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Improved strong tracking adaptive interactive multi model tracking algorithm for highly maneuverable targets
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DOI：10.1016/j.phycom.2025.102915.png)
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摘要
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为解决交互式多模型目标跟踪算法在跟踪高机动目标时，模型切换缓慢和滤波器预测误差大导致跟踪精度低的问题，提出了一种改进的强跟踪自适应交互式多模型跟踪算法。采用滑动窗口计算历史残差的校正因子，利用后验信息实现状态转移概率矩阵的实时调整。此外，将改进的强跟踪衰减因子整合到Unscented Kalman Filter中，动态调整协方差矩阵以提高估计精度。仿真结果表明，与传统的交互式多模型算法相比，所提方法将模型匹配概率提高了11.14%，同时将位置均方根误差（RMSE）降低68.89%，速度均方根误差（RMSE）降低39.80%。所提算法在跟踪高机动目标时加速了运动模型切换并减少了滤波器预测误差，从而提升了整体跟踪性能。
Keyword:
Target tracking
Sliding window
Historical residual
Correction factor
Strong tracking filter
期刊
IF:
2.2
论文数:
363
被引数:
2.6K
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