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中文摘要：
针对常规自适应网格多模型滤波方法存在的模式跟踪能力不强,在系统模式发生大幅度跳变时,滤波模型集难以快速适应模式变化,容易出现模式跟踪失败的问题,模拟生物免疫系统识别抗原的原理,提出一种新的多模型滤波方法.该方法在原有算法基础上,增加了一个监测模型集来随机探测当前模式的分布信息,并对滤波模型集的适应过程进行引导和纠偏.仿真结果表明该方法能够获得更好的模式跟踪能力.
英文摘要：
Because the mode-tracking ability of a conventional adaptive grid interacting multiple model （AGIMM） is not strong, when the system mode has a long span jump, the model-set cannot adapt to the mode change quickly enough, resulting in mode tracking failure. In this paper, an improved AGIMM that mimics the antigen identifying mechanism of the immune system is proposed. In this algorithm, a monitor set is introduced to detect the distribution of the system mode randomly, which guides and corrects the adaptation process of the filtering model-set. Simulation results show that this algorithm has better mode tracking ability.
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