In kinematic navigation and positioning,abnormal observations and kinematic model disturbances are one of the key factors affecting the stability and reliability of positioning performance.Generally,robust adaptive fi...In kinematic navigation and positioning,abnormal observations and kinematic model disturbances are one of the key factors affecting the stability and reliability of positioning performance.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 abnormal observations and kinematic model disturbances on positioning results,especially in the application 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 analysis 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 reliability of kinematic PPP is significant.展开更多
In this paper a model of transversal filter is presented to study the adaptive match of the time variant channel. The least mean square error filtering method is used to obtain the weighting coefficients of the filter...In this paper a model of transversal filter is presented to study the adaptive match of the time variant channel. The least mean square error filtering method is used to obtain the weighting coefficients of the filter. With the purpose of speeding up the convergence of the iteration equation of adaptive filtering, an adaptive factor of the iteration step size μa is derived in this paper. The result of computer simulation shows that in the case of using adaptive μa, the convergence speed of the iteration equation is increased 2 times approximately in comparison with constant μ1. The study suggests that the adaptive filter with adaptive μa have the performance to follow the change of time-variant characteristics of the channel.展开更多
基金co-supported by the National Natural Science Foundation of China(No.41874034)the National key research and development program of China(No.2016YFB0502102)+1 种基金the Beijing Natural Science Foundation(No.4202041)the Aeronautical Science Foundation of China(No.2016ZC51024)。
文摘In kinematic navigation and positioning,abnormal observations and kinematic model disturbances are one of the key factors affecting the stability and reliability of positioning performance.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 abnormal observations and kinematic model disturbances on positioning results,especially in the application 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 analysis 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 reliability of kinematic PPP is significant.
文摘In this paper a model of transversal filter is presented to study the adaptive match of the time variant channel. The least mean square error filtering method is used to obtain the weighting coefficients of the filter. With the purpose of speeding up the convergence of the iteration equation of adaptive filtering, an adaptive factor of the iteration step size μa is derived in this paper. The result of computer simulation shows that in the case of using adaptive μa, the convergence speed of the iteration equation is increased 2 times approximately in comparison with constant μ1. The study suggests that the adaptive filter with adaptive μa have the performance to follow the change of time-variant characteristics of the channel.
