Because the signals of global positioning system （GPS） satellites are susceptible to obstructions in urban environment with many high buildings around, the number of GPS useful satellites is usually less than six. I...Because the signals of global positioning system （GPS） satellites are susceptible to obstructions in urban environment with many high buildings around, the number of GPS useful satellites is usually less than six. In this case, the receiver autonomous integrity monitoring （RAIM） method earmot exclude faulty satellite. In order to improve the performance of RAIM method and obtain the reliable positioning results with five satellites, the series of receiver clock bias （RCB） is regarded as one useful satellite and used to aid RAIM method. From the point of nonlinear series, a grey-Markov model for predicting the RCB series based on grey theory and Markov chain is presented. And then the model is used for aiding RAIM method in order to exclude faulty satellite. Experimental results demonstrate that the prediction model is fit for predicting the RCB series, and with the clock-based RAIM method the faulty satellite can be correctly excluded and the positioning precision of GPS receiver can be improved for the case where there are only five useful satellites.展开更多
Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Marko...Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Markov theory into a higher precision model.The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values,and thus gives forecast results involving two aspects of information.The procedure for forecasting annul maximum water levels with the GMM contains five main steps:1) establish the GM(1,1) model based on the data series;2) estimate the trend values;3) establish a Markov Model based on relative error series;4) modify the relative errors caused in step 2,and then obtain the relative errors of the second order estimation;5) compare the results with measured data and estimate the accuracy.The historical water level records(from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin,China are utilized to calibrate and verify the proposed model according to the above steps.Every 25 years' data are regarded as a hydro-sequence.Eight groups of simulated results show reasonable agreement between the predicted values and the measured data.The GMM is also applied to the 10 other hydrological stations in the same estuary.The forecast results for all of the hydrological stations are good or acceptable.The feasibility and effectiveness of this new forecasting model have been proved in this paper.展开更多
基金Project(20090580013) supported by the Aeronautic Science Foundation of ChinaProject(ZYGX2010J119) supported by the Fundamental Research Funds for the Central Universities,China
文摘Because the signals of global positioning system （GPS） satellites are susceptible to obstructions in urban environment with many high buildings around, the number of GPS useful satellites is usually less than six. In this case, the receiver autonomous integrity monitoring （RAIM） method earmot exclude faulty satellite. In order to improve the performance of RAIM method and obtain the reliable positioning results with five satellites, the series of receiver clock bias （RCB） is regarded as one useful satellite and used to aid RAIM method. From the point of nonlinear series, a grey-Markov model for predicting the RCB series based on grey theory and Markov chain is presented. And then the model is used for aiding RAIM method in order to exclude faulty satellite. Experimental results demonstrate that the prediction model is fit for predicting the RCB series, and with the clock-based RAIM method the faulty satellite can be correctly excluded and the positioning precision of GPS receiver can be improved for the case where there are only five useful satellites.
基金supported by the National Natural Science Foundation of China (50879085)the Program for New Century Excellent Talents in University(NCET-07-0778)the Key Technology Research Project of Dynamic Environmental Flume for Ocean Monitoring Facilities (201005027-4)
文摘Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Markov theory into a higher precision model.The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values,and thus gives forecast results involving two aspects of information.The procedure for forecasting annul maximum water levels with the GMM contains five main steps:1) establish the GM(1,1) model based on the data series;2) estimate the trend values;3) establish a Markov Model based on relative error series;4) modify the relative errors caused in step 2,and then obtain the relative errors of the second order estimation;5) compare the results with measured data and estimate the accuracy.The historical water level records(from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin,China are utilized to calibrate and verify the proposed model according to the above steps.Every 25 years' data are regarded as a hydro-sequence.Eight groups of simulated results show reasonable agreement between the predicted values and the measured data.The GMM is also applied to the 10 other hydrological stations in the same estuary.The forecast results for all of the hydrological stations are good or acceptable.The feasibility and effectiveness of this new forecasting model have been proved in this paper.
