Abstract Kinematic multi-sensor systems (MSS) are widely used for various applications, like mobile mapping or for autonomous systems. Depending on the application, insufficient knowledge of a system, like wrong assumptions about the accuracy of calibrations, might lead to inaccurate maps for mapping tasks or it might endanger humans in the context of autonomous driving. Uncertainty modeling can help to gain knowledge about the data captured by a system. Usually, uncertainty estimations for MSSs are done as backward modeling based on a comparison to reference datasets. In this paper, a forward modeling approach for the uncertainty modeling of a LiDAR-based kinematic MSS is chosen to estimate the uncertainty of an acquired point cloud. The MSS consists of a Leica Absolute Tracker and a platform with a 6-DoF sensor and Velodyne VLP-16 LiDAR. Results of multiple calibrations are used as the source for the uncertainty information for a Monte Carlo (MC) variance propagation of the point uncertainties. The deviations of the acquired point clouds in comparison to a ground truth can be decreased by an ensemble referencing process using the MC samples. Furthermore, the predicted uncertainties for the point clouds are well representing the actual deviations for reference panels closer to the system. Panels farther away indicate remaining distance depending effects.
{"title":"Monte Carlo variance propagation for the uncertainty modeling of a kinematic LiDAR-based multi-sensor system","authors":"Dominik Ernst, S. Vogel, H. Alkhatib, I. Neumann","doi":"10.1515/jag-2022-0033","DOIUrl":"https://doi.org/10.1515/jag-2022-0033","url":null,"abstract":"Abstract Kinematic multi-sensor systems (MSS) are widely used for various applications, like mobile mapping or for autonomous systems. Depending on the application, insufficient knowledge of a system, like wrong assumptions about the accuracy of calibrations, might lead to inaccurate maps for mapping tasks or it might endanger humans in the context of autonomous driving. Uncertainty modeling can help to gain knowledge about the data captured by a system. Usually, uncertainty estimations for MSSs are done as backward modeling based on a comparison to reference datasets. In this paper, a forward modeling approach for the uncertainty modeling of a LiDAR-based kinematic MSS is chosen to estimate the uncertainty of an acquired point cloud. The MSS consists of a Leica Absolute Tracker and a platform with a 6-DoF sensor and Velodyne VLP-16 LiDAR. Results of multiple calibrations are used as the source for the uncertainty information for a Monte Carlo (MC) variance propagation of the point uncertainties. The deviations of the acquired point clouds in comparison to a ground truth can be decreased by an ensemble referencing process using the MC samples. Furthermore, the predicted uncertainties for the point clouds are well representing the actual deviations for reference panels closer to the system. Panels farther away indicate remaining distance depending effects.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49511367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Determination of the precision of the designed observations in a geodetic network referred as the Second Order Design is an essential element of the network design process. Although the precision requirements are usually of key importance, ensuring an adequate level of reliability, understood as the possibility of outliers detection can be also vital. The subject of this study is the optimization of the observations’ precision distribution to get the balanced observation reliability indices. The objective of the work is to test usability of two optimization methods based on optimization algorithms, (simulated annealing and Hooke–Jeeves optimization), to solve the mentioned problem. An analytical method proposed by Amiri-Simkooei was applied as a reference. The performance of the above-mentioned methods was tested on two simulated angular-linear networks. Due to acceptable working time and the possibility of defining the boundary conditions on the final solution, the Hooke–Jeeves method appeared to be the most suitable to solve the analysed problem.
