01-0001-11439f68db-e036-4c08-be17-b1abf4bb0acd.png)
01-0012-075f870d4d-1fcb-4c5b-9b55-12aa8ce0d355.png)
01-0051-052ecadc80-2a2a-49c1-aeb1-dd6c4abff1e3.png)
05-0001-095363216a-abbd-400c-bb15-62b84834d935.png)
02-0001-12bad211c0-cc16-4248-a8f3-6cdb6580f5d2.jpg)
Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
2024, 49(2): 1-8.
doi: 10.12265/j.gnss.2023225
Abstract:
Ionospheric delay can seriously affect the positioning accuracy of single-frequency global navigation satellite system (GNSS) receiver. Thus, this paper assessed the positioning error of single-frequency GNSS receiver corrected by four commonly used ionospheric delay correction methods, i.e., broadcast ionospheric correction models (strategy 1), time-rotation interpolation of Global Ionosphere Map (GIM) considering the variation of the position for the sun (strategy 2), GIM corrected by ionospheric mapping function (strategy 3), and half-sum correction model (strategy 4). Meanwhile, the correction results of different methods for the single-frequency precise point positioning (SF-PPP) were evaluated by using the data collected by ground-based GNSS stations over different latitudes on solar condition days. The assessment results were listed as follows. 1) The positioning error of SF-PPP corrected by the half-sum correction model was the best, then was the ionospheric delay corrected GIM. The positioning error corrected by broadcast ionospheric model was the worst. 2) On different solar condition days of each strategy, the positioning error for low-latitude stations was the largest, the was high-latitude stations. The positioning error for mid-latitude stations was the smallest. 3) The horizontal positioning error of strategy 2 and strategy 3 was about 0.150 m over different latitudes on different solar activity periods, while the 3D positioning error is about 0.700 m. The corresponding errors were about 0.100 m and 0.500 m for strategy 4.
Ionospheric delay can seriously affect the positioning accuracy of single-frequency global navigation satellite system (GNSS) receiver. Thus, this paper assessed the positioning error of single-frequency GNSS receiver corrected by four commonly used ionospheric delay correction methods, i.e., broadcast ionospheric correction models (strategy 1), time-rotation interpolation of Global Ionosphere Map (GIM) considering the variation of the position for the sun (strategy 2), GIM corrected by ionospheric mapping function (strategy 3), and half-sum correction model (strategy 4). Meanwhile, the correction results of different methods for the single-frequency precise point positioning (SF-PPP) were evaluated by using the data collected by ground-based GNSS stations over different latitudes on solar condition days. The assessment results were listed as follows. 1) The positioning error of SF-PPP corrected by the half-sum correction model was the best, then was the ionospheric delay corrected GIM. The positioning error corrected by broadcast ionospheric model was the worst. 2) On different solar condition days of each strategy, the positioning error for low-latitude stations was the largest, the was high-latitude stations. The positioning error for mid-latitude stations was the smallest. 3) The horizontal positioning error of strategy 2 and strategy 3 was about 0.150 m over different latitudes on different solar activity periods, while the 3D positioning error is about 0.700 m. The corresponding errors were about 0.100 m and 0.500 m for strategy 4.
2024, 49(2): 9-15.
doi: 10.12265/j.gnss.2023096
Abstract:
Aiming at the problem that it is difficult to accurately separate the useful signal and noise in the GNSS coordinate time series, this paper proposes a noise reduction method based on combined weighted wavelet Z-transform (WWZ) and set empirical mode decomposition (EEMD). Through the noise reduction processing of the vertical coordinate time series of 70 continuous stations in the northwest region, the root mean square error (RMSE), signal-to-noise ratio (SNR), flicker noise (FN) amplitude and velocity uncertainty are used as the evaluation indicators respectively, which verifies that the noise reduction effect of the method in this paper is superior to wavelet noise reduction and EEMD noise reduction to a certain extent. The results show that compared with wavelet denoising and EEMD denoising, the RMSE of signal sequence after denoising is reduced by 0.331 mm and 0.757 mm respectively, and the SNR is increased by 1.911 dB and 3.635 dB respectively; The uncertainty of FN amplitude and velocity has been significantly improved, which verifies the effectiveness of the noise reduction method in this paper.
