Terrain Observation By Progressive Scans Research Articles

An enhanced spectral diversity coregistration method for dual-polarimetric Sentinel-1A/B TOPS data

Sentinel-1A/B data are crucial for retrieving numerical information about surface phenomena and processes. Coregistration of terrain observation by progressive scans (TOPS) data is a critical step in its application. TOPS data must be fundamentally co-registered with an accuracy of 0.001 pixels. However, various decorrelation factors due to natural vegetation and seasonal effects affect the coregistration accuracy of TOPS data. This paper proposed an enhanced spectral diversity coregistration method for dual-polarimetric (PolESD) Sentinel-1A/B TOPS data. The PolESD method suppresses speckle noise based on a unified non-local framework in dual-pol Synthetic Aperture Radar (SAR), and extracts the phase of the optimal polarization channel from the denoised polarimetric interferometric coherency matrix. Compared with the traditional ESD method developed for single-polarization data, the PolESD method can obtain more accurate coherence and phase and get more pixels for azimuth-offset estimation. In bare areas covered with low vegetation, the number of pixels selected by PolESD is more than the Boxcar method. It can also correct misregistration more effectively and eliminate phase jumps in the burst edge. Therefore, PolESD will help improve the application of TOPS data in low-coherence scenarios.

The capability of Sentinel-1 polarization combinations for oil spill detection (study case: Karawang, Indonesia)

Marine pollution is one of issues that is widely discussed such as marine debris, chemical contamination, and oil spill. It has many impacts on the environment. Remote sensing helps detect the presence of an oil spill via satellite platform. One commonly used satellite is Synthetic-Aperture Radar (SAR) imagery, which can see oil spills even in cloudy conditions. However, the black and white appearance of the radar sometimes makes it difficult to distinguish between an oil spill and look alike. Therefore, this study aims to determine the polarization combination in the Sentinel-1 SAR imagery. Sentinel-1 Single Look Complex (SLC) is used as input and processes through various stages to obtain Coherence Vertical-Vertical (VV) and Vertical-Horizontal (VH) results. There are four steps for processing the data; convert the data to backscattering coefficient from SLC data, stacking, Terrain Observation by Progressive Scan (TOPS) coherence, and building the robust combinations. The polarization in the Sentinel-1 was calculated to determine artificial bands for the correct combination, namely Divide (VV/VH) as band 1, Average ((VV+VH)/2) as band 2, Multiple (VVxVH) as band 3, Add (VV+VH) as band 4, and Subtract (VV-VH) as band 5. Furthermore, the determination of the band used in the polarization composite display is based on the intensity value. As a result, the recommendation for Sentinel-1 polarization is obtained, which involves bands 2, 3, and 5.

An MT-InSAR Data Partition Strategy for Sentinel-1A/B TOPS Data

The Sentinel-1A/B satellite launched by European Space Agency (ESA) in 2014 provides a huge amount of free Terrain Observation by Progressive Scans (TOPS) data with global coverage to the public. The TOPS data have a frame width of 250 km and have been widely used in surface deformation monitoring. However, traditional Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) methods require large computer memory and time when processing full resolution data with large width and long strips. In addition, they hardly correct atmospheric delays and orbital errors accurately over a large area. In order to solve these problems, this study proposes a data partition strategy based on MT-InSAR methods. We first process the partitioned images over a large area by traditional MT-InSAR method, then stitch the deformation results into a complete deformation result by correcting the offsets of adjacent partitioned images. This strategy is validated in a flat urban area (Changzhou City in Jiangsu province, China), and a mountainous region (Qijiang in Chongqing City, China). Compared with traditional MT-InSAR methods, the precision of the results obtained by the new strategy is improved by about 5% for Changzhou city and about 15% for Qijiang because of its advantage in atmospheric delay correction. Furthermore, the proposed strategy needs much less memory and time than traditional methods. The total time needed by the traditional method is about 20 h, and by the proposed method, is about 8.7 h, when the number of parallel processing is 5 in the Changzhou city case. The time will be further reduced when the number of parallel processes increases.