{"title":"Comparison of selected reliability optimization methods in application to the second order design of geodetic network","authors":"W. Odziemczyk","doi":"10.1515/jag-2023-0024","DOIUrl":"https://doi.org/10.1515/jag-2023-0024","url":null,"abstract":"Abstract Determination of the precision of the designed observations in a geodetic network referred as the Second Order Design is an essential element of the network design process. Although the precision requirements are usually of key importance, ensuring an adequate level of reliability, understood as the possibility of outliers detection can be also vital. The subject of this study is the optimization of the observations’ precision distribution to get the balanced observation reliability indices. The objective of the work is to test usability of two optimization methods based on optimization algorithms, (simulated annealing and Hooke–Jeeves optimization), to solve the mentioned problem. An analytical method proposed by Amiri-Simkooei was applied as a reference. The performance of the above-mentioned methods was tested on two simulated angular-linear networks. Due to acceptable working time and the possibility of defining the boundary conditions on the final solution, the Hooke–Jeeves method appeared to be the most suitable to solve the analysed problem.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46447663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In this contribution two new approaches are applied to predict polar motion and length-of-day. The first one is based on Dynamic Mode Decomposition (DMD), that is purely data-driven and is capable of reconstructing and forecasting time series in one numerical procedure. The other one is based on a vector autoregression of order p – VAR(p), which is a vector counterpart of AR(p) that accounts for an evolution of variables in time and a coevolution with other variables. DMD was applied to polar motion and length-of-day whilst VAR(p) to a joint prediction of polar motion. A prediction experiment concerned 30-day forecast horizon with a 7-day shift. It was performed separately for years 2017–2022 giving 48 predictions within each year. This study uses IERS EOP 14 C04 (IAU2000) as a reference for all computations and a mean absolute prediction error (MAPE) as a measure of prediction quality. For DMD, MAPEs for x coordinate of the pole vary from 0.22–0.30 mas for the 1st day and 6.64–8.56 mas for the 30th day of prediction depending on the year whilst those values vary from 0.20–0.27 mas and 5.27–7.66 mas for VAR(p) based prediction. Corresponding values for y coordinate of the pole vary from 0.15–0.23 mas and 4.27–5.93 mas for DMD, whilst 0.13–0.21 mas and 3.46–3.82 mas for VAR(p). In case of LOD forecast, MAPEs vary from 0.023–0.031 ms for the 1st day and 0.142–0.205 ms for the 30th day depending on the year.
{"title":"Dynamic mode decomposition and bivariate autoregressive short-term prediction of Earth rotation parameters","authors":"M. Ligas, Maciej Michalczak","doi":"10.1515/jag-2023-0030","DOIUrl":"https://doi.org/10.1515/jag-2023-0030","url":null,"abstract":"Abstract In this contribution two new approaches are applied to predict polar motion and length-of-day. The first one is based on Dynamic Mode Decomposition (DMD), that is purely data-driven and is capable of reconstructing and forecasting time series in one numerical procedure. The other one is based on a vector autoregression of order p – VAR(p), which is a vector counterpart of AR(p) that accounts for an evolution of variables in time and a coevolution with other variables. DMD was applied to polar motion and length-of-day whilst VAR(p) to a joint prediction of polar motion. A prediction experiment concerned 30-day forecast horizon with a 7-day shift. It was performed separately for years 2017–2022 giving 48 predictions within each year. This study uses IERS EOP 14 C04 (IAU2000) as a reference for all computations and a mean absolute prediction error (MAPE) as a measure of prediction quality. For DMD, MAPEs for x coordinate of the pole vary from 0.22–0.30 mas for the 1st day and 6.64–8.56 mas for the 30th day of prediction depending on the year whilst those values vary from 0.20–0.27 mas and 5.27–7.66 mas for VAR(p) based prediction. Corresponding values for y coordinate of the pole vary from 0.15–0.23 mas and 4.27–5.93 mas for DMD, whilst 0.13–0.21 mas and 3.46–3.82 mas for VAR(p). In case of LOD forecast, MAPEs vary from 0.023–0.031 ms for the 1st day and 0.142–0.205 ms for the 30th day depending on the year.