Aiming at the problem that it is difficult to accurately separate the useful signal and noise in the GNSS coordinate time series, this paper proposes a noise reduction method based on combined weighted wavelet Z-transform (WWZ) and set empirical mode decomposition (EEMD). Through the noise reduction processing of the vertical coordinate time series of 70 continuous stations in the northwest region, the root mean square error (RMSE), signal-to-noise ratio (SNR), flicker noise (FN) amplitude and velocity uncertainty are used as the evaluation indicators respectively, which verifies that the noise reduction effect of the method in this paper is superior to wavelet noise reduction and EEMD noise reduction to a certain extent. The results show that compared with wavelet denoising and EEMD denoising, the RMSE of signal sequence after denoising is reduced by 0.331 mm and 0.757 mm respectively, and the SNR is increased by 1.911 dB and 3.635 dB respectively; The uncertainty of FN amplitude and velocity has been significantly improved, which verifies the effectiveness of the noise reduction method in this paper.
2024, 49(2): 16-22.
doi: 10.12265/j.gnss.2023119
Abstract:
5G channel state information (CSI) has rich feature information, but it is greatly affected by environmental information , which directly affects the fingerprint positioning performance. In order to analyze the degree of influence of different factors on 5G signal quality and positioning performance, this paper first expounds the 5G signal characteristics and positioning algorithm based on support vector regression (SVR), analyzes the influence of terminal height, direction, human body occlusion and other factors on signal quality during data acquisition, and tests the positioning performance in three scenarios: hallway, small office and medium-sized conference room. The results show that the 5G signal is greatly affected by the surrounding environment, and the positioning accuracy of the location fingerprint localization algorithm based on 5G channel state information has positioning accuracy of 0.93 m, 1.46 m and 1.94 m respectively in three scenarios, which can meet the needs of most indoor positioning applications.
5G channel state information (CSI) has rich feature information, but it is greatly affected by environmental information , which directly affects the fingerprint positioning performance. In order to analyze the degree of influence of different factors on 5G signal quality and positioning performance, this paper first expounds the 5G signal characteristics and positioning algorithm based on support vector regression (SVR), analyzes the influence of terminal height, direction, human body occlusion and other factors on signal quality during data acquisition, and tests the positioning performance in three scenarios: hallway, small office and medium-sized conference room. The results show that the 5G signal is greatly affected by the surrounding environment, and the positioning accuracy of the location fingerprint localization algorithm based on 5G channel state information has positioning accuracy of 0.93 m, 1.46 m and 1.94 m respectively in three scenarios, which can meet the needs of most indoor positioning applications.
2024, 49(2): 23-29.
doi: 10.12265/j.gnss.2023192
Abstract:
The results of time-frequency transfer will be affected by the non-modeling error and observation noise, which is often high-frequency signals, and the construction of low-pass filter can eliminate the high-frequency noise signals in the observation sequence to a certain extent. In this paper, we analyze the nature of the Vondrak filter function, weight the clock difference sequence by the IGG3 algorithm and select the suitable filtering factor by the frequency response method; we conduct the satellite two-way time and frequency transfer experiment (TWSTFT), the satellite two-way time and frequency transfer experiment based on the software receiver (SDR-TWSTFT), and the short-baseline common-view time and frequency transfer experiment on the different links, and use the short-baseline common-sight time and frequency transfer method on the results. experiments, and the clock difference results are smoothed and denoised by anti-differential Vondrak filtering. The results show that: the filtered clock sequence can well reflect the trend of the original clock sequence; the daily fluctuation effect is effectively suppressed and the accuracy of the smoothed TWSTFT clock result is significantly improved; the accuracy of the common-view clock result is significantly improved, and the difference between the result and the precise point positiening (PPP) timing result is kept in the range of −1.0 to 1.0 ns.
The results of time-frequency transfer will be affected by the non-modeling error and observation noise, which is often high-frequency signals, and the construction of low-pass filter can eliminate the high-frequency noise signals in the observation sequence to a certain extent. In this paper, we analyze the nature of the Vondrak filter function, weight the clock difference sequence by the IGG3 algorithm and select the suitable filtering factor by the frequency response method; we conduct the satellite two-way time and frequency transfer experiment (TWSTFT), the satellite two-way time and frequency transfer experiment based on the software receiver (SDR-TWSTFT), and the short-baseline common-view time and frequency transfer experiment on the different links, and use the short-baseline common-sight time and frequency transfer method on the results. experiments, and the clock difference results are smoothed and denoised by anti-differential Vondrak filtering. The results show that: the filtered clock sequence can well reflect the trend of the original clock sequence; the daily fluctuation effect is effectively suppressed and the accuracy of the smoothed TWSTFT clock result is significantly improved; the accuracy of the common-view clock result is significantly improved, and the difference between the result and the precise point positiening (PPP) timing result is kept in the range of −1.0 to 1.0 ns.