Fast InSAR Time-Series Analysis Method in a Full-Resolution SAR Coordinate System: A Case Study of the Yellow River Delta

Ground deformation is a major determinant of delta sustainability. Sentinel-1 Terrain Observation by Progressive Scans (TOPS) data are widely used in interferometric synthetic aperture radar (InSAR) applications to monitor ground subsidence. Due to the unparalleled mapping coverage and considerable data volume requirements, high-performance computing resources including graphics processing units (GPUs) are employed in state-of-the-art methodologies. This paper presents a fast InSAR time-series processing approach targeting Sentinel-1 TOPS images to process massive data with higher efficiency and resolution. We employed a GPU-assisted InSAR processing method to accelerate data processing. Statistically homogeneous pixel selection (SHPS) filtering was used to reduce noise and detect features in scenes with minimal image resolution loss. Compared to the commonly used InSAR processing software, the proposed method significantly improved the Sentinel-1 TOPS data processing efficiency. The feasibility of the method was investigated by mapping the surface deformation over the Yellow River Delta using SAR datasets acquired between January 2021 and February 2022. The findings indicate that several events of significant subsidence have occurred in the study area. Combined with the geological environment, underground brine and hydrocarbon extraction as well as sediment consolidation and compaction contribute to land subsidence in the Yellow River Delta.

A Unified Algorithm for the Sliding Spotlight and TOPS Modes Data Processing in Bistatic Configuration of the Geostationary Transmitter with LEO Receivers

This paper deals with the imaging problem for sliding spotlight (SS) and terrain observation by progressive scan (TOPS) modes in bistatic configuration of the geostationary (GEO) transmitter with a low earth orbit satellite (LEO) receiver, named GTLR-BiSAR system. A unified imaging algorithm is proposed to process the GTLR-BiSAR data acquired in SS or TOPS modes. Our main contributions include four aspects. Firstly, the imaging geometry of this novel configuration is described in detail. Furthermore, the GTLR-BiSAR signal expressions were deduced in both time and frequency domains. These signal expressions provide great support for the design of processing the algorithm theoretically. Secondly, we present a unified deramping-based technique according to the special geometry of GTLR-BiSAR to overcome the azimuth spectrum aliasing phenomenon, which typically affects SS and TOPS data. Thirdly, the spatial variance of GTLR-BiSAR data were thoroughly analyzed based on the range-Doppler (RD) geolocation functions. On the basis of a former analysis, we put forward the azimuth variance correction strategy and modified the conventional chirp scaling function to solve the range variance problem. Finally, we completed the derivation of the two-dimensional spectrum after the range chirp scaling. On the basis of spectrum expressions, we compensated for the quadratic and residue phase, and the azimuth compression was completed by SPECAN operation. In addition, we provide a flow diagram to visually exhibit the processing procedures. At the end of this paper, the simulation and real data experiment results are presented to validate the effectiveness of the proposed algorithm.

Design and Performance Analysis of Sparse TOPS SAR Mode

Terrain observation by progressive scans (TOPS) is a novel and promising wide-swath synthetic aperture radar (SAR) imaging mode, which overcomes the scalloping effect existing in ScanSAR. Traditional imaging algorithms are computationally efficient in raw data processing of TOPS, but the problems from clutter and sidelobes suppression have not been effectively solved. Sparse SAR imaging not only effectively solves these problems, but also has great potential in improving system performance, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , lower requirement of pulse repetition frequency (PRF), higher swath coverage, less data amount, and lower system complexity. Therefore, this paper proposes a novel sparse TOPS SAR imaging mode. The proposed mode combines advantages of sparse imaging system and TOPS mode to achieve high-quality and wide-swath SAR imaging. In this mode, we first design the beam position by timing diagram. Then the basic parameters of the mode are calculated according to the radar equation, and the properties such as grating lobes are analyzed. Finally, an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L_{2,1}$</tex-math></inline-formula> -norm regularization based sparse TOPS SAR imaging algorithm is introduced to achieve the high-quality sparse scene recovery. Experimental results show that compared with conventional TOPS imaging mode, the proposed mode can obtain wide swath with lower PRF and effectively solve the effect on distributed target ambiguity ratio (DTAR). Compared with matched filtering (MF) based TOPS imaging algorithm, the sparse method can achieve unambiguous reconstruction of the considered scene from down-sampled data, and obtain the image with less artifacts.