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42537135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Android smartphone has gained attention in precise positioning applications since it can collect raw observable GNSS (Global Navigation Satellite System) data. Some studies have reported that the positioning accuracy may reach the sub-decimeter level. However, these studies mostly rely on a flagship Android smartphone that is made with better internal hardware, while the use of a non-flagship Android smartphone is not reported for this field. In this study, therefore, we explore non-flagship Android smartphones for positioning applications. We assessed the observable data quality and positioning performance of two non-flagship Android GNSS smartphones of a Samsung M21 and a Redmi Note 7. The data quality assessment includes satellite tracking and carrier-to-noise density ratio analysis. Also, the positioning performance was assessed for Single Point Positioning (SPP) and relative positioning methods in static and open-sky conditions. In addition, the residual properties of GNSS measurements were also evaluated. The results were further compared to the high-grade GNSS device. We found that the observable pseudorange and carrier phase measurements from Android smartphones were about 70 % and 36 % of what high-grade GNSS obtained. Furthermore, within a span of 1 h of observations, a considerable amount of cycle slips, amounting to as many as 518 instances, were noted in the observations from Android GNSS devices. While for the carrier-to-noise density ratio in Android smartphones, it was estimated to be about 15 dB-Hz lower than in high-grade GNSS devices. The spread of the residuals for pseudorange and carrier phase from Android smartphones was estimated to be about ±15 and ±6 m, respectively. The 3D positioning error for SPP was estimated to be about 4.7 m, with a position spread reaching tens of meters. At the same time, the 3D positioning error was calculated to be 4.6 m with the estimated standard error at the centimeter level when using the relative positioning method. To improve the positioning performance, applying a C/N0 mask to the observations become the best solution. The 3D positioning error for the relative positioning method reduces to 2.7 m when applying a C/N0 mask of 30 dB-Hz. The observable data quality of non-flagship Android GNSS devices possibly causes relatively poor performance of positioning applications.
摘要安卓智能手机由于可以收集可观测的GNSS（全球导航卫星系统）原始数据，在精确定位应用中备受关注。一些研究报告称，定位精度可能达到亚分米级别。然而，这些研究主要依赖于采用更好内部硬件制造的旗舰安卓智能手机，而该领域没有使用非旗舰安卓手机的报道。因此，在这项研究中，我们探索了非旗舰安卓智能手机的定位应用。我们评估了三星M21和Redmi Note 7这两款非旗舰安卓GNSS智能手机的可观测数据质量和定位性能。数据质量评估包括卫星跟踪和载波噪声密度比分析。此外，还评估了静态和开放天空条件下单点定位（SPP）和相对定位方法的定位性能。此外，还评估了全球导航卫星系统测量的剩余特性。将结果与高级GNSS设备进行了进一步比较。我们发现，安卓智能手机的可观测伪距和载波相位测量值约为70 % 和36 % 全球导航卫星系统获得了什么样的高等级。此外，在1的跨度内 h的观测结果，在安卓全球导航卫星系统设备的观测结果中发现了相当多的周期滑动，多达518次。而安卓智能手机的载波噪声密度比估计约为15 dB Hz，低于高级GNSS设备。安卓智能手机的伪距和载波相位的残差分布估计约为±15和±6 m、 分别。SPP的3D定位误差估计约为4.7 m、 其位置分布达到数十米。同时，计算出三维定位误差为4.6 m与使用相对定位方法时在厘米级的估计标准误差。为了提高定位性能，将C/N0掩模应用于观测成为最佳解决方案。相对定位法的三维定位误差降至2.7 m，当应用30的C/N0掩模时 dB Hz。非旗舰Android GNSS设备的可观测数据质量可能导致定位应用程序的性能相对较差。
