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IMPROVED CURRENT STATISTIC MODEL AND ADAPTIVE FILTERING

机译:改进的电流统计模型和自适应滤波

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摘要

Current statistical model needs to pre-define the value of maximum accelerations of maneuvering targets. So it may be difficult to meet all maneuvering conditions. In this paper a novel adaptive algorithm for tracking maneuvering targets is proposed. The algorithm is implemented with fuzzy-controlled current statistic model adaptive filtering and unscented transformation. The Monte Carlo simulation results show that this method outperforms the conventional tracking algorithm based on current statistical model.
机译:当前的统计模型需要预先定义机动目标的最大加速度值。因此可能很难满足所有机动条件。本文提出了一种新型的跟踪机动目标的自适应算法。该算法通过模糊控制的电流统计模型自适应滤波和无味变换实现。蒙特卡罗仿真结果表明,该方法优于基于当前统计模型的传统跟踪算法。

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