2024, 49(2): 30-35.
doi: 10.12265/j.gnss.2023190
Abstract:
A method based on grey theory is proposed to solve the problem of unmanned moving target positioning caused by weak signals or strong interference in the BeiDou Navigation System (BDS). The method uses the grey model GM(1,1) to establish a coordinate prediction model based on the historical discrete data of unmanned moving targets, and verifies the validity of the model using measured data. The accuracy of the grey model in positioning prediction is quantitatively analyzed through simulation experiments, and its error probability is calculated. Compared with traditional positioning methods, this model requires less data and is computationally convenient, with lower complexity.
A method based on grey theory is proposed to solve the problem of unmanned moving target positioning caused by weak signals or strong interference in the BeiDou Navigation System (BDS). The method uses the grey model GM(1,1) to establish a coordinate prediction model based on the historical discrete data of unmanned moving targets, and verifies the validity of the model using measured data. The accuracy of the grey model in positioning prediction is quantitatively analyzed through simulation experiments, and its error probability is calculated. Compared with traditional positioning methods, this model requires less data and is computationally convenient, with lower complexity.
2024, 49(2): 36-42.
doi: 10.12265/j.gnss.2023084
Abstract:
Quantization is an important part of analog-to-digital conversion in satellite signal reception. Signal quantization brings energy loss, which affects the subsequent signal processing. It can effectively improve this loss on choosing appropriate quantization bits and system reference power according to signal characteristics. The quantization loss is visually expressed in the form of signal-to-noise ratio comparison, and a general analysis formula is introduced. The function of automatic gain control (AGC) module in signal quantization is explained. Combined with quantization loss formula, a selection method of reference power is explained by determining the best gain coefficient, which makes the quantization loss of signals with different signal-to-noise ratios obviously reduced. Simulation results show that this method can improve the quantization loss of satellite navigation signals by about 1.5 dB when quantizing low bits. It has certain reference significance for the design and engineering implementation of the receiver.
Quantization is an important part of analog-to-digital conversion in satellite signal reception. Signal quantization brings energy loss, which affects the subsequent signal processing. It can effectively improve this loss on choosing appropriate quantization bits and system reference power according to signal characteristics. The quantization loss is visually expressed in the form of signal-to-noise ratio comparison, and a general analysis formula is introduced. The function of automatic gain control (AGC) module in signal quantization is explained. Combined with quantization loss formula, a selection method of reference power is explained by determining the best gain coefficient, which makes the quantization loss of signals with different signal-to-noise ratios obviously reduced. Simulation results show that this method can improve the quantization loss of satellite navigation signals by about 1.5 dB when quantizing low bits. It has certain reference significance for the design and engineering implementation of the receiver.
2024, 49(2): 43-53.
doi: 10.12265/j.gnss.2023175
Abstract:
To facilitate the problems of low accuracy, fuzzy boundary, and difficulty in identifying small targets in building extraction using deep learning semantic segmentation networks, we propose an advanced attention gate U-Net (AA_U-Net) to improve the effect of building extraction. This network improves the structure of classic U-Net, using VGG16 as the backbone feature extraction network, attention-gated module participating in skip connection, and bilinear interpolation instead of deconvolution for upsampling. In the experiment, we use the Wuhan University building dataset (WHD) to compare the extraction effect of the proposed network and some classical semantic segmentation networks and explore the influence of each module of the network improvement on the extraction. The results show that the total accuracy, intersection of union, precision, recall rate, and F1 score of the network are 98.78%, 89.71%, 93.30%, 95.89%, and 94.58%, respectively. All evaluation indexes are better than the classical semantic segmentation network, and the improved modules can effectively improve the extraction accuracy. The problem of unclear outlines of buildings and fragmentation of small target buildings was improved, too. It can be used to accurately extract building information from high-resolution remote sensing images, which has guiding significance for urban planning, land use, production, life, and military reconnaissance.
To facilitate the problems of low accuracy, fuzzy boundary, and difficulty in identifying small targets in building extraction using deep learning semantic segmentation networks, we propose an advanced attention gate U-Net (AA_U-Net) to improve the effect of building extraction. This network improves the structure of classic U-Net, using VGG16 as the backbone feature extraction network, attention-gated module participating in skip connection, and bilinear interpolation instead of deconvolution for upsampling. In the experiment, we use the Wuhan University building dataset (WHD) to compare the extraction effect of the proposed network and some classical semantic segmentation networks and explore the influence of each module of the network improvement on the extraction. The results show that the total accuracy, intersection of union, precision, recall rate, and F1 score of the network are 98.78%, 89.71%, 93.30%, 95.89%, and 94.58%, respectively. All evaluation indexes are better than the classical semantic segmentation network, and the improved modules can effectively improve the extraction accuracy. The problem of unclear outlines of buildings and fragmentation of small target buildings was improved, too. It can be used to accurately extract building information from high-resolution remote sensing images, which has guiding significance for urban planning, land use, production, life, and military reconnaissance.