{"title":"Assessment of GNSS observations and positioning performance from non-flagship Android smartphones","authors":"B. Bramanto, I. Gumilar, Irma A. N. Kuswanti","doi":"10.1515/jag-2023-0033","DOIUrl":"https://doi.org/10.1515/jag-2023-0033","url":null,"abstract":"Abstract Android smartphone has gained attention in precise positioning applications since it can collect raw observable GNSS (Global Navigation Satellite System) data. Some studies have reported that the positioning accuracy may reach the sub-decimeter level. However, these studies mostly rely on a flagship Android smartphone that is made with better internal hardware, while the use of a non-flagship Android smartphone is not reported for this field. In this study, therefore, we explore non-flagship Android smartphones for positioning applications. We assessed the observable data quality and positioning performance of two non-flagship Android GNSS smartphones of a Samsung M21 and a Redmi Note 7. The data quality assessment includes satellite tracking and carrier-to-noise density ratio analysis. Also, the positioning performance was assessed for Single Point Positioning (SPP) and relative positioning methods in static and open-sky conditions. In addition, the residual properties of GNSS measurements were also evaluated. The results were further compared to the high-grade GNSS device. We found that the observable pseudorange and carrier phase measurements from Android smartphones were about 70 % and 36 % of what high-grade GNSS obtained. Furthermore, within a span of 1 h of observations, a considerable amount of cycle slips, amounting to as many as 518 instances, were noted in the observations from Android GNSS devices. While for the carrier-to-noise density ratio in Android smartphones, it was estimated to be about 15 dB-Hz lower than in high-grade GNSS devices. The spread of the residuals for pseudorange and carrier phase from Android smartphones was estimated to be about ±15 and ±6 m, respectively. The 3D positioning error for SPP was estimated to be about 4.7 m, with a position spread reaching tens of meters. At the same time, the 3D positioning error was calculated to be 4.6 m with the estimated standard error at the centimeter level when using the relative positioning method. To improve the positioning performance, applying a C/N0 mask to the observations become the best solution. The 3D positioning error for the relative positioning method reduces to 2.7 m when applying a C/N0 mask of 30 dB-Hz. The observable data quality of non-flagship Android GNSS devices possibly causes relatively poor performance of positioning applications.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49497294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Variations in Total Electron Content (TEC) between the COSMIC-2, IRI-2016, and IRI-2020 are considered under different levels of geomagnetic storm activity: minor, moderate, and severe. TEC values are scrutinized at three levels of the Kp index, which serves as a metric for gauging the strength of a magnetic storm (Kp = 3.0, Kp = 6.0, Kp = 8.0) and across four-time intervals throughout 24 h to understand the performance of the models during both day and night-time conditions. Statistical analysis reveals that the standard deviation of TEC variations is lower during minor storms than moderate and severe. The comparison of variations between COSMIC-2 Radio Occultation TEC and both IRI-2016 and IRI-2020 models revealed more substantial discrepancies during day-time intervals; This was likely attributed to the dynamic and complex nature of the ionosphere influenced by solar radiation and other factors. Comparative analysis across the three levels of storm activity demonstrated that IRI2020 provided improved results over IRI2016, particularly during minor geomagnetic storm events. The study demonstrates that IRI2020 is more accurate than IRI-2016 at forecasting ionospheric conditions, especially at night and during moderate geomagnetic storm activity periods. Both models, however, provide valuable insights during challenging space weather conditions, and the results demonstrate their utility in understanding and forecasting the ionosphere’s behavior. The results yield valuable insights into space weather conditions and their effects on technology and communication, highlighting the potential for further improvement in TEC prediction models.
