【摘 要】
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In kinematic navigation and positioning,abnormal observations and kinematic model disturbances are one of the key factors affecting the stability and reliability of positioning perfor-mance.Generally,robust adaptive filtering algorithm is used to reduce t
【机 构】
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School of Automation Science and Electrical Engineering,Beihang University,Beijing 100083,China
论文部分内容阅读
In kinematic navigation and positioning,abnormal observations and kinematic model disturbances are one of the key factors affecting the stability and reliability of positioning perfor-mance.Generally,robust adaptive filtering algorithm is used to reduce the influence of them on positioning results.However,it is difficult to accurately identify and separate the influence of abnor-mal observations and kinematic model disturbances on positioning results,especially in the appli-cation of kinematic Precise Point Positioning (PPP).This has always been a key factor limiting the performance of conventional robust adaptive filtering algorithms.To address this problem,this paper proposes a two-step robust adaptive filtering algorithm,which includes two filtering steps:without considering the kinematic model information,the first step of filtering only detects the abnormal observations.Based on the filtering results of the first step,the second step makes further detection on the kinematic model disturbances and conducts adaptive processing.Theoretical anal-ysis and experiment results indicate that the two-step robust adaptive filtering algorithm can further enhance the robustness of the filtering against the influence of abnormal observations and kinematic model disturbances on the positioning results.Ultimately,improvement of the stability and reliabil-ity of kinematic PPP is significant.
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