Study on Airborne Near-Nadir TOPS SAR Imaging With Attitude Angle Error

Combined with terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR), near-nadir SAR (N-SAR) system has great potential for the surface water and ocean topography (SWOT) observation. However, one practical problem of the airborne N-SAR is the non-ideal attitude angle caused by the environment. Normally, the influence of attitude angle error can be considered as a constant squint angle of the system. However, in fact, for the near-nadir SAR system with TOPS SAR mode, the attitude angle error will cause a non-ideal 2-dimensional space-variant Doppler centroid for the receiving data and cause the traditional imaging algorithm failure. To deal with such problems, an imaging algorithm with attitude angle estimation for the near-nadir TOPS SAR system is proposed in this paper. Firstly, the influence of attitude angle error and the signal properties are analyzed. Secondly, based on the analysis, an attitude angle estimate algorithm (AAE), utilizing the nonlinear least square method (NLSM) and minimum entropy criterion, is proposed. Then, based on the estimated altitude angle, without data blocking, a full data imaging algorithm (FDA) is proposed. Its main idea is to obtain an un-ambiguous azimuth spectrum and design an appropriate range-variant azimuth filter through frequency chirp scaling (FCS). The numerical simulations and real data processing demonstrate that the proposed algorithm has good performance on attitude angle error estimation and well-focused image obtaining.

A Compressive-Sensing Approach for Opportunistic Bistatic SAR Imaging Enhancement by Harnessing Sparse Multiaperture Data

This article introduces a compressive sensing (CS)-based approach for increasing bistatic synthetic aperture radar (SAR) imaging quality in the context of a multiaperture acquisition. The analyzed data were recorded over an opportunistic bistatic setup including a stationary ground-based-receiver opportunistic C-band bistatic SAR differential interferometry (COBIS) and Sentinel-1 C-band transmitter. Since the terrain observation by progressive scans (TOPS) mode is operated, the receiver can record synchronization pulses and echoed signals from the scene during many apertures. Hence, it is possible to improve the azimuth resolution by exploiting the multiaperture data. The recorded data are not contiguous and a naive integration of the chopped azimuth phase history would generate undesired grating lobes. The proposed processing scheme exploits the natural sparsity characterizing the illuminated scene. For azimuth profiles recovery greedy, convex, and nonconvex CS solvers are analyzed. The sparsifying basis/dictionary is constructed using the synthetically generated azimuth chirp derived considering Sentinel-1 orbital parameters and COBIS position. The chirped-based CS performance is further put in contrast with a Fourier-based CS method and an autoregressive model for signal reconstruction in terms of scene extent limitations and phase restoration efficiency. Furthermore, the analysis of different receiver-looking scenarios conducted to the insertion in the processing chain of a direct and an inverse Keystone transform for range cell migration (RCM) correction to cope with squinted geometries. We provide an extensive set of simulated and real-world results that prove the proposed workflow is efficient both in improving the azimuth resolution and in mitigating the sidelobes.

A Real-Time Unified Focusing Algorithm (RT-UFA) for Multi-Mode SAR via Azimuth Sub-Aperture Complex-Valued Image Combining and Scaling

Spaceborne synthetic aperture radar (SAR) can operate at various modes, including stripmap mode, spotlight mode, sliding spotlight mode, and Terrain observation by progressive scans (TOPS) mode. These four imaging modes can be regarded as unified, differing in rotation-center ranges. To uniformly focus the data of these four imaging modes in real-time, this article proposes a real-time unified focusing algorithm (RT-UFA) for the multi-mode SAR via azimuth sub-aperture complex-valued image combining and scaling. The imaging processing can be performed while the data are being recorded. In the first stage of imaging, sub-aperture complex-valued images with relative low-resolution can be obtained by the cascade of the extended chirp scaling (ECS) and azimuth dechirp. Then, these complex-valued images are coherently combined by shifting the integer number of pixels, and thus the full-resolution image of all the recorded data can be obtained. The azimuth scaling and the pixels shifting in the RT-UFA are analyzed in detail. Simulation and SAR data results are presented to validate the analysis and RT-UFA.

