Modeling and Quantitative Analysis of Tropospheric Impact on Inclined Geosynchronous SAR Imaging

Dong, Xichao; Hu, Junling; Hu, Cheng; Li, Teng; Li, Yuanhao; Tian, Ye

doi:10.3390/rs11070803

Cited by 10 publications

(3 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, GEO SAR has excellent potential in remote sensing, disaster management, marine monitoring, etc. Most GEO SAR research focuses on system design and optimization, resolution analysis, accurate imaging algorithms, and deformation retrieval [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Moving Target Detection and Parameter Estimation via a Modified Imaging STAP with a Large Baseline in Multistatic GEO SAR

et al. 2021

Self Cite

View full text Add to dashboard Cite

With the development trends of multistatic spaceborne synthetic aperture radar (SAR), geosynchronous SAR (GEO SAR) employing several formation-flying small satellites also has great potential for remote sensing. The small satellites can cooperate to acquire multi-channel data for moving target detection and parameter estimation in strong clutters. However, multistatic GEO SAR has large satellite spacing and a curved trajectory, which induce the near-field effects and channels out of alignment, respectively, bringing about challenges for the spatial adaptive processing. These problems produce a high-order term in the multi-channel slant range model, making the traditional model and adaptive processing method invalid. In this paper, to meet the requirement of SAR focusing, we firstly derive a fourth-order slant range model and a third-order path difference model for multistatic GEO SAR. Secondly, based on the derived model, the principle of stationary phase and series reversion method are utilized to derive the spatial steering vector for a moving target, which is a basis of spatial adaptive processing in the range-Doppler domain. Thirdly, the time-domain match filtering is constructed based on the fourth-order slant range model to image the moving target. Additionally, the moving targets are detected in the image domain. The motion parameter is estimated by iteratively maximizing the output signal to clutter and noise ratio (SCNR) through the range of possible target velocities. Finally, considering that the GEO SAR is still in development, the computer simulations are carried out to verify the effectiveness and evaluate the performance.

show abstract

Section: Introductionmentioning

confidence: 99%

Moving Target Detection and Parameter Estimation via a Modified Imaging STAP with a Large Baseline in Multistatic GEO SAR

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…in 2017 with the Toolbox for Reducing Atmospheric InSAR Noise (TRAIN) [25] and in 2018 with GACOS [31], [43] or [26], [27]. In the broader context of geosynchronous synthetic aperture radar, troposphere and APS models are also proposed [44], [45], [46]. However, little is published recently on troposphere mitigation based on F) high resolution weather model data based on NWP.…”

Section: Introductionmentioning

confidence: 99%

Methodology of a Troposphere Effect Mitigation Processor for SAR Interferometry

Adam

2019

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Troposphere effect mitigation based on numerical weather prediction (NWP) is an actual research topic in SAR interferometry (InSAR) and especially in persistent scatterer interferometry (PSI). This is the reason, a scientific troposphere effect mitigation processing system has been developed. The objective of this paper is to provide the methodology of four developed algorithms, demonstrate application examples, discuss the methods characteristic and recommend techniques for operational systems. Index Terms-persistent scatterer interferometry (PSI), atmospheric phase screen (APS), numerical weather prediction (NWP), wide area processing (WAP)

show abstract

“…These influences will increase in images with higher resolution and larger incidence angles [24]. [25] proposed a power spectrum model for modeling the turbulence random errors, showing the influence of the time-varying troposphere on radar imaging. [26] analyzed different types of temporal decorrelation and suggested that an advanced atmospheric model could provide wet delay prediction with a high precision based on a numerical model [27].…”

mentioning

confidence: 99%

Evaluating Short-Term Spatio-Temporal Tropospheric Variability in Multi-Temporal SAR Interferograms Using LES Models

Hu¹,

Hanssen²,

Siebesma³

et al. 2023

Preprint

View full text Add to dashboard Cite

Atmospheric delay has a significant impact on synthetic aperture radar (SAR) interferometry, inducing spatial phase errors and decorrelation in extreme weather condition. For Low Earth Orbit (LEO) SAR missions, the atmosphere can be considered as being spatio-temporally frozen due to the short integration time. Geosynchronous (GEO) SAR missions, however, have short revisit times and extensive imaging coverage but with a longer integration time. As a result, GEOSAR interferograms can provide continuous deformation monitoring and integrated refractivity for weather forecasting. However, as the troposphere may vary significantly within the integration time, this may lead to a degradation during focusing and decorrelation of the InSAR pair. Here we simulate a time-series refractivity distribution with a high spatio-temporal resolution, for a fair-weather situation using an advanced Large Eddy Simulation (LES) model, to show the spatio-temporal variability of the troposphere on short time scales. Given GEO orbit parameters with different viewing angles along both azimuth and range directions, corresponding time-series of tropospheric interferograms are obtained based on the SAR geometry, and the impacts of different parameters are compared. Tropospheric delay is found to vary rapidly and a lead to phase gradient exceeding one cycle within a few minutes. Yet, for periods of less than ~15 minutes, a frozen-flow approximation may be successful to mitigate atmospheric decorrelation. Consequently, GEOSAR imaging should be iterative to compensate the atmospheric effects.

show abstract

Modeling and Quantitative Analysis of Tropospheric Impact on Inclined Geosynchronous SAR Imaging

Cited by 10 publications

References 56 publications

Moving Target Detection and Parameter Estimation via a Modified Imaging STAP with a Large Baseline in Multistatic GEO SAR

Moving Target Detection and Parameter Estimation via a Modified Imaging STAP with a Large Baseline in Multistatic GEO SAR

Methodology of a Troposphere Effect Mitigation Processor for SAR Interferometry

Evaluating Short-Term Spatio-Temporal Tropospheric Variability in Multi-Temporal SAR Interferograms Using LES Models

Contact Info

Product

Resources

About