2024, 49(2): 54-60.
doi: 10.12265/j.gnss.2022223
Abstract:
In view of the difference of antenna phase center (APC) model and instrument manufacturer model of domestic ground receiver of different brands and models, relative positioning and precise single point positioning (PPP) methods are adopted respectively in this paper, based on the analysis of the difference of the estimated position caused by different APC correction models in GPS/BDS high precision positioning, the average difference value of the influence of different APC correction models of each antenna on the estimated position of the station is obtained. The experimental results show that different APC correction models have the same effect on the positioning accuracy of the station, but have little effect on the estimated position in the plane direction and the elevation direction. The influence of the same type of antenna on the different experimental area is consistent, and the influence of the same brand antenna on the estimated position of the station is similar, especially with the brand with the series of products its phase center closer to the impact.
In view of the difference of antenna phase center (APC) model and instrument manufacturer model of domestic ground receiver of different brands and models, relative positioning and precise single point positioning (PPP) methods are adopted respectively in this paper, based on the analysis of the difference of the estimated position caused by different APC correction models in GPS/BDS high precision positioning, the average difference value of the influence of different APC correction models of each antenna on the estimated position of the station is obtained. The experimental results show that different APC correction models have the same effect on the positioning accuracy of the station, but have little effect on the estimated position in the plane direction and the elevation direction. The influence of the same type of antenna on the different experimental area is consistent, and the influence of the same brand antenna on the estimated position of the station is similar, especially with the brand with the series of products its phase center closer to the impact.
2024, 49(2): 61-68.
doi: 10.12265/j.gnss.2023164
Abstract:
Global navigation satellite system (GNSS) water vapor tomography technique can be used to retrieve the three-dimensional spatiotemporal variation of the atmospheric water vapor, but this technique is complicated, which requires a large number of computation and a certain amount of time. Therefore, this paper proposes a rapid tomography technique that uses the precipitable water vapor (PWV) from ground-based GNSS inversion and combines with the exponential distribution characteristics of water vapor in the vertical direction to calculate the three-dimensional distribution of atmospheric water vapor. In this paper, the GNSS data over Hong Kong area, China in August 2022 are used to carry out the experiment in which the rapid tomography technique are compared with the traditional GNSS tomography technique. The experimental results show that the two methods have good agreement with the radiosonde data. Due to lacking of some details of water vapor change in the bottom region, the accuracy of the rapid tomography technique in such region is slightly lower than that of the traditional tomography technique. However, the accuracy of the rapid tomography technique is improved in the middle and high levels, and the results of the tomography technique solution are good. In addition, the rapid tomography technique proposed in this paper does not need to construct and solve complex tomography equations, and can reduce the computational complexity and improve the computing power when a large number of GNSS stations participate in water vapor tomography technique. At the same time, the water vapor density at any level can be obtained rapidly, which is a simple and efficient tomography technique.
Global navigation satellite system (GNSS) water vapor tomography technique can be used to retrieve the three-dimensional spatiotemporal variation of the atmospheric water vapor, but this technique is complicated, which requires a large number of computation and a certain amount of time. Therefore, this paper proposes a rapid tomography technique that uses the precipitable water vapor (PWV) from ground-based GNSS inversion and combines with the exponential distribution characteristics of water vapor in the vertical direction to calculate the three-dimensional distribution of atmospheric water vapor. In this paper, the GNSS data over Hong Kong area, China in August 2022 are used to carry out the experiment in which the rapid tomography technique are compared with the traditional GNSS tomography technique. The experimental results show that the two methods have good agreement with the radiosonde data. Due to lacking of some details of water vapor change in the bottom region, the accuracy of the rapid tomography technique in such region is slightly lower than that of the traditional tomography technique. However, the accuracy of the rapid tomography technique is improved in the middle and high levels, and the results of the tomography technique solution are good. In addition, the rapid tomography technique proposed in this paper does not need to construct and solve complex tomography equations, and can reduce the computational complexity and improve the computing power when a large number of GNSS stations participate in water vapor tomography technique. At the same time, the water vapor density at any level can be obtained rapidly, which is a simple and efficient tomography technique.