{"title":"Assessing the performance of IRI-2016 and IRI-2020 models using COSMIC-2 GNSS radio occultation TEC data under different magnetic activities over Egypt","authors":"A. Sherif, M. Rabah, A. Mousa, A. Zaki, A. Sedeek","doi":"10.1515/jag-2023-0068","DOIUrl":"https://doi.org/10.1515/jag-2023-0068","url":null,"abstract":"Abstract Variations in Total Electron Content (TEC) between the COSMIC-2, IRI-2016, and IRI-2020 are considered under different levels of geomagnetic storm activity: minor, moderate, and severe. TEC values are scrutinized at three levels of the Kp index, which serves as a metric for gauging the strength of a magnetic storm (Kp = 3.0, Kp = 6.0, Kp = 8.0) and across four-time intervals throughout 24 h to understand the performance of the models during both day and night-time conditions. Statistical analysis reveals that the standard deviation of TEC variations is lower during minor storms than moderate and severe. The comparison of variations between COSMIC-2 Radio Occultation TEC and both IRI-2016 and IRI-2020 models revealed more substantial discrepancies during day-time intervals; This was likely attributed to the dynamic and complex nature of the ionosphere influenced by solar radiation and other factors. Comparative analysis across the three levels of storm activity demonstrated that IRI2020 provided improved results over IRI2016, particularly during minor geomagnetic storm events. The study demonstrates that IRI2020 is more accurate than IRI-2016 at forecasting ionospheric conditions, especially at night and during moderate geomagnetic storm activity periods. Both models, however, provide valuable insights during challenging space weather conditions, and the results demonstrate their utility in understanding and forecasting the ionosphere’s behavior. The results yield valuable insights into space weather conditions and their effects on technology and communication, highlighting the potential for further improvement in TEC prediction models.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42393841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract On a regional or worldwide scale, satellite-based navigation systems can offer three-dimensional Position, Velocity, and Timing (PVT) services to an indefinite number of users. BeiDou-2 is China’s regional navigation satellite system that encompasses the Asia-Pacific region. BeiDou-2’s space section comprises GEO, MEO, and IGSO satellites, making it unique among the navigation systems. This research focuses on key aspects, including satellite visibility and signal strength, as a function of the elevation angle across the low latitude region (Indian region). In addition, the results were compared with those obtained using the GPS. The data is acquired from a GNSS receiver located at the Hyderabad station (latitude:17°24′28″, longitude:78°31′04″). The results show that BeiDou-2 satellites have better visibility than GPS satellites at all elevation angles. However, visibility is low at high elevations; therefore, multiple systems are required to obtain user information. As the elevation angle increases, the carrier-to-noise density ratio (C/No) also increases. Additionally, the standard deviation (STD) was calculated and compared to that of the GPS. Despite the average signal strength of GPS satellites remaining high throughout the elevation range, the STD of BeiDou-2 satellites was found to be low. These results indicate that further work is needed to improve the interoperability of multiple navigation systems and to provide more accurate location information to Indian users.
{"title":"Preliminary performance analysis of BeiDou-2/GPS navigation systems over the low latitude region","authors":"Santhosh Narsetty, Sricharani Thomala, Naveen Kumar Perumalla","doi":"10.1515/jag-2023-0052","DOIUrl":"https://doi.org/10.1515/jag-2023-0052","url":null,"abstract":"Abstract On a regional or worldwide scale, satellite-based navigation systems can offer three-dimensional Position, Velocity, and Timing (PVT) services to an indefinite number of users. BeiDou-2 is China’s regional navigation satellite system that encompasses the Asia-Pacific region. BeiDou-2’s space section comprises GEO, MEO, and IGSO satellites, making it unique among the navigation systems. This research focuses on key aspects, including satellite visibility and signal strength, as a function of the elevation angle across the low latitude region (Indian region). In addition, the results were compared with those obtained using the GPS. The data is acquired from a GNSS receiver located at the Hyderabad station (latitude:17°24′28″, longitude:78°31′04″). The results show that BeiDou-2 satellites have better visibility than GPS satellites at all elevation angles. However, visibility is low at high elevations; therefore, multiple systems are required to obtain user information. As the elevation angle increases, the carrier-to-noise density ratio (C/No) also increases. Additionally, the standard deviation (STD) was calculated and compared to that of the GPS. Despite the average signal strength of GPS satellites remaining high throughout the elevation range, the STD of BeiDou-2 satellites was found to be low. These results indicate that further work is needed to improve the interoperability of multiple navigation systems and to provide more accurate location information to Indian users.