An Integrated Approach for Mapping Three-Dimensional CoSeismic Displacement Fields from Sentinel-1 TOPS Data Based on DInSAR, POT, MAI and BOI Techniques: Application to the 2021 Mw 7.4 Maduo Earthquake

Sentinel-1 Terrain Observation by Progressive Scans (TOPS) data have been widely applied in earthquake studies due to their open-source policy, short revisit cycle and wide coverage. However, significant near-fault displacement gradients and the moderate azimuth resolution of TOPS data make achieving high-precision along-track measurements challenging, which prevents the generation of high-quality three-dimensional (3D) displacement maps. Here, we propose an integrated method to retrieve high-quality 3D displacements based on the differential interferometric SAR (DInSAR), burst-overlap interferometry (BOI), multiple-aperture InSAR (MAI) and pixel offset tracking (POT) techniques, which are achieved to use only two track Sentinel-1 TOPS data with different viewing geometries. The key step of this method is using a weighted fusion algorithm with the interpolated BOI-derived and MAI-derived 3D displacements. In a case study of the 2021 Maduo earthquake, the calculated root mean square errors (RMSEs) from global navigation satellite system (GNSS) data and the InSAR-derived 3D displacement fields were found to be 6.3, 5.8 and 1.7 cm in north–south, east–west and up–down components, respectively. Moreover, the slip model of the 2021 Maduo earthquake jointly estimated by DInSAR and BOI measurements indicates that this seismic event was dominated by sinistral strike-slip motion mixed with some dip-slip movements; the estimated seismic moment was 1.75 × 1020 Nm, corresponding to a Mw 7.44 event.

Burst Overlap Coregistration for Sentinel-1 TOPS DInSAR Ice Velocity Measurements

The application of Sentinel-1 interferometry to ice velocity measurements has until recently been limited by the significant horizontal scene motion associated with ice flow, which causes phase discontinuities (and associated unwrapping problems) at burst boundaries in Terrain Observation by Progressive Scans (TOPS) interferograms. Coregistering with a multiyear averaged external velocity mosaic based on offset-tracking can account for the bulk of the ice motion, but residual discontinuities sometimes remain, for example, due to seasonal variations in the ice velocity, or due to error sources such as azimuth shifts caused by ionospheric propagation. The presented method extends the external velocity coregistration with a local, spatially varying, coregistration in the burst overlap regions. This is based on the extended spectral diversity principle, which can only be applied in the overlap regions, but offers superior accuracy and resolution compared with traditional coregistration methods. The method considerably reduces phase discontinuities at burst boundaries, and potential new phase discontinuities at the overlap region edges are suppressed by an azimuth tapering of the applied coregistration shifts. An example scene is presented, and the phase discontinuities before and after application of the method are evaluated. The method is seen to remove phase discontinuities, with no adverse effects.

Motion bias analysis of sea surface height measurement by near-nadir interferometric Synthetic Aperture Radar (SAR) and its compensation method research

ABSTRACT High-precision observation of ocean surface topography is of great significance in studying the ocean mesoscale and sub-mesoscale processes. Spaceborne near-nadir interferometric synthetic aperture radar (InSAR) is capable of measuring sea surface height with centimetre-level accuracy and over a wide swath. It differs from terrestrial height measurement because the constant movement of the dynamic ocean surface creates biases in synthetic aperture radar imaging and leads to height measurement inaccuracy. This study investigates the bias due to the motion of ocean surface waves and establishes a theoretical model of the height measurement motion bias related to the ocean wave spectrums and InSAR system parameters. The motion bias model was simulated in different SAR modes, including Stripmap and Terrain Observation by Progressive Scans (TOPS) modes in various oceanic states. The results showed that the motion biases are smaller in Stripmap mode than TOPS mode under the same oceanic conditions. By adopting the total zero steering technology in Stripmap mode, the motion bias can be significantly decreased. In the same oceanic state, the motion bias increases with increasing angle of incidence. In the TOPS mode, the Doppler centroid frequency of the antenna’s signal changes linearly with the azimuth time, and thus, the biases change significantly in the azimuth direction. The motion bias model is validated by the interferometric full-link experimental simulation and the results are consistent with the theoretical values. This study provides a compensation method with millimetre level accuracy to compensate for the height measurement bias caused by sea surface motion. The theoretical derivation of motion bias models and simulation results provide feasible suggestions for the design of InSAR systems and bias compensation for sea surface height measurement.

A Channel Phase Error Estimation Method for Multichannel TOPS and Multichannel Sliding Spotlight SAR Imaging

In an azimuth multichannel synthetic aperture radar (SAR) system operating in sliding spotlight mode or Terrain Observation by Progressive Scans (TOPS) mode, due to the varying Doppler centroid and the greater processed Doppler bandwidth, the conventional channel phase error estimation algorithms that tailored to stripmap mode will fail and unable to be directly employed. To address these issues, a deramping-based method is proposed in this letter, which extends the conventional methods to sliding spotlight and TOPS cases. By multiplying the signals of each channel with the corresponding deramp phase, the problem of varying Doppler centroid is solved, and its resulting greater Doppler bandwidth is reduced. Therefore, the spectral properties of the signals are the same as those in the stripmap case, and the conventional channel phase error estimation methods can be applied subsequently. Estimation and imaging results of the simulation data and the real data of GaoFen-3 (GF-3) operating in dual-channel sliding spotlight mode demonstrate the effectiveness of the proposed method.

Persistent Scatterer Densification Through Capon-Based SAR Reprocessing for Sentinel-1 TOPS Data

Several researchers have shown that the Capon algorithm can be applied to reprocess SAR images, resulting in super-resolution reconstructed scenes with lower sidelobe levels. Thus by employing the Capon-based reprocessed images in Persistent Scatterer Interferometry (PSI), the persistent scatterer (PS) density can be increased. In this letter, we exploit the Capon-based PS densification method for Sentinel-1 (S-1)Terrain Observation by Progressive Scans(TOPS) data. We propose a revised robust approach of the Capon algorithm, which applies the automatic diagonal loading (DL) method when the condition number of the covariance matrix is big enough. The proposed approach is robust and can avoid spurious persistent scatterer candidate (PSC) points introduced by DL approaches. We also consider and analyze the spectral property caused by the scanning mode of TOPS in the reprocessing. We applied the revised-robust-Capon-based reprocessing algorithm to a stack of real-life S-1 data and selected PSCs from them. The final result shows that the number of PSs increases by approximately 30% with respect to the original stack.

Intrapulse Azimuth Frequency Scanning-Based 2-D Scanning SAR for HRWS Imaging

In this article, a novel 2-D scanning synthetic aperture radar mode for high-resolution and wide-swath imaging is introduced. Instead of the interpulse progressive azimuth beam scanning used in Terrain Observation by Progressive Scans (TOPS) mode, the intrapulse continuous azimuth frequency scanning is employed in this mode. The same azimuth resolution as the multichannel TOPS mode can be obtained through this mode in the case of single channel transmitting and receiving. And the wide-swath imaging in range is still achieved through the cyclically elevation beam scanning from burst to burst. Moreover, the antenna aperture can be fully exploited for transmitting in this mode. Therefore, it will outperform the multichannel TOPS mode especially in the case of active array antenna. The signal model of this mode is derived. Based on the analysis of the characteristics of echo spectrum, the design criteria for this mode are developed, followed by a design example. Finally, an imaging algorithm for this mode is presented. Theoretical analysis and numerical simulations verify the effectiveness of the proposed design criteria and imaging algorithm.

A Sequential Approach for Sentinel-1 TOPS Time-Series Co-Registration Over Low Coherence Scenarios

In the coming era of synthetic aperture radar (SAR) big data, the in-orbit Sentinel-1 mission will provide unprecedented data with an increasing volume. As a fundamental step of time-series analysis for such large and growing amount data, terrain observation by progressive scans (TOPS) co-registration still presents a relative challenge: 1) low coherence scenarios may degrade the estimate accuracy and 2) unprecedented and growing data volume increases the computational burden. To overcome both limitations, this article presents a sequential approach for TOPS time-series co-registration, with an emphasis on the enhanced spectral diversity (ESD) estimate accuracy over low coherence scenes. We first employ double sample over the burst overlap region to improve the statistical proprieties of sample covariance matrix, followed by ESD phase estimation using a phase linking algorithm. Then, we carry out the sequential co-registration on each mini-stack without the necessity for reprocessing the entire stack by introducing a data compression technique. Using synthetic data and real Sentinel-1 TOPS data over densely vegetated areas in the Yunan-Kweichow plateau, we fully evaluate the performance of presented approach and compare the results with those obtained from the state-of-the-art techniques. We found that the sequential approach can provide better time-series co-registration accuracy over low coherence scenes with the moderate computational efficiency.