2024, 49(2): 69-75.
doi: 10.12265/j.gnss.2023151
Abstract:
The prediction of air quality during the winter and spring seasons can be used for the public to make reasonable arrangements for travel and traffic management by relevant government departments. The main influencing factors of PM2.5 concentration include atmospheric pollutants, precipitable water vapor (PWV), etc. To improve the accuracy of PM2.5 concentration prediction, taking Beijing-Tianjin-Hebei region as an example, it was combined fast Fourier transform (FFT) and LSTM neural network methods, considered observation elements such as GNSS, ERA5 PWV, and atmospheric pollutants, and constructed the PM2.5 concentration prediction model to predict the concentration of PM2.5 in the next 24 hours. It was used GNSS PWV to correct the ERA5 PWV in the region and evaluated the accuracy. The public change period of air pollutants, ERA5 PWV and other observation elements are extracted by FFT, and the optimal public period is 78 hours; Select various factors with the best common cycle length as the model input, and the PM2.5 concentration of the 24 hour sequence as the model output. Evaluate model accuracy through RMSE evaluation indicators. The research results are indicated that the accuracy of ERA5 PWV correction model based on GNSS is better than 2 mm in autumn and winter seasons. The prediction accuracy of the FFT-LSTM model is 10.22 μg/m3 in plain, 8.56 μg/m3 in mountainous, and 9.02 μg/m3 in plateau regions, while the predicted time limit of 24 hours. It can effectively predict the PM2.5 concentration in the next 24 hours. This model can provide reference for relevant departments in air pollution control.
The prediction of air quality during the winter and spring seasons can be used for the public to make reasonable arrangements for travel and traffic management by relevant government departments. The main influencing factors of PM2.5 concentration include atmospheric pollutants, precipitable water vapor (PWV), etc. To improve the accuracy of PM2.5 concentration prediction, taking Beijing-Tianjin-Hebei region as an example, it was combined fast Fourier transform (FFT) and LSTM neural network methods, considered observation elements such as GNSS, ERA5 PWV, and atmospheric pollutants, and constructed the PM2.5 concentration prediction model to predict the concentration of PM2.5 in the next 24 hours. It was used GNSS PWV to correct the ERA5 PWV in the region and evaluated the accuracy. The public change period of air pollutants, ERA5 PWV and other observation elements are extracted by FFT, and the optimal public period is 78 hours; Select various factors with the best common cycle length as the model input, and the PM2.5 concentration of the 24 hour sequence as the model output. Evaluate model accuracy through RMSE evaluation indicators. The research results are indicated that the accuracy of ERA5 PWV correction model based on GNSS is better than 2 mm in autumn and winter seasons. The prediction accuracy of the FFT-LSTM model is 10.22 μg/m3 in plain, 8.56 μg/m3 in mountainous, and 9.02 μg/m3 in plateau regions, while the predicted time limit of 24 hours. It can effectively predict the PM2.5 concentration in the next 24 hours. This model can provide reference for relevant departments in air pollution control.
2024, 49(2): 76-81.
doi: 10.12265/j.gnss.2023219
Abstract:
To investigate the abnormal environmental response caused by the magnitude 5.5 earthquake in Pingyuan County, Shandong Province, on August 6th, 2023, this study based on the Global Navigation Satellite System (GNSS) observation data located about 26 km northeast of the epicenter, proposes a moving time-varying frequency method and incorporates the interquartile range (IQR) method to analyze the abnormal environmental responses triggered by the earthquake. The results indicate significant anomalies in the N and E directional coordinate velocity time series at 9 to 10 seconds after the earthquake, with a minor anomaly in the U direction at 16 seconds. Moreover, the sliding time-varying frequency method detects noticeable changes 5 to 10 seconds before the abnormal jump in the velocity time series, demonstrating higher sensitivity. The study also discovered abnormal disturbances in the ionosphere above the epicenter the day before the earthquake, with the anomaly reaching 4 TECU. This research demonstrates the effectiveness of GNSS technology in detecting abnormal environmental responses during earthquakes, offering a new perspective and tools for earthquake monitoring and early warning.
