Junli Wu

Junli Wu


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 August 2017 in Remote Sensing
Verified
Journal Article
Open access
PDF file
MCMing Chen
Ming Chen
YLYang Liu
Yang Liu
JGJiming Guo
Jiming Guo
WSWeiwei Song
Weiwei Song
JWJunli Wu
Junli Wu
DZDi Zhang
Di Zhang
The precise orbit determination (POD) for BeiDou satellites is usually limited by the insufficient quantity and poor distribution of ground tracking stations. To cope with this problem, this study used the GPS and BeiDou joint POD method based on Chinese national continuous operating reference stations (CNCORS) and IGS/MGEX stations. The results show that the 3D RMS of the differences of overlapping arcs is better than 22 cm for geostationary orbit (GEO) satellites and better than 10 cm for inclined geosynchronous orbit (IGSO) and medium earth orbit (MEO) satellites. The radial RMS is better than 2 cm for all three types of BeiDou satellites. The results of satellite laser ranging (SLR) residuals show that the RMS of the IGSO and MEO satellites is better than 5 cm, whereas the GEO satellite has a systematic bias. This study investigates the contributions of CNCORS to the POD of BeiDou satellites. The results show that after the incorporation of CNCORS, the precision of overlapping arcs of the GEO, IGSO, and MEO satellites is improved by 15.5%, 57.5%, and 5.3%, respectively. In accordance with the improvement in the precision of overlapping arcs, the accuracy of the IGSO and MEO satellites assessed by the SLR is improved by 30.1% and 4.8%, respectively. The computation results and analysis demonstrate that the inclusion of CNCORS yields the biggest contribution in the improvement of orbit accuracy for IGSO satellites, when compared to GEO satellites, while the orbit improvement for MEO satellites is the lowest due to their global coverage.

21 August 2023 in Remote Sensing
Verified
Journal Article
Open access
PDF file
ZJzhang jie
zhang jie
LZLI Zhicai
LI Zhicai
PZPeng Zhang
Peng Zhang
Fei YangFei Yang
Fei Yang
JWJunli Wu
Junli Wu
QTQianchi Tan
Qianchi Tan
This study investigated the nonlinear changes in the vertical motion of 411 GNSS reference stations situated in mainland China and assessed the influence of the environmental load on their vertical displacement. The researchers evaluated the effect of environmental load by calculating the change in annual cycle amplitude before and after its removal, focusing on its impact across regions with distinct foundation types. The results demonstrate that removing the environmental load led to a considerable reduction of approximately 50.25% in the annual cycle amplitude of vertical motion for GNSS reference stations in mainland China. This reduction in amplitude improved the positioning accuracy of the stations, with the highest WRMS reduction being 2.72 mm and an average reduction of 1.03 mm. The most significant impact was observed in the southwestern, northern, and northwestern regions, where the amplitude experienced a notable decrease. Conversely, the southeastern region exhibited a corresponding increase in amplitude. This article innovatively explored the effects of environmental loads on diverse foundation types. When categorizing GNSS reference stations based on their foundation type, namely, bedrock, 18 m soil layer, and 4–8 m soil layer stations, this study found that removing the environmental load resulted in reductions in annual cycle amplitudes of 49.37%, 59.61%, and 46.48%, respectively. These findings indicate that 18 m soil layer stations were more susceptible to environmental load-induced vertical motion. In conclusion, the impact of the environmental load was crucial when analyzing the vertical motion of GNSS reference stations in mainland China, as it was essential for establishing a high-precision coordinate reference framework and studying the tectonic structure of the region.

13 December 2023 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Verified
Journal Article
Open access
PDF file
XWX. Wang
X. Wang
PZP. Zhang
P. Zhang
JWJunli Wu
Junli Wu
ZLZ. Li
Z. Li
WTW. Tang
W. Tang
ZSZ. Sun
Z. Sun
Synthetic aperture radar interferometry (InSAR) measurement technology is a new remote sensing technology that can effectively monitor slight land deformation. Compared with traditional monitoring technology, InSAR technology has the advantages of wide coverage, all-weather and low cost, providing a technical means of high-resolution, high-precision and low-cost for hidden geological hazard identification and deformation monitoring along pipelines. For purpose of this paper, we performed deformation time-series comprehensive processing and analysis on gas pipeline based on Sentinel-1 image data through small baseline data processing, and extracted pipeline deformation quantities from 2020 to 2022. The land deformation rate of the ascending track data during this period ranges from −43 mm/year to 25 mm/year, and that of the descending track data from −66 mm/year to 33 mm/year. The results show that the area along the gas pipeline is in stable condition on the whole, deformation mainly occurred along a section in the northwest of Haidian District, and a large quantity of deformation occurred since January of 2020 until December of 2021, with the maximum deformation quantity of −70mm, This result provided a reliable reference for safety monitoring and repair & maintenance of the gas pipeline.

