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- 2016
使用Kalman滤波器调整预测值的时间尺度算法
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Abstract:
时间尺度算法用于综合钟组内所有的原子钟，建立一个频率稳定度更高的时间尺度，其核心环节可以概括为通过N-1组观测量（钟差）计算得到N台钟的权重和预测值。传统算法主要关注如何调整权重来提高时间尺度的稳定度，本文算法通过调整预测值来提高时间尺度的稳定度。本文算法使用Kalman滤波器对观测钟差进行状态估计，在Kalman滤波器每一次递推的过程中，调整一次预测值，通过每次实时调整预测值来建立时间尺度。理论推导和仿真实验都表明，本文建立的时间尺度滤除了频率白噪声，主要只含有频率随机游走噪声，所以具有很高的中短期稳定度。该时间尺度是一个连续、实时、可预测的时间尺度
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