An enhanced spectral diversity coregistration method for dualpolarimetric 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.

SAR Image Coregistration Using Fringe Definition Detection

In order to overcome the limitation of cross correlation coregistration method for Synthetic Aperture Radar （SAR） interferometric pairs with low coherence, a new image coregistration algorithm based on Fringe Definition Detection （FDD） is presented in this paper. The Fourier transformation was utilized to obtain spectrum characteristics of interferometric fringes. The ratio between spectrum mean and peak was proposed as the evaluation index for identifying homologous pixels from interferometric images. The satellites ERS-1/2 C-band SAR acquisitions covering the Yangtze River plain delta, eastern China and ALOS/PALSAR L-band images over the Longmen Shan mountainous area, southwestern China were respectively employed in the experiment to validate the proposed coregistration method. The testing results suggested that the derived Digital Elevation Model （DEM） from FDD method had good agreement with that from the cross correlation method as well as the reference DEM at high coherence area. However, The FDD method achieved a totally improved topographic mapping accuracy by 24 percent in comparison to the cross correlation method. The FDD method also showed better robustness and achieved relatively higher performance for SAR image eoregistration in mountainous areas with low coherence.

An estimation method for InSAR interferometric phase combined with image auto-coregistration

In this paper we propose a method to estimate the InSAR interferometric phase of the steep terrain based on the terrain model of local plane by using the joint subspace projection technique proposed in our previous paper. The method takes advantage of the coherence information of neighboring pixel pairs to auto-coregister the SAR images and employs the projection of the joint signal subspace onto the corresponding joint noise subspace to estimate the terrain interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the interferometric phase （interferogram） of very steep terrain even if the coregistration error reaches one pixel. The effectiveness of the method is verified via simulated data and real data.

High sidelobe effects on interferometric coherence for circular SAR imaging geometry

The coherence is a measure for the accuracy of the interferometric phase, and the synthetic aperture radar （SAR） inter- ferometric coherence is affected by several sources of the decor- relation noise. For the circular SAR （CSAR） imaging geometry, the system response function is in the form of the Bessel function which brings a high sidelobe, and the high sidelobe of CSAR will be an important factor influencing the interferometric coherence. The effect of the high sidelobe on the coherence is analyzed and deduced. Based on the interferometric characteristics of the slight difference in the viewing angles and the potential pixel off- set in the interferometric SAR （InSAR） images, a relation between the radar impulse response and the coherence loss function is derived. From the relational model, the coherence loss function due to the high sidelobe of CSAR is then deduced, and compared with that of the conventional SAR. It is shown that the high sidelobe of CSAR focusing signal will severely affect the baseline decorre- lation and coregistration decorrelation. Simulation results confirm the theoretical analysis and quantitatively show the baseline and coregistration decorrelation degradation due to the high sidelobes of CSAR.

arcPycor:an open-source automated GIS tool to co-register elevation datasets

Subtraction of elevation datasets(e.g.digital elevation models(DEMs)and non-continuous elevation points)acquired at different times is a useful method to monitor landform surface change.Due to heavy post-processing of these elevation datasets,multi-source errors are introduced into the resulting elevation data products.To improve the estimation of elevation change,co-registration of elevation datasets is a prerequisite.This paper presents an open-source automated GIS tool(arc Pycor)for co-registering elevation datasets.arc Pycor is coded in Python 2.7 and is run via Arc GIS for Desktop.The performances of arc Pycor have been evaluated using a series of experiments.In benchmark tests,the resolved co-registration vectors of arc Pycor are compared to the predefined shift vectors obtained by artificially misaligning the slave DEMs from the master elevation datasets.Results show that arc Pycor is able to co-register DEMs with relative high accuracy and can well align slave DEMs to non-continuous elevation points,which indicates its robustness in co-registering of elevation datasets.arc Pycor is also able to co-register multi-sourced DEMs of different resolutions in mountain areas.

Robust PolInSAR optimal interferogram estimation method based on generalized scattering vector

For the polarimetric synthetic aperture radar interferometry (PoIInSAR) processing, it is necessary to coregister all the images, including the coregistration of polarimetric SAR images and the coregistration of interferometric SAR images. Otherwise, the performance of the estimated optimal interferograms will be deteriorated. A generalized scattering vector (GSV) model is proposed to execute the PoIInSAR optimal interferograms estimation. The generalized scattering vector is constructed by the Pauli scattering vectors of the processing pixel and the surrounding pixels. Even though there are coregistration errors, all the polarimetric information of the current processing pixel is entirely included in the generalized scattering vector. Therefore, the GSV-based method can automatically recover the optimal scattering mechanisms of the processing pixel with coregistration errors either in interferoemetric channels or polarimetric channels. Theoretical analysis and processing results of simulated PoISARPro data and real PALSAR data validate the effectiveness and correctness of the proposed method.

SIFT-based automatic tie-points extraction for airborne InSAR images

The scale-invariant feature transform (SIFT) is often applied to extract tie-points for airborne SAR images. When a pair of airborne SAR images differs with look angles obviously, shadow sizes and shapes of same objects will differ obviously. In main and slave SAR images, key-points around shadows often match as tie-points, although they are not homologous points. The phenomenon worsens the performance of SIFT on SAR images. On the basis of SIFT, a modified matching method is proposed to decrease the number of incorrect tie-points. High-resolution airborne SAR images are used in Experiments. Experiment results show that the proposed method is very effective to extract correct tie-points for SAR images.