20 January 2025
Verified
Conference Paper
Open access
JWJunli Wu
Junli Wu
XWXiaoqing Wang
Xiaoqing Wang
QZQinglan Zhang
Qinglan Zhang
In high-risk and complex mountainous environmental conditions, geological hazard bodies are often located in high mountain and canyon areas, with problems such as poor observation environment, large altitude differences, frequent extreme weather, and poor data communication. When deploying GNSS monitoring equipment using drones, they face difficulties in safe flight and precise navigation and positioning.This article studies the performance enhancement technology of multi-sensor integrated navigation. Based on the low-cost MEMS and GNSS tight combination algorithm, a comprehensive filtering technology integrating unscented Kalman filtering (UKF) and particle filtering (PF) is proposed. Two parallel running UKF and PF predictors are used to alternately use the information received by the fusion filter through input interaction, model filtering, and adaptive filtering optimization, in order to improve the reliability and accuracy of filtering, Simultaneously combining the advantages of Fuzzy Inference System (FIS) and Sparse Random Gaussian Model (SRG), the SRG model is used to estimate the initial state vector, and then FIS is used to update all current states to obtain the optimal predicted state vector. During the interruption of GNSS signal, the measurement data trained by FIS is jointly provided by INS and GNSS. In order to improve the required prediction accuracy, time sliding is used to control the data flow generated by INS and GNSS, Fully utilize the linear velocity and angular velocity increments output by INS to update the attitude, velocity, and position of unmanned aerial vehicles, improve the filtering convergence speed, navigation positioning accuracy, and reliability in the event of GNSS signal interruption. This article designs a multi-source fusion positioning system framework and integration scheme for unmanned aerial vehicle applications, and develops a high-precision fusion positioning software system, mainly including GNSS real-time data reception, GNSS data preprocessing, GNSS/INS integrated navigation data processing, real-time positioning result forwarding and other modules. The test results show that the positioning accuracy of complex environment integrated navigation is better than 0.5 meters.Key words:Geological disasters;Unmanned Aerial Vehicle;Integrated navigation;High precision

14 March 2026
Verified
Conference Paper
Open access
JWJunli Wu
Junli Wu
LZLI Zhicai
LI Zhicai
XWXq Wang
Xq Wang
YZYanfen Zhang
Yanfen Zhang
CLChen Liu
Chen Liu
The thermoelastic deformation of GNSS monuments and foundations is a significant contributor to the vertical nonlinear variations observed in the GNSS coordinate time series. A rigorous thermoelastic effect model, which takes into account the diversity of monument depths and foundation types of the reference stations, was proposed in this paper to quantify the influence of thermal expansion on the vertical displacement using 409 GNSS reference stations in Mainland China. The periodic characteristics of the GNSS vertical time series, GREL time series, and thermal expansion effect show a higher consistency between the GREL time series and the thermal expansion effects. The annual amplitude of thermal expansion for GNSS reference stations across Mainland China ranges from 0.2 mm to 1.9 mm, increasing with latitude, with a characteristic distribution of lower values in the south and higher in the north. After applying thermal expansion corrections, 79.2% of the reference stations across Mainland China exhibit a decreasing trend in amplitude, with an average reduction of 0.4 mm. Regional variability in the correction effects is significant: the largest corrections occur in Central China, followed by Northwest China and East China, while corrections in Southwest China, South China, and North China are comparatively smaller, and the corrections in Northeast China are negative. The thermal expansion correction demonstrates similar effectiveness across different types of foundational reference stations. A reduction in amplitude was observed in 78.5% of bedrock monument stations and 80.2% of soil monument stations, with a difference of 1.7% between the two. The average reduction in amplitude variation for different types was the same at 0.4 mm, indicating a comparable effect. Notably, the correction effect varies significantly based on the burial depth of the GNSS monuments, with the largest correction observed for the 5.5 m soil monument stations, followed by 2 m bedrock monument stations, 18 m soil monument stations, and 7.5 m soil monument stations. The correction effect for 8.5 m soil monument stations is negative.

14 March 2026
Verified
Conference Paper
Open access
CLChen Liu
Chen Liu
JWJunli Wu
Junli Wu
XWXq Wang
Xq Wang
CXChaoqian Xu
Chaoqian Xu
Significant spatial heterogeneity of tropospheric water vapor over the Tibetan Plateau, particularly along the vertical dimension, presents a major challenge to traditional tropospheric wet delay models used in GNSS applications across large height ranges. To address this issue, we developed a refined Tibetan zenith wet delay (ZWD) model based on pressure-level ERA5 reanalysis data with a spatial resolution of 0.25°, providing ZWD estimates at arbitrary times and heights. The model adopts an improved vertical correction in which ZWD vertical profiles are represented by a cubic polynomial height-correction function. The polynomial coefficients are estimated at each ERA5 grid node using ERA5-derived ZWD profiles and are further parameterized using harmonics up to the semidiurnal term to characterize temporal variability. ZWD at user locations is obtained through bilinear interpolation of the four surrounding grid nodes, ensuring continuous spatial and vertical coverage over Tibet. Validation using ERA5- and radiosonde-derived ZWDs shows that the TZ model achieves lower bias and reduced root-mean-square error (RMSE) than the widely used GPT3 model at both surface and elevated layers. These results indicate stable performance of the model across the full altitude range. The proposed model can be readily integrated into GNSS positioning frameworks. In precise point positioning (PPP), it may be introduced as a virtual observation of ZWD, with the model RMSE used to define the initial measurement-noise covariance. As the model provides a priori information rather than true observations, a time-varying down-weighting strategy is applied so that the ZWD estimation progressively relies on actual GNSS observations. In network real-time kinematic (NRTK) applications with large height differences, model-derived ZWD combined with mapping functions can be used to mitigate height-dependent double-differenced tropospheric delay residuals. This improves positioning accuracy, especially in the vertical component.