To investigate the abnormal environmental response caused by the magnitude 5.5 earthquake in Pingyuan County, Shandong Province, on August 6th, 2023, this study based on the Global Navigation Satellite System (GNSS) observation data located about 26 km northeast of the epicenter, proposes a moving time-varying frequency method and incorporates the interquartile range (IQR) method to analyze the abnormal environmental responses triggered by the earthquake. The results indicate significant anomalies in the N and E directional coordinate velocity time series at 9 to 10 seconds after the earthquake, with a minor anomaly in the U direction at 16 seconds. Moreover, the sliding time-varying frequency method detects noticeable changes 5 to 10 seconds before the abnormal jump in the velocity time series, demonstrating higher sensitivity. The study also discovered abnormal disturbances in the ionosphere above the epicenter the day before the earthquake, with the anomaly reaching 4 TECU. This research demonstrates the effectiveness of GNSS technology in detecting abnormal environmental responses during earthquakes, offering a new perspective and tools for earthquake monitoring and early warning.
2024, 49(2): 82-87.
doi: 10.12265/j.gnss.2023201
Abstract:
In response to the accuracy issue in tidal signal calculation during Global Navigation Satellite System (GNSS) buoy ocean measurements, particularly in high-noise conditions affecting wave parameter calculations, this paper proposes a novel step detection and restoration method based on the sliding window cumulative sum (CUSUM) algorithm, which has been extensively utilized in non-intrusive load monitoring. The algorithm is applied to detect and correct step discontinuities in the sea surface height (SSH) obtained from precise point positioning (PPP) computations and the significant wave height (SWH) extracted from the SSH time series. The performance of the method is evaluated by comparing it with reference data from tide gauge stations and dedicated wave buoys. The results demonstrate that the proposed method significantly improves the accuracy and reliability of GNSS technology in inverting wave parameters. The root mean square error (RMSE) of SSH is enhanced by 75.5%, and the correlation is increased by 7.46%. Moreover, the RMSE of SWH is improved by 65.22%, and the correlation is boosted by 208.28%. These findings underscore the effectiveness of the proposed method in enhancing the accuracy of wave parameter extraction using GNSS technology. The method's implications for enhancing marine engineering safety and economic benefits are also highlighted, making it a valuable contribution to GNSS step detection and providing valuable insights into the extraction and application of tidal signals using GNSS technology.
In response to the accuracy issue in tidal signal calculation during Global Navigation Satellite System (GNSS) buoy ocean measurements, particularly in high-noise conditions affecting wave parameter calculations, this paper proposes a novel step detection and restoration method based on the sliding window cumulative sum (CUSUM) algorithm, which has been extensively utilized in non-intrusive load monitoring. The algorithm is applied to detect and correct step discontinuities in the sea surface height (SSH) obtained from precise point positioning (PPP) computations and the significant wave height (SWH) extracted from the SSH time series. The performance of the method is evaluated by comparing it with reference data from tide gauge stations and dedicated wave buoys. The results demonstrate that the proposed method significantly improves the accuracy and reliability of GNSS technology in inverting wave parameters. The root mean square error (RMSE) of SSH is enhanced by 75.5%, and the correlation is increased by 7.46%. Moreover, the RMSE of SWH is improved by 65.22%, and the correlation is boosted by 208.28%. These findings underscore the effectiveness of the proposed method in enhancing the accuracy of wave parameter extraction using GNSS technology. The method's implications for enhancing marine engineering safety and economic benefits are also highlighted, making it a valuable contribution to GNSS step detection and providing valuable insights into the extraction and application of tidal signals using GNSS technology.
2024, 49(2): 88-97.
doi: 10.12265/j.gnss.2023177
Abstract:
In this paper ,aiming at the characteristics of the site coordinates of the continuously operating reference stations (CORS) in Sichuan-Tibet region containing complex influence factors and abundant and weak beneficial signals ,in order to solve the problem that the regional large-scale time series data analysis and processing process is cumbersome and cannot be processed in large quantities, this paper designs and develops a GNSS coordinate time series preprocessing system, which supports the multi-site batch solving mode of large area, realizes data product preprocessing, download and visualization, and realizes least squares fitting, coarse rejection, and integration of integrated functional modules such as modeling interpolation and common-mode error correction. The long-term coordinate time series data of the crustal movement observation network of China (CMONOC) is used to evaluate the performance of the software from the aspects of solution accuracy and efficiency. The results show that the goodness of fit R2 of the least squares fitting in the N direction and E direction of each station in the CMONOC is about 99%, and the fitting effect is good. The WRMS values of the time series after coarse rejection are lower than those in all directions before rejection. The RMSE values of the results after horizontal interpolation are better than 8 mm. After the common-mode error is removed, the RMS values in both the horizontal and vertical directions decrease.
