Atmospheric phase delay correction of PS-InSAR to Monitor Land Subsidence in Surabaya

Atmospheric phase delay is one of the most significant errors limiting the accuracy of Interferometric Synthetic Aperture Radar (InSAR) results. In this research, we used the Generic Atmospheric Correction Online Service for InSAR (GACOS) data to correct the tropospheric delay modeling from the persistent scatterers’ InSAR monitoring. Eighty-one (81) Sentinel-1A images and tropospheric delay maps from GACOS monitored land subsidence in Surabaya city between 2017 and 2019. InSAR processing was carried out using the GMTSAR software, continued with StaMPS and TRAIN, which were used to correct the tropospheric delay of PSInSAR-derived deformation measurements. The results before and after the atmospheric phase delay correction using GACOS were confirmed and analyzed in the main subsidence area. The findings of the experiments reveal that the atmospheric phase affects the mean LOS velocity results to some extent. The average difference between PS-InSAR before and after tropospheric correction is 1.734 mm/year with a standard deviation of 0.550 mm/year. The significance test of the two variables, 95%, showed that the tropospheric correction with GACOS data could affect the PS-InSAR results. Furthermore, GACOS correction may increase the error at some points, which could be due to its turbulence data’s low accuracy.

Evaluation of Seasonal Variability of First-order Ionospheric Delay Correction at L5 and S1 Frequencies Using Dual-frequency Navic System

For the precise positioning application it is important to determine and eliminate the positioning error introduced by various sources such as the ionosphere. To develop a standalone precise navigation system, India has launched the seven satellite constellations of NavIC (Navigation with Indian Constellation) system to provide precision positioning over India and surrounded landmass. Since the ionospheric delay depends on the frequency of the satellite signal and NavIC systems work at different frequencies (L5 and S1) than GPS systems (L1 and L2), it is not possible to use the GPS data-driven study for NavIC based location calculations directly. Thus there is a need for a specialized ionospheric study for NavIC systems. In addition, the ionospheric delay is directly proportional to Slant Total Electron Content (STEC) which is dependent upon diurnal and seasonal solar activity. To achieve accurate positioning facilities, there is also a need for evaluation for seasonal variability of ionospheric delay correction for NavIC receivers. This paper deals with the STEC estimation; its smoothing, and removal of instrumental biases from STEC. The determined true STEC has been used to determine first-order ionospheric delay at L5 and S1 frequencies. The delay at S1 has been found less (2 to 7m) as compared to L5 (10 to 30m). Furthermore, the seasonal variability of ionospheric delay has been analyzed using about 19 months of data (from June 2017 to December 2018) and found that the ionospheric delay follows unique seasonal characteristics which can be utilized for delay modeling. It has been also observed that the geostationary satellites of the NavIC system are more appropriate than geosynchronous satellites for ionospheric related studies.

A Real-Time Circuit Phase Delay Correction System for MEMS Vibratory Gyroscopes

With the development of the designing and manufacturing level for micro-electromechanical system (MEMS) gyroscopes, the control circuit system has become a key point to determine their internal performance. Nevertheless, the phase delay of electronic components may result in some serious hazards. This study described a real-time circuit phase delay correction system for MEMS vibratory gyroscopes. A detailed theoretical analysis was provided to clarify the influence of circuit phase delay on the in-phase and quadrature (IQ) coupling characteristics and the zero-rate output (ZRO) utilizing a force-to-rebalance (FTR) closed-loop detection and quadrature correction system. By deducing the relationship between the amplitude-frequency, the phase-frequency of the MEMS gyroscope, and the phase relationship of the whole control loop, a real-time correction system was proposed to automatically adjust the phase reference value of the phase-locked loop (PLL) and thus compensate for the real-time circuit phase delay. The experimental results showed that the correction system can accurately measure and compensate the circuit phase delay in real time. Furthermore, the unwanted IQ coupling can be eliminated and the ZRO was decreased by 755% to 0.095°/s. This correction system realized a small angle random walk of 0.978°/√h and a low bias instability of 9.458°/h together with a scale factor nonlinearity of 255 ppm at room temperature. The thermal drift of the ZRO was reduced to 0.0034°/s/°C at a temperature range from −20 to 70 °C.

