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Estimation covariance of measurement fusion on track-to-track problem

机译:测量融合对轨道跟踪问题的协方差

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Measurement fusion is an optimal data fusion algorithm. The covariance of measurement fusion is proved to be decided by a function of measurement matrix and measurement noise covariance. The greater the function is, the less covariance measurement fusion method can obtain. Therefore estimation accuracy increases when the function increase. The results of simulation agree with the theoretical results.
机译:测量融合是最佳数据融合算法。证明测量融合的协方差被测量矩阵和测量噪声协方差的函数决定。功能越大,可以获得较少的协方差测量融合方法。因此,当函数增加时,估计精度会增加。模拟结果与理论结果一致。

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