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43027669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The rising sea level caused by global climate change might impact the human living environment. Global navigation satellite systems (GNSS)-multipath reflection (MR) technology holds significant potential for monitoring tide level changes. GNSS-MR technology typically employs low-order polynomials to extract the signal-to-noise ratio (SNR) residuals containing GNSS interference signals. It utilizes Lomb-Scargle (LSP) spectral analysis or empirical mode decomposition (EMD) to obtain the dominant frequency of the SNR residuals, which is then converted into tidal heights. However, as the satellite elevation angle increases, the GNSS interference signals decrease and the traditional method does not adapt well to the extraction of SNR residuals under such conditions. A series of improved EMD-kind algorithms, namely ensemble empirical mode decomposition (EEMD), complementary ensemble empirical mode decomposition (CEEMD), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and improved complete ensemble empirical mode decomposition with adaptive noise (ICEEDMAN), have been proposed to address the shortcomings of EMD algorithms such as end effect and mode aliasing. However, these improved EMD-kind algorithms have yet to be reported in sea level inversion. This study investigates the mitigation effects of EMD-kind algorithms on GNSS-MR direct signal and noise to improve the stability and accuracy of an SNR residual sequence with high satellite elevation angles. Experimental data from the HKQT station for one week and the SC02 station for one year are utilized to validate the effectiveness and accuracy of these algorithms in extracting SNR residuals. Compared to the traditional polynomial method, the experimental results demonstrate that all EMD-kind algorithms effectively address the distortion issue in traditional inversion methods under long periods, higher satellite elevation angles, and low GNSS receiver sampling rates. Among these algorithms, the results from the experiments show that ICEEMDAN consistently provides the best inversion accuracy. The results of the comparative analysis show that ICEEMDAN effectively reduces non-interference signals in SNR residuals at higher satellite elevation angles, expanding the useable range of satellite elevation angles and improving the utilization and temporal resolution of GNSS data inversion. Hence, it is an effective and appropriate approach to improving the accuracy of GNSS-MR tide level monitoring.
{"title":"Comparative analysis of different empirical mode decomposition-kind algorithms on sea-level inversion by GNSS-MR","authors":"Linghuo Jian, Xinpeng Wang, Shengxiang Huang, Haining Hao, Xianyun Zhang, Xiyuan Yang","doi":"10.1515/jag-2023-0027","DOIUrl":"https://doi.org/10.1515/jag-2023-0027","url":null,"abstract":"Abstract The rising sea level caused by global climate change might impact the human living environment. Global navigation satellite systems (GNSS)-multipath reflection (MR) technology holds significant potential for monitoring tide level changes. GNSS-MR technology typically employs low-order polynomials to extract the signal-to-noise ratio (SNR) residuals containing GNSS interference signals. It utilizes Lomb-Scargle (LSP) spectral analysis or empirical mode decomposition (EMD) to obtain the dominant frequency of the SNR residuals, which is then converted into tidal heights. However, as the satellite elevation angle increases, the GNSS interference signals decrease and the traditional method does not adapt well to the extraction of SNR residuals under such conditions. A series of improved EMD-kind algorithms, namely ensemble empirical mode decomposition (EEMD), complementary ensemble empirical mode decomposition (CEEMD), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and improved complete ensemble empirical mode decomposition with adaptive noise (ICEEDMAN), have been proposed to address the shortcomings of EMD algorithms such as end effect and mode aliasing. However, these improved EMD-kind algorithms have yet to be reported in sea level inversion. This study investigates the mitigation effects of EMD-kind algorithms on GNSS-MR direct signal and noise to improve the stability and accuracy of an SNR residual sequence with high satellite elevation angles. Experimental data from the HKQT station for one week and the SC02 station for one year are utilized to validate the effectiveness and accuracy of these algorithms in extracting SNR residuals. Compared to the traditional polynomial method, the experimental results demonstrate that all EMD-kind algorithms effectively address the distortion issue in traditional inversion methods under long periods, higher satellite elevation angles, and low GNSS receiver sampling rates. Among these algorithms, the results from the experiments show that ICEEMDAN consistently provides the best inversion accuracy. The results of the comparative analysis show that ICEEMDAN effectively reduces non-interference signals in SNR residuals at higher satellite elevation angles, expanding the useable range of satellite elevation angles and improving the utilization and temporal resolution of GNSS data inversion. Hence, it is an effective and appropriate approach to improving the accuracy of GNSS-MR tide level monitoring.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45362452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ansgar Dreier, Berit Jost, H. Kuhlmann, L. Klingbeil