Surface Deformation due to the 2017-2018 Agung Volcano Eruption from Interferometric Synthetic Aperture Radar (InSAR) Sentinel-1 TOPS

This paper described the application of Sentinel-1 TOPS (Terrain Observation by Progressive Scans) SAR (Synthetic Aperture Radar) to analyze the surface deformation of the Agung Volcano due to 2017-2018 eruption. Agung volcano is an active stratovolcano located in eastern part of Bali island. We processed the interferometric from a pair of Sentinel-1A each representing before and after eruption periods. The results of this research showed that the eruption of Agung Volcano during 2017-2018 has caused surface deformation. The deformation that occurs was related to changes in land surface due to lava and pyroclastic deposits resulting from the eruption process in the area around the crater and the northern slope.

Improved Ice Velocity Measurements with Sentinel-1 TOPS Interferometry

In recent years, the Sentinel-1 satellites have provided a data archive of unprecedented volume, delivering C-band Synthetic Aperture Radar (SAR) acquisitions over most of the polar ice sheets with a repeat-pass period of 6–12 days using Interferometric Wide swath (IW) imagery acquired in Terrain Observation by Progressive Scans (TOPS) mode. Due to the added complexity of TOPS-mode interferometric processing, however, Sentinel-1 ice velocity measurements currently rely exclusively on amplitude offset tracking, which generates measurements of substantially lower accuracy and spatial resolution than would be possible with Differential SAR Interferometry (DInSAR). The main difficulty associated with TOPS interferometry lies in the spatially variable azimuth phase contribution arising from along-track motion within the scene. We present a Sentinel-1 interferometric processing chain, which reduces the azimuth coupling to the line-of-sight phase signal through a spatially adaptive coregistration refinement incorporating azimuth velocity measurements. The latter are based on available ice velocity mosaics, optionally supplemented by Burst-Overlap Multi-Aperture Interferometry. The DInSAR processing chain is demonstrated for a large drainage basin in Northeast Greenland, encompassing the Northeast Greenland Ice Stream (NEGIS), and integrated with state-of-the-art offset tracking measurements. In the ice sheet interior, the combined DInSAR and offset tracking ice velocity product provides a spatial resolution of 50 × 50 m and 1-sigma accuracies of 0.18 and 0.44 m/y in the x and y components respectively, compared to GPS.

A High-Squint TOPS SAR Imaging Algorithm for Maneuvering Platforms Based on Joint Time-Doppler Deramp Without Subaperture

The beam steering of high-squint terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR) mounted on maneuvering platforms causes azimuth spectrum aliasing and nonlinear variation of the Doppler center with target azimuth position. A joint time-Doppler deramp (JTDD) based method is proposed and mainly contains two parts. First, for the azimuth spectrum aliasing, the unfolded 2-D spectrum is obtained by a modified linear deramp function in the azimuth time domain constructed from the 3-D motion parameters. After range cell migration correction (RCMC), the data supporting area in the azimuth time domain is expanded, and thus, aliased because of the nonlinear variation of Doppler center. Then, a nonlinear deramp operation in the Doppler domain is further proposed to obtain a nonaliasing signal. The proposed algorithm is efficient with less zero-padding due to the consideration of nonlinear components of Doppler center variation. Simulation and real SAR data processing are presented to validate the proposed algorithm.

A Modification to Time-Series Coregistration for Sentinel-1 TOPS Data

Very high requirement of co-registration accuracy better than 0.001 pixels for Sentinel-1 TOPS (Terrain Observation by Progressive Scan) mode presents a great challenge for application of SAR (synthetic aperture radar) interferometry in Earth Observation. The state-of-the-art techniques have demonstrated that the low coherence scenarios and abrupt loss of coherence between two arbitrary acquisitions are main sources of error to degrade the performance of TOPS time-series co-registration. In this paper, we present a modification to overcome both limitations through the coherence enhancement. The motive behind this is to improve the quality of observations before co-registration and meanwhile avoiding the coherence loss caused by fast decorrelation. To this end, principal components analysis based spatio-temporal filtering is first used to remove the artifacts in burst interferograms over strong noise areas. Rather than heuristically choosing a sub-set of interferograms as a small baseline technique does, we use Dijkstra's shortest path algorithm under graph theory framework to maximize the coherence of a sub-set interferograms. The performance of presented method against the state-of-the-art techniques is fully evaluated by synthetic data and a Sentinel-1A stack over a low coherence scene in Indonesia. Comprehensive comparisons demonstrate 9%–17% uncertainty reduction of time-series co-registration when applying our method.