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Strong Tracking Filters: Derivation and Improved Heuristic

机译:强大的跟踪过滤器:推导和改进的启发式

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This paper reviews variants of “strong tracking filters,” and offers a new method of adjusting the innovation matrix that allows the filter to be used with measurements of varying dimensionalities over time. Strong tracking filters are more robust to model mismatches than Kalman filters. Variants of the extended strong Kalman filter are compared to the extended Kalman filter for two types of model mismatch.
机译:本文评论了“强跟踪过滤器”的变体,并提供了一种调整创新矩阵的新方法,允许过滤器随时间测量不同的尺寸。强大的跟踪过滤器对模型不匹配比卡尔曼过滤器更强大。扩展强Kalman滤波器的变体与扩展卡尔曼滤波器进行比较,用于两种类型的模型不匹配。

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