Abstract Due to recent improvements in sensor technology, UAV-based laser scanning is nowadays used in more and more applications like topographic surveying or forestry. The quality of the scanning result, a georeferenced 3D point cloud, mainly depends on errors coming from the trajectory estimation, the system calibration and the laser scanner itself. Due to the combined propagation of errors into the point cloud, the individual contribution is difficult to assess. Therefore, we propose an entire investigation of the scan characteristics of a 2D laser scanner without the use of the other sensors included in the system. The derived parameters include the range precision, the rangefinder offset as part of the range accuracy, the angular resolution capability and the multi-target capability of the RIEGL miniVUX-2UAV. The range precision is derived from amplitude values by a stochastic model, with observations fitting a theoretical model very well. The resolution capability in the angular direction is about twice the laser beam footprint size and therefore increases linearly for larger distances. Further, a new approach with the corresponding methodology for the investigation of multi-target capability is presented. The minimum distance between two targets to appear as separated echoes within a single laser beam is about 1.6 m and inliers within the measurement precision occur from 1.9 m separation distance. The scan attributes amplitude and deviation, which are computed during the online waveform processing, show a clear systematic relation to the range precision, also in cases of multiple echoes.
{"title":"Investigations of the scan characteristics with special focus on multi-target capability for the 2D laser scanner RIEGL miniVUX-2UAV","authors":"Ansgar Dreier, Berit Jost, H. Kuhlmann, L. Klingbeil","doi":"10.1515/jag-2022-0029","DOIUrl":"https://doi.org/10.1515/jag-2022-0029","url":null,"abstract":"Abstract Due to recent improvements in sensor technology, UAV-based laser scanning is nowadays used in more and more applications like topographic surveying or forestry. The quality of the scanning result, a georeferenced 3D point cloud, mainly depends on errors coming from the trajectory estimation, the system calibration and the laser scanner itself. Due to the combined propagation of errors into the point cloud, the individual contribution is difficult to assess. Therefore, we propose an entire investigation of the scan characteristics of a 2D laser scanner without the use of the other sensors included in the system. The derived parameters include the range precision, the rangefinder offset as part of the range accuracy, the angular resolution capability and the multi-target capability of the RIEGL miniVUX-2UAV. The range precision is derived from amplitude values by a stochastic model, with observations fitting a theoretical model very well. The resolution capability in the angular direction is about twice the laser beam footprint size and therefore increases linearly for larger distances. Further, a new approach with the corresponding methodology for the investigation of multi-target capability is presented. The minimum distance between two targets to appear as separated echoes within a single laser beam is about 1.6 m and inliers within the measurement precision occur from 1.9 m separation distance. The scan attributes amplitude and deviation, which are computed during the online waveform processing, show a clear systematic relation to the range precision, also in cases of multiple echoes.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42515527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The northern part of the East African Rift System is characterized by depleted Moho depth and thermally thinned lithosphere. This research aims to determine the Moho depth of the study area through non-linear gravity inversion and cross-validation with seismic Moho estimates. The study utilized gravity data to obtain the gravity anomaly of the Moho interface, a topographic grid for removing topographic effects, a crustal model to determine total sediment thickness and its gravitational effect, and seismic Moho depth for constraining the forward model and cross-validation. The estimated Moho depth of the study area ranges between 5 km (in the Indian Ocean) to 45 km (in the Ethiopian Highlands), with slight variation compared to seismic Moho relief. This is because the reference level, calculated for the thinner part of the study region, underestimates the entire area. Upwelling magma in the Eastern branches of the EARS may also incur slight variation in the estimated Moho depth; rifting, volcanism, melt intrusion, magmatic uplift, and tectonic setting all influence the Moho depth of the study area. Furthermore, reverberations affect most seismic Moho estimations in the region. The slight variation can be mitigated by improving the gravity network for accurate validation and precise heat flow measurement to correctly identify magmatic anomalies and density contrasts. Additionally, applying reverberation removal techniques in the study region could improve seismic Moho estimation.