In this paper ,aiming at the characteristics of the site coordinates of the continuously operating reference stations (CORS) in Sichuan-Tibet region containing complex influence factors and abundant and weak beneficial signals ,in order to solve the problem that the regional large-scale time series data analysis and processing process is cumbersome and cannot be processed in large quantities, this paper designs and develops a GNSS coordinate time series preprocessing system, which supports the multi-site batch solving mode of large area, realizes data product preprocessing, download and visualization, and realizes least squares fitting, coarse rejection, and integration of integrated functional modules such as modeling interpolation and common-mode error correction. The long-term coordinate time series data of the crustal movement observation network of China (CMONOC) is used to evaluate the performance of the software from the aspects of solution accuracy and efficiency. The results show that the goodness of fit R2 of the least squares fitting in the N direction and E direction of each station in the CMONOC is about 99%, and the fitting effect is good. The WRMS values of the time series after coarse rejection are lower than those in all directions before rejection. The RMSE values of the results after horizontal interpolation are better than 8 mm. After the common-mode error is removed, the RMS values in both the horizontal and vertical directions decrease.
2024, 49(2): 98-105.
doi: 10.12265/j.gnss.2023194
Abstract:
In the ground antenna observation mission of low-orbit space station, the azimuth and elevation angle of the antenna to the space station are usually planned based on the satellite tool kit (STK) software, and then the antenna automatically tracks the space station. In order to ensure the accuracy and reliability of antenna tracking, it is necessary to calculate the accurate space station orbit and antenna’s azimuth and elevation angle regularly and update the planning task. Therefore, scientific analysis and evaluation of the long-term forecast accuracy of space station orbit provided by the two-line orbit root number two line elements (TLE) of LEO satellites is of great significance for ground stations to achieve accurate tracking of satellites. In this paper, taking the Mengtian space lab module of China Space Station (CSS) as an example, based on the TLE data, the simplified general perturbations (SGP4) model provided by STK software is used to calculate the satellite’s orbit as well as the space station’s azimuth and elevation angle relative to the Xi’an Ground Station, and to analyse the effect of the accuracy under different strategies. The experimental results show that updating the space station’s two rows of orbital roots on the second day can obtain better orbital results to ensure the tracking accuracy of the antenna.
In the ground antenna observation mission of low-orbit space station, the azimuth and elevation angle of the antenna to the space station are usually planned based on the satellite tool kit (STK) software, and then the antenna automatically tracks the space station. In order to ensure the accuracy and reliability of antenna tracking, it is necessary to calculate the accurate space station orbit and antenna’s azimuth and elevation angle regularly and update the planning task. Therefore, scientific analysis and evaluation of the long-term forecast accuracy of space station orbit provided by the two-line orbit root number two line elements (TLE) of LEO satellites is of great significance for ground stations to achieve accurate tracking of satellites. In this paper, taking the Mengtian space lab module of China Space Station (CSS) as an example, based on the TLE data, the simplified general perturbations (SGP4) model provided by STK software is used to calculate the satellite’s orbit as well as the space station’s azimuth and elevation angle relative to the Xi’an Ground Station, and to analyse the effect of the accuracy under different strategies. The experimental results show that updating the space station’s two rows of orbital roots on the second day can obtain better orbital results to ensure the tracking accuracy of the antenna.
2024, 49(2): 106-110.
doi: 10.12265/j.gnss.2023160
Abstract:
The function expression of the rain intensity- polarimetric phase shift model is complex, making it difficult to derive an analytical expression for inverting the rainfall intensity. Simulated annealing is an effective method for inverting rain intensity, but it is computationally time-consuming. In response to this problem, a rain intensity inversion algorithm based on the bisection method is proposed. Firstly, the rain intensity inversion problem is transformed into a function zero-point solving problem. Then, the bisection method is employed for model calculation, and a rain intensity inversion algorithm based on the bisection method is presented. Finally, the efficiency of the new algorithm is verified through simulation experiments. The results show that compared with the simulated annealing algorithm, the bisection method can significantly improve the inversion efficiency while ensuring the inversion accuracy, reducing the average required time for each inversion by about 75%.
The function expression of the rain intensity- polarimetric phase shift model is complex, making it difficult to derive an analytical expression for inverting the rainfall intensity. Simulated annealing is an effective method for inverting rain intensity, but it is computationally time-consuming. In response to this problem, a rain intensity inversion algorithm based on the bisection method is proposed. Firstly, the rain intensity inversion problem is transformed into a function zero-point solving problem. Then, the bisection method is employed for model calculation, and a rain intensity inversion algorithm based on the bisection method is presented. Finally, the efficiency of the new algorithm is verified through simulation experiments. The results show that compared with the simulated annealing algorithm, the bisection method can significantly improve the inversion efficiency while ensuring the inversion accuracy, reducing the average required time for each inversion by about 75%.
