Development of a Kalman filter based GPS satellite clock time-offset prediction algorithm
Development of a Kalman filter based GPS satellite clock time-offset prediction algorithm
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DOI：
10.1109/eftf.2012.6502355
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发表时间：
2012-04
期刊：
影响因子：
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通讯作者：
John Davis;S. Bhattarai;M. Ziebart
中科院分区：
文献类型：
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作者：
John Davis;S. Bhattarai;M. Ziebart
改进的确定性模型与描述时钟噪声的随机模型一起用于计算从IGS快速时间尺度对单个GPS卫星的时间偏差的预测。与目前使用IGS超快速预报可能获得的预测不确定度相比，这些预测的确定具有明显更低的不确定性。在一天的预报长度下，所有GPS卫星时钟的IGS预报误差通常在几ns量级。相比之下，新技术将新一代Block IIR和IIF卫星一天的预测误差限制在1 ns量级。讨论了导致IGS预报不确定的因素。基于卡尔曼滤波的预测算法的应用表明，产生了接近最优的预测。
An enhanced deterministic model along with a stochastic model for describing clock noise is used to compute predictions of the time-offset of individual GPS satellites from the IGS rapid timescale. These are determined with significantly lower prediction uncertainties than may currently be obtained using the IGS ultra-rapid predictions. At prediction length of one day IGS prediction errors are commonly of the order of several ns for all GPS satellite clocks. In comparison the new techniques offers to limit prediction errors at the order of 1 ns for prediction lengths of one day in the newer generation Block IIR and IIF satellites. The factors contributing to the uncertainties in the IGS predictions are discussed. The application of a Kalman filter based prediction algorithm is shown to produce close to optimal predictions.