Multibaseline (MB) phase unwrapping (PU) is a key processing technique in MB interferometric synthetic aperture radar (InSAR). As one of the most popular methods, the cluster analysis (CA)-based MBPU method often suffers from the problem of low noise robustness. Therefore, the block-matching and 3D filtering (BM3D) algorithm, one of the most effective filtering methods for image denoising, is applied to improve the performance of the method. Five different filtering strategies for applying BM3D are proposed in the paper: interferogram filtering (IFF), intercept filtering (ICF), cluster number filtering (CNF), unwrapped phase filtering (UPF), and simultaneous filtering (STF). In particular, while keeping the general structure of BM3D, four different similarity measures are defined for interferograms, intercepts, clusters, and unwrapped phases to accommodate the special characteristics of different filtering objects. Experiments on synthesized and real InSAR datasets prove their feasibility and effectiveness, and the experiment results show that (1) the PU accuracy and robustness of the CA-based MBPU method can be greatly improved by adding BM3D denoising; (2) simultaneous filtering of interferograms, intercepts, cluster numbers, and unwrapped phases works best, but with the worst time complexity; (3) when filtering is performed for only one object of the CA-based MBPU method, the filtering effect of CNF and UPF is better than that of IFF and ICF; and (4), considering the three indicators of PUSR, NRSE, and time consumption, CNF and UPF should be the best choices.

Ocean tide loading (OTL) causes crustal displacements in coastal regions, and the relative variation of these ground displacements may reach several centimeters across differential interferometric synthetic aperture radar (DInSAR) interferograms. However, orbit errors seriously affect the analysis of long-wavelength crustal deformation signals such as the OTL effect because of their similar signatures in DInSAR interferograms. To correct the orbit errors, we used a linear surface model to model the relative displacements of the Global Positioning System (GPS) precise point positioning (PPP) in the line of sight (LOS) direction as a priori parameter of the long-wavelength crustal deformation signals. After correcting the orbit errors, an ocean tide model was applied to correct the OTL effect in the DInSAR interferograms. The proposed approach was verified with the DInSAR interferograms from the Los Angeles basin. The experimental results confirm that the real orbit errors can be modeled by the bilinear ramp function under the constraint of the priori parameter. Moreover, after removing the orbit errors, the OTL effect, which is dominant in the long-wavelength crustal deformation signals, can be revealed, and then be effectively eliminated by the FES2004 tide model.

Deformation prediction for a salt solution mining area is essential to mining environmental protection. The combination of Synthetic Aperture Radar Interferometry (InSAR) technique with Probability Integral Method (PIM) has proven to be powerful in predicting mining-induced subsidence. However, traditional mathematical empirical models (such as linear model or linear model combined with periodical function) are mostly used in InSAR approaches, ignoring the underground mining mechanisms, which may limit the accuracy of the retrieved deformations. Inaccurate InSAR deformations will transmit an unavoidable error to the estimated PIM parameters and the forward predicted subsidence, which may induce more significant errors. Besides, theoretical contradictory and non-consistency between InSAR deformation model and future prediction model is another limitation. This paper introduces the Coordinate-Time (CT) function into InSAR deformation modeling. A novel time-series InSAR model (namely, CT-PIM) is proposed as a substitute for traditional InSAR mathematical empirical models and directly applied for future dynamic prediction. The unknown CT-PIM parameters can be estimated directly via InSAR phase observations, which can avoid the error propagation from the InSAR-generated deformations. The new approach has been tested by both simulated and real data experiments over a salt mine in China. The root mean square error (RMSE) is determined as ±10.9 mm, with an improvement of 37.2% compared to traditional static PIM prediction method. The new approach provides a more robust tool for the forecasting of mining-induced hazards in salt solution mining areas, as well as a reference for ensuring the environment protection and safety management.

Global Positioning System (GPS) kinematic precise point positioning (KPPP) is an effective approach for estimating the Earth’s tidal deformation. The accuracy of KPPP is usually evaluated by comparing results with tidal models. However, because of the uncertainties of the tidal models, the accuracy of KPPP-estimated tidal displacement is difficult to accurately determine. In this paper, systematic vector differences between GPS estimates and tidal models were estimated by least squares methods in complex domain to analyze the uncertainties of tidal models and determine the accuracy of KPPP-estimated tidal displacements. Through the use of GPS data for 12 GPS reference stations in Hong Kong from 2008 to 2017, vertical ocean tide loading displacements (after removing the body tide effect) for eight semidiurnal and diurnal tidal constituents were obtained by GPS KPPP. By an in-depth analysis of the systematic and residual differences between the GPS estimates and nine tidal models, we demonstrate that the uncertainty of the tidal displacement determined by GPS KPPP for the M2, N2, O1, and Q1 tidal constituents is 0.2 mm, and for the S2 constituent it is 0.5 mm, while the accuracy of the GPS-estimated K1, P1, and K2 tidal constituents is weak because these three tidal constituents are affected by significant common-mode errors. These results suggest that GPS KPPP can be used to precisely constrain the Earth’s vertical tidal displacement in the M2, N2, O1, and Q1 tidal frequencies.

The long‐term spatial‐temporal deformation monitoring of densely distributed infrastructures near the lake area is of great significance to understand the urban health status and prevent the potential traffic safety problems. In this paper, the permanent scatterer interferometry (PSI) technology with TerraSAR‐X imagery over the area around Dongting Lake was utilized to generate the long‐term spatial‐temporal deformation. Since the X‐band SAR interferometric phases are highly influenced by the thermal dilation of the observed objects, and the deformation of large infrastructures are highly related to external temperature, a combined deformation model considering the thermal expansion and the seasonal environmental factors was proposed to model the temporal variations of the deformation. The time series deformation and the thermal dilation parameter over the area were obtained, and a comparative study with the traditional linear model was conducted. The Dongting Lake Bridge and the typical feature points distributed around the lake were analyzed in details. In order to compensate for the unavailability of external in situ measurements over the area, phase residuals and the subsidence generated through Differential Interferometric Synthetic Aperture Radar (D‐InSAR) were utilized to verify the accuracy of the obtained deformation time series. Experiment results suggested that the proposed model is suitable and suggested for the selected study site. The root mean square error (RMSE) of the residual phase was estimated as 0.32 rad, and the RMSE compared with D‐InSAR derived deformation was ±1.1 mm.

The coastal crustal deformation caused by ocean tidal loading (OTL) varies spatially and temporally, and this spatiotemporal variation in satellite-based interferometric synthetic aperture radar (InSAR) measurements needs to be determined. In this article, we propose a spatiotemporal modeling method to estimate the OTL displacements in InSAR measurements using the kinematic precise point positioning (PPP) solutions of a regional GPS network. We tested the method through an experiment using 25 Sentinel-1B images and long-term observations of 172 GPS reference sites from Southern California. The experimental results suggest that there are significant OTL and solid Earth tide effects in the differential InSAR interferogram, which is greater than 40 mm. We find that the spatial characteristics of OTL variations can be expressed as a high-order polynomial in the two variables of latitude and longitude, and the spatiotemporally modeled PPP tidal estimates of the high-density GPS sites can provide high precision OTL correction for all the pixels in the interferogram. In the last part of the study, we show that the spatial large-scale signals in the differential interferograms of Sentinel-1B data are mainly atmospheric delay, solid Earth tidal, and OTL effect, and demonstrate the importance of the tidal correction in the InSAR measurements.