2024, 49(2): 111-126.
doi: 10.12265/j.gnss.2023105
Abstract:
Ionospheric error seriously affects the positioning accuracy of the global navigation satellite system. GPS, BDS, Galileo and GLONASS all adopt different ionospheric error correction methods. The ionospheric error correction methods in satellite navigation are introduced, and the principle and development of single frequency ionospheric error correction, dual-frequency ionospheric error correction and multi-frequency ionospheric error correction are summarized in this paper. In the single frequency correction, the ionospheric error correction techniques in enhanced systems, BDGIM model, Klobuchar model, optimization of single frequency ionospheric error correction technology-IRI constraint model and NeQuick-G model are summarized; In the dual-frequency correction, the ionosphere-free model and the ionospheric error correction methods in the PPP-RTK technology are summarized; In the multi-frequency correction, the optimization and improvement of ionospheric error correction technique with the high order correction and geomagnetic field model are summarized. Finally, the ionospheric error correction techniques and their derivative are analyzed and encapsulated, the development trend and future hotspots of ionospheric error correction technology in satellite navigation are listed and analyzed.
Ionospheric error seriously affects the positioning accuracy of the global navigation satellite system. GPS, BDS, Galileo and GLONASS all adopt different ionospheric error correction methods. The ionospheric error correction methods in satellite navigation are introduced, and the principle and development of single frequency ionospheric error correction, dual-frequency ionospheric error correction and multi-frequency ionospheric error correction are summarized in this paper. In the single frequency correction, the ionospheric error correction techniques in enhanced systems, BDGIM model, Klobuchar model, optimization of single frequency ionospheric error correction technology-IRI constraint model and NeQuick-G model are summarized; In the dual-frequency correction, the ionosphere-free model and the ionospheric error correction methods in the PPP-RTK technology are summarized; In the multi-frequency correction, the optimization and improvement of ionospheric error correction technique with the high order correction and geomagnetic field model are summarized. Finally, the ionospheric error correction techniques and their derivative are analyzed and encapsulated, the development trend and future hotspots of ionospheric error correction technology in satellite navigation are listed and analyzed.
2019, 44(2): 1-12.
doi: DOI:10.13442/j.gnss.1008-9268.2019.02.001
摘要：
2018, 43(1): 43-48.
doi: 0.13442/j.gnss.1008-9268.2018.01.008
摘要：
2020, 45(1): 19-25.
doi: DOI:10.13442/j.gnss.1008-9268.2020.01.003
摘要：
2018, 43(6): 1-7.
doi: doi:10.13442/j.gnss.1008-9268.2018.06.001
摘要：
2018, 43(3): 39-44.
doi: 10.13442/j.gnss.1008-9268.2018.03.007
摘要：
2017, 42(1): 70-73.
doi: 10.13442/j.gnss.1008-9268.2017.01.014
摘要：
2018, 43(1): 19-24.
doi: doi:10.13442/j.gnss.1008-9268.2018.01.004
摘要：
2018, 43(5): 77-83.
doi: 10.13442/j.gnss.1008-9268.2018.05.015
摘要：
2019, 44(2): 1-12.
doi: DOI:10.13442/j.gnss.1008-9268.2019.02.001
Abstract:
2018, 43(6): 8-13.
doi: doi:10.13442/j.gnss.1008-9268.2018.06.002
Abstract:
2019, 44(5): 1-9.
doi: DOI:10.13442/j.gnss.1008-9268.2019.05.001
Abstract:
2019, 44(1): 1-9.
doi: DOI:10.13442/j.gnss.1008-9268.2019.01.001
Abstract:
2017, 42(5): 53-58.
doi: 10.13442/j.gnss.1008-9268.2017.05.011
Abstract:
Bimonthly, Established 1976
Sponsored by：China Institute of Radio Transmission
Competent Authorities：China Electronics Technology Group Corporation
ISSN 1008-9268
CN 41-1317/TN
Article Recommend
MORE>
Development of factor graph and its application technology in positioning and navigation
SIC-based anti near-far effect acquisition method for pseudolites systems
GNSS interference localization technology based on position information of GNSS receivers
Fog positioning and its applications
Construction and development of satellite navigation augmentation systems
Research on GNSS time offset monitoring based on GLONASS IFBs
Download
1 Research on normal height service method of grid CORS
2 A Study of Eliminating the Gross Error in Long Range Lightning Localization
3 Construction and development of satellite navigation augmentation systems
4 Development of factor graph and its application technology in positioning and navigation
Links
MORE>
Total visits
Today's visit