{"title":"Moho depth estimation of northern of East African Rift System","authors":"Eyasu Alemu","doi":"10.1515/jag-2023-0003","DOIUrl":"https://doi.org/10.1515/jag-2023-0003","url":null,"abstract":"Abstract The northern part of the East African Rift System is characterized by depleted Moho depth and thermally thinned lithosphere. This research aims to determine the Moho depth of the study area through non-linear gravity inversion and cross-validation with seismic Moho estimates. The study utilized gravity data to obtain the gravity anomaly of the Moho interface, a topographic grid for removing topographic effects, a crustal model to determine total sediment thickness and its gravitational effect, and seismic Moho depth for constraining the forward model and cross-validation. The estimated Moho depth of the study area ranges between 5 km (in the Indian Ocean) to 45 km (in the Ethiopian Highlands), with slight variation compared to seismic Moho relief. This is because the reference level, calculated for the thinner part of the study region, underestimates the entire area. Upwelling magma in the Eastern branches of the EARS may also incur slight variation in the estimated Moho depth; rifting, volcanism, melt intrusion, magmatic uplift, and tectonic setting all influence the Moho depth of the study area. Furthermore, reverberations affect most seismic Moho estimations in the region. The slight variation can be mitigated by improving the gravity network for accurate validation and precise heat flow measurement to correctly identify magmatic anomalies and density contrasts. Additionally, applying reverberation removal techniques in the study region could improve seismic Moho estimation.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45858859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract A high-resolution gravimetric geoid model was developed for the Eastern Province Kingdom of Saudi Arabia region. The model was created using various datasets, including 320,434 land gravity measurements, 5442 shipborne marine gravity data, the DTU17 altimetry gravity model, and the XGM2019e global geopotential model. The computation strategy employed for modeling the gravimetric geoid involved the Remove-Compute-Restore method with Residual Terrain Model reduction and the 1D-Fast Fourier Transform approach technique. Geoid heights were determined using the Stokes integral with the Wong-Gore modification. To assess the accuracy of the resulting geoid models, they were compared with 4401 GNSS/Levelling points. The geoid accuracy throughout the entire area is better than 1.6 cm in terms of standard deviation (STD) after fitting.
{"title":"Determination of a gravimetric geoid model for Eastern Province in the Kingdom of Saudi Arabia","authors":"Ali Al Shehri, S. Mogren, E. Ibrahim, A. Zaki","doi":"10.1515/jag-2023-0034","DOIUrl":"https://doi.org/10.1515/jag-2023-0034","url":null,"abstract":"Abstract A high-resolution gravimetric geoid model was developed for the Eastern Province Kingdom of Saudi Arabia region. The model was created using various datasets, including 320,434 land gravity measurements, 5442 shipborne marine gravity data, the DTU17 altimetry gravity model, and the XGM2019e global geopotential model. The computation strategy employed for modeling the gravimetric geoid involved the Remove-Compute-Restore method with Residual Terrain Model reduction and the 1D-Fast Fourier Transform approach technique. Geoid heights were determined using the Stokes integral with the Wong-Gore modification. To assess the accuracy of the resulting geoid models, they were compared with 4401 GNSS/Levelling points. The geoid accuracy throughout the entire area is better than 1.6 cm in terms of standard deviation (STD) after fitting.","PeriodicalId":45494,"journal":{"name":"Journal of Applied Geodesy","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44407857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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