An integrity monitoring framework is proposed to ensure the quality of the real-time Precise Point Positioning(PPP)correction data at the service end.The key contributions are designing quantitative metrics to charact...An integrity monitoring framework is proposed to ensure the quality of the real-time Precise Point Positioning(PPP)correction data at the service end.The key contributions are designing quantitative metrics to characterize the integrity status of the precise Orbit,Clock(OC)and Code Bias(OCB)corrections,and deriving the corresponding algorithms to detect and exclude anomalies,and to evaluate the real-time accuracy levels of the OCB.Compared to many prior works whose interests focused on analyzing and improving the averaged long-term accuracy,this work is established from integrity perspective.In particular,a two-layer fault detection and identification approach is developed to reduce the miss detection and false alert probabilities.The test statistics are constructed based on the raw observations from a network of worldwide sparsely distributed monitor stations.In addition,a realistic data-driven model is established to compute the Quality Indicators(QI)for healthy OCB products.The proposed scheme is validated respectively for multi-constellation OC and code bias,using historical correction data.The results suggest that the detection algorithms can effectively identify and alert the faults,so that the remaining correction errors approximate well to Gaussian distributions.Moreover,the computed QI are shown to be consistent with the truth error variations in real time.Most importantly,the position domain verification shows noticeable positioning accuracy and robustness improvements under both nominal and faulty conditions of the OCB correction data.展开更多
基金supported by supported by the National Key Research and Development Plan,China(No.2023YFB3906501)the National Natural Science Foundation of China(No.42227802)the Fundamental Research Funds for the Central Universities,China(No.501JCGG2024133001)。
文摘An integrity monitoring framework is proposed to ensure the quality of the real-time Precise Point Positioning(PPP)correction data at the service end.The key contributions are designing quantitative metrics to characterize the integrity status of the precise Orbit,Clock(OC)and Code Bias(OCB)corrections,and deriving the corresponding algorithms to detect and exclude anomalies,and to evaluate the real-time accuracy levels of the OCB.Compared to many prior works whose interests focused on analyzing and improving the averaged long-term accuracy,this work is established from integrity perspective.In particular,a two-layer fault detection and identification approach is developed to reduce the miss detection and false alert probabilities.The test statistics are constructed based on the raw observations from a network of worldwide sparsely distributed monitor stations.In addition,a realistic data-driven model is established to compute the Quality Indicators(QI)for healthy OCB products.The proposed scheme is validated respectively for multi-constellation OC and code bias,using historical correction data.The results suggest that the detection algorithms can effectively identify and alert the faults,so that the remaining correction errors approximate well to Gaussian distributions.Moreover,the computed QI are shown to be consistent with the truth error variations in real time.Most importantly,the position domain verification shows noticeable positioning accuracy and robustness improvements under both nominal and faulty conditions of the OCB correction data.