A Real-Time Circuit Phase Delay Correction System for MEMS Vibratory Gyroscopes

With the development of designing and manufacturing level for micro-electromechanical system (MEMS) gyroscopes, the control circuit system becomes a key point to determine their internal performances. Nevertheless, phase delay of electron components may result in some serious hazards. This paper describes a real-time circuit phase delay correction system for MEMS vibratory gyroscopes. A detailed theoretical analysis is provided to clarify the influences of circuit phase delay on the in-phase and quadrature (IQ) coupling characteristics and zero rate output (ZRO) utilizing force-to-rebalance (FTR) closed-loop detection and quadrature correction system. By deducing the relationship between amplitude-frequency, phase-frequency of MEMS gyroscope and the phase relationship of the whole control loop, a real-time correction system is proposed to automatically adjust the phase reference value of phase-locked loop (PLL) and thus compensate for the real-time circuit phase delay. The experimental results show that the correction system can accurately measure and compensate the circuit phase delay in real time. Furthermore, the unwanted IQ coupling can be eliminated and the ZRO is decreased by 755% to 0.095°/s. This correction system realizes a small angle random walk of 0.978°/√h, and a low bias instability of 9.458°/h together with a scale factor nonlinearity of 255 ppm at room temperature. Besides, the thermal drift of ZRO is reduced to 0.0034°/s/°C at a temperature range from -20°C to 70°C.

Detecting Lake Level Change From 1992 to 2019 of Zhari Namco in Tibet Using Altimetry Data of TOPEX/Poseidon and Jason-1/2/3 Missions

Zhari Namco, a large lake in the Tibetan Plateau (TP), is sensitive to climate and environmental change. However, it is difficult to retrieve accurate and continuous lake levels for Zhari Namco. A robust strategy, including atmospheric delay correction, waveform retracking, outlier deletion, and inter-satellite adjustment, is proposed to generate a long-term series of lake levels for Zhari Namco through multi-altimeter data. Apparent biases are found in troposphere delay correction from different altimeter products and adjusted using an identical model. The threshold (20%) algorithm is employed for waveform retracking. The two-step method combining a sliding median filter and 2σ criterion is used to eliminate outliers. Tandem mission data of altimeters are used to estimate inter-satellite bias. Finally, a 27-year-long lake level time series of Zhari Namco are constructed using the TOPEX/Poseidon-Jason1/2/3 (T/P-Jason1/2/3) altimeter data from 1992 to 2019, resulting in an accuracy of 10.1 cm for T/P-Jason1/2/3. Temperature, precipitation, lake area, equivalent water height, and in situ gauge data are used for validation. The correlation coefficient more than 0.90 can be observed between this result and in situ gauge data. Compared with previous studies and existing database products, our method yields sequences with the best observational quality and the longest continuous monitoring in Zhari Namco. The time series indicates that the lake level in Zhari Namco has increased by ∼ 5.7 m, with an overall trend of 0.14 ± 0.01 m/yr, showing a fluctuating rate (1992–1999: −0.25 ± 0.05 m/yr, 2000–2008: 0.26 ± 0.04 m/yr, 2009–2016: −0.05 ± 0.03 m/yr, 2017–2019: 1.34 ± 0.34 m/yr). These findings will enhance the understanding of water budget and the effect of climate change in the TP.

Refined InSAR landslides deformation monitoring with tropospheric delay correction using multi-temporal moving-window linear model

<p>SAR Interferometry (InSAR) has been proven to be effective for measuring landslides deformation. However, the accuracy of InSAR application of landslide mapping and monitoring is limited by the complex atmospheric distortion in alpine valley areas. The sparse external atmospheric data cannot accurately reflect the complex heterogeneous atmosphere in alpine valley areas. The conventional atmospheric delay corrections based on InSAR phase are weakened by the presence of confounding signals (e.g., tropospheric delays, deformation signals, and topographic errors) and spatial heterogeneity of the troposphere.<br>In this study, we propose the multi-temporal moving-window linear model to estimate the stratified tropospheric delay. The linear relationship between the multi-temporal interferometric phases and the local terrain is estimated using moving windows and then we retrieve the vertical stratified atmospheric phase over the whole scene. Taking into account the deformation information and phase unwrapping errors, the model is solved by an iterative robust estimation algorithm weighted by both deformation rates and residual unwrapping phases.<br> We first compared our model with four other InSAR atmospheric delay correction methods: traditional empirical linear model, REA5 numerical atmospheric model, GACOS, and temporal/spatial filtering method. The results demonstrated that our proposed model has the best performance on atmospheric delay correction over the reservoir of the Lianghekou hydropower station using Sentinel-1 datasets. Meanwhile, our model was less affected by randomly turbulent phase and phase unwrapping errors, which significantly improves the accuracy of landslide deformation detection and monitoring.<br>Then, we integrated the multi-temporal moving window atmospheric delay correction model into the STAMPS-SBAS program. The high-precision wide-area time series deformation over the reservoir area can be obtained through iterating phase unwrapping and atmospheric delay correction. In particular, the phase unwrapping errors were gradually corrected during the iteration process. The improvement of the proposed model on the landslide investigations was validated through using UAV images and field surveys. Some landslides that have not been identified in the traditional time-series InSAR results can be identified after atmospheric delay correction by the proposed model.</p>