detection threshold， and adjusts the parameters adaptively according to the detection results. Firstly， by using the variance information of acceleration prediction error， the maneuvering frequency and acceleration variance are adaptively adjusted to overcome the problem of prior setting of model parameters and improve the tracking accuracy of weak maneuvering target； Secondly， the fading factor is introduced after the detection of maneuver， which makes the introduction time of fading factor more reasonable and enhances the response ability of the algorithm to maneuver. The simulation results in two typical maneuvering scenarios show that the proposed method can better adapt to acceleration step maneuver and turning maneuver than the Kalman filter algorithm based on the current statistical model with fixed parameters. |
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