Interferometric Information Research Articles

Research on absolute ranging technology of resampling phase comparison method based on FMCW

Abstract As an advanced optical precision ranging method, FMCW (frequency-modulated continuous-wave) laser interferometric ranging technology can achieve a large-scale and high-precision absolute distance measurement, so it has high research and application value in the field of coordinate measurement in large space. How to improve the resolution and stability of laser interferometry is a research difficulty in this technology. Based on FMCW laser interferometry relative distance technology, a method for achieving absolute distance measurement through phase comparison after repeated sampling is proposed. Using the FMCW laser distance measuring system, two interference optical paths of measuring interferometer and auxiliary interferometer are constructed, respectively. Synchronous sampling is performed on two interference signals, and the phase ratio of the two interference signals is obtained through the extracted frequency information. The optical path difference of the unknown measurement interferometer is derived from the known auxiliary interferometer information. This method uses a triangular wave modulation laser to reduce the influence of Doppler frequency shift and eliminate quantization errors. By using the fixed-point repeated sampling, the optical path difference information is quickly extracted, and the nonlinear error of laser interference frequency modulation is effectively reduced.

Despeckling Multitemporal Polarimetric SAR Data Based on Tensor Decomposition

Despeckling is an essential task in polarimetric synthetic aperture radar (PolSAR) image processing. Most existing filters developed for multi-temporal SAR images make use of either real or complex information. Real information refers to amplitude or intensity values, whereas complex information refers to complex covariance matrix (CCM) derived from either interferometric SAR (InSAR) or PolSAR data. The InSAR CCM is formed using images of the same polarimetric channel but acquired at different dates, and the PolSAR CCM contains information acquired simultaneously in different polarimetric channels. Therefore, these despeckling methods may present a good performance in some applications and scenes but fail in other cases, due to differences in input sources. In order to achieve a more robust result in all cases, we develop a method for multi-temporal polarimetric SAR data filtering based on tensor decomposition (TD-MPF), which aims at improving the identification of homogeneous pixels for spatially adaptive filtering. The key element of this approach consists of exploiting tensor theory to construct a new CCM that contains both polarimetric and interferometric information, as well as multi-temporal information for each pixel. The effectiveness of the proposed method and its performance are evaluated with simulated and real SAR data in comparison with several established methods.

JPPL: A joint-polarization phase linking algorithm for phase optimization of TSPolInSAR data

• As a new polarimetric optimization, the joint-polarization phase linking (JPPL) is proposed to improve the phase quality. • The used joint diagonalization can extract the ESM phases from multi-polarimetric time-series coherence matrices. • Simulated experiment analyzes the interferometric phase quality of the HH, ESPO, and JPPL algorithms quantitatively. • Real experiment demonstrates that the proposed method reduces the speckle noise and restores the interferometric phase. In the time-series interferometric SAR (TSInSAR) technology, the phase linking (PL) algorithm can exploit all interferometric combinations to reconstruct the equivalent single master (ESM) interferograms for the phase quality improvement. According to the Cramer-Rao lower bound (CRLB) for PL, besides the number of spatial samples, the time-series coherence magnitude matrix determines the reconstruction performance of the ESM phases. With the abundance of time-series polarimetric SAR data, many polarimetric optimization algorithms for distributed scatterer (DS) have been introduced, mainly the averaged coherence magnitude maximization-based exhaustive search polarimetric optimization (ESPO) algorithm. However, traditional polarimetric optimization algorithms cannot work satisfactorily because of the unstable statistical characteristics. Similarly, the multi-temporal observations of each polarimetric channel contain interferometric information. From the perspective of redundant observation, introducing full-polarization information can increase the number of observations significantly. Therefore, based on the PL theory and the polarimetric optimization, this paper proposes to perform the joint diagonalization method to simultaneously extract the ESM interferometric phases of interest from three time-series coherence matrices in the Pauli basis polarizations, called the joint-polarization phase linking (JPPL) algorithm. In the experiments, the proposed JPPL algorithm can better improve the optimization performance of time-series interferometric phases of DSs than the HH and traditional ESPO algorithms in terms of speckle noise reduction and interferometric phase restoration.

Interferometric beam combination with a triangular tricoupler photonic chip

Beam combiners are important components of an optical/infrared astrophysical interferometer, with many variants as to how to optimally combine two or more beams of light to fringe-track and obtain the complex fringe visibility. One such method is the use of an integrated optics chip that can instantaneously provide the measurement of visibility without temporal or spatial modulation of the optical path. Current asymmetric planar designs are complex, resulting in a throughput penalty, and so here, we present developments into a three-dimensional triangular tricoupler that can provide the required interferometric information with a simple design and only three outputs. Such a beam combiner is planned to be integrated into the upcoming Pyxis interferometer, where it can serve as a high-throughput beam combiner with a low size footprint. Results into the characterization of such a coupler are presented, highlighting a throughput of 85 ± 7 % and a flux splitting ratio between 33:33:33 and 52:31:17 over a 20% bandpass. We also show the response of the chip to changes in the optical path, obtaining an instantaneous complex visibility and group delay estimate at each input delay.

On the Discovery of a Roman Fortified Site in Gafsa, Southern Tunisia, Based on High-Resolution X-Band Satellite Radar Data

The increasing availability of multiplatform, multiband, very-high-resolution (VHR) satellite synthetic aperture radar (SAR) data has attracted the attention of a growing number of scientists and archeologists. In particular, over the last two decades, archeological research has benefited from SAR development mainly due to its unique ability to acquire scenes both at night and during the day under all weather conditions, its penetration capability, and the provided polarimetric and interferometric information. This paper explored the potential of a novel method (nonlocal (NL)-SAR) using TerraSAR-X (TSX) and Constellation of Small Satellites for Mediterranean Basin Observation (COSMO)-SkyMed (CSK) data to detect buried archeological remains in steep, rugged terrain. In this investigation, two test sites were selected in southern Tunisia, home to some of the most valuable and well-preserved limes from the Roman Empire. To enhance the subtle signals linked to archeological features, the speckle noise introduced into SAR data by the environment and SAR system must be mitigated. Accordingly, the NL-SAR method was applied to SAR data pertaining to these two significant test sites. Overall, the investigation (i) revealed a fortified settlement from the Roman Empire and (ii) identified an unknown urban area abandoned during this period via a field survey, thus successfully confirming the capability of SAR data to reveal unknown, concealed archeological sites, even in areas with a complex topography.

On the Value of Sentinel-1 InSAR Coherence Time-Series for Vegetation Classification

Synthetic aperture radar (SAR) acquisitions are mainly deemed suitable for mapping dynamic land-cover and land-use scenarios due to their timeliness and reliability. This particularly applies to Sentinel-1 imagery. Nevertheless, the accurate mapping of regions characterized by a mixture of crops and grasses can still represent a challenge. Radar time-series have to date mainly been exploited through backscatter intensities, whereas only fewer contributions have focused on analyzing the potential of interferometric information, intuitively enhanced by the short revisit. In this paper, we evaluate, as primary objective, the added value of short-temporal baseline coherences over a complex agricultural area in the São Paulo state, cultivated with heterogeneously (asynchronously) managed annual crops, grasses for pasture and sugarcane plantations. We also investigated the sensitivity of the radar information to the classification methods as well as to the data preparation and sampling practices. Two supervised machine learning methods—namely support vector machine (SVM) and random forest (RF)—were applied to the Sentinel-1 time-series at the pixel and field levels. The results highlight that an improvement of 10 percentage points (p.p.) in the classification accuracy can be achieved by using the coherence in addition to the backscatter intensity and by combining co-polarized (VV) and cross-polarized (VH) information. It is shown that the largest contribution in class discrimination is brought during winter, when dry vegetation and bare soils can be expected. One of the added values of coherence was indeed identified in the enhanced sensitivity to harvest events in a small but significant number of cases.

Improvement of the signal-to-noise ratio in a low power self-mixing interferometer using a coupled interferometric effect.

We present experimental results of a low-emission self-mixing interferometer that uses a coupled interferometric effect to improve the signal produced by a vibrating target. This method is intended to be useful in applications where the target is prone to be damaged by high-intensity laser sources. The beam of a Fabry-Perot laser diode is split and ∼21% of the original emission is used to measure the harmonic micro-displacements of the target using the self-mixing effect. A portion of the residual beam, which also carries the interferometric information related to the target displacement, is reinjected back into the laser cavity by means of a fixed reflector, causing a second interferometric phenomenon that improves the signal-to-noise ratio of the measurement by up to ∼13 dB. A theoretical description of the phenomena is also proposed. Further, we apply this technique to the two most common self-mixing sensing schemes: internal photodiode and junction voltage. The reported results show good agreement with theory and prove the capability of the method to enhance the SNR in SMI schemes.

Interferometric Phase Retrieval for Multimode InSAR via Sparse Recovery

Modern spaceborne synthetic aperture radar (SAR) features a capacity of multiple imaging modes. It comes with Earth-observation data archives consisting of SAR images acquired in various modes with different resolutions and coverage. In this context, in addition to using single-mode images for SAR interferometry (InSAR), exploiting images acquired in different imaging modes for InSAR can provide extra interferograms and, thus, favors the retrieval of interferometric information. The interferometric processing of multimode image pairs requires special considerations due to significant variations in the Doppler spectra. Conventionally, the InSAR technique only uses the spectral band common in both master and slave images, and the remaining band is discarded before interferogram formation. Therefore, conventional processing cannot make full use of the observed data, and the interferogram quality is limited by the common band spectra. In this article, by exploiting the conventionally discarded spectrum, we present a new interferometric phase retrieval method for multimode InSAR data to improve interferogram quality. To this end, first, we propose a linear model to characterize the interferometric phase of a multimode image pair based on image spectral relation. Second, we adopt a sparse recovery method to inverse the linear model for the retrieval of the interferometric phase. Finally, we present real-data experiments on TerraSAR-X staring spotlight to sliding spotlight interferometry and Sentinel-1 strip map to Terrain Observation by Progressive Scan (TOPS) interferometry to test the proposed method. The experiment results show that the proposed method can provide interferograms with reduced phase noise and defocusing effect for multimode InSAR.

Introducing Spatial Regularization in SAR Tomography Reconstruction

The resolution achieved by current synthetic aperture radar (SAR) sensors provides a detailed visualization of urban areas. Spaceborne sensors such as TerraSAR-X can be used to analyze large areas at a very high resolution. In addition, repeated passes of the satellite give access to temporal and interferometric information on the scene. Because of the complex 3-D structure of urban surfaces, scatterers located at different heights (ground, building facade, and roof) produce radar echoes that often get mixed within the same radar cells. These echoes must be numerically unmixed in order to get a fine understanding of the radar images. This unmixing is at the core of SAR tomography. SAR tomography reconstruction is generally performed in two steps: 1) reconstruction of the so-called tomogram by vertical focusing, at each radar resolution cell, to extract the complex amplitudes (a 1-D processing) and 2) transformation from radar geometry to ground geometry and extraction of significant scatterers. We propose to perform the tomographic inversion directly in ground geometry in order to enforce spatial regularity in 3-D space. This inversion requires solving a large-scale nonconvex optimization problem. We describe an iterative method based on variable splitting and the augmented Lagrangian technique. Spatial regularizations can easily be included in this generic scheme. We illustrate, on simulated data and a TerraSAR-X tomographic data set, the potential of this approach to produce 3-D reconstructions of urban surfaces.

A detection method for near-ship wakes based on interferometric magnitude, phase and physical shape in ATI-SAR systems

ABSTRACTNear-ship wakes approximately form a triangle region on the sea surface, and they differ from the background sea in a wave pattern, wave propagation direction and velocity, and fluid particle orbital motion. The differences are observed by along-track interferometric synthetic aperture radar (ATI-SAR) systems, and can be properly measured by the ATI techniques. In this paper, a detection method for near-ship wakes based on interferometric magnitude, phase and physical shape in ATI-SAR systems is proposed. The complex multi-look interferometric information for near-ship wakes is first utilized to detect potential pixels. Then, a cluster algorithm is designed based on the interferometric phase and spatial position characteristics of near-ship wakes. After clustering the detected pixels and performing image close operation, the near-ship wakes, which is the triangular region with a much larger physical area than those of common ships or other false alarms, can be identified. Finally, simulation results validate the effectiveness of the proposed method.

Quantifying the force between mercury and mica across an ionic liquid using white light interferometry

HypothesisUnder axisymmetric conditions, changes in the thickness of the thin film between a fluid drop and a solid revealed by white light interferometry can provide information about the interaction of the bodies. Thus, in principle one can quantify the force between the surfaces using interferometric information of film thickness profile. This is needed to quantify and analyze drop-solid interactions across complex fluids such as an ionic liquid to independently characterize new surface forces. ExperimentsInterferometric fringes were obtained in experiments on the interaction between a mercury drop and mica across a film of room temperature ionic liquid. The data is analyzed using a novel formula giving the total force acting on the drop. The calculations are compared with two other approaches to estimating forces. Qualitative and quantitative differences are discussed. FindingsThis is the first report of forces measured between mercury and mica across an ionic liquid. The system is subjected to different applied electric potentials. In each case a long ranged, exponentially decaying repulsive force is found. At small separations, the system becomes unstable and the surfaces jump into contact. The comparison of force calculation methods demonstrates the superiority of the force approach proposed here.

Covariance Symmetries Detection in PolInSAR Data

In the last two decades, the use of synthetic aperture radar (SAR) for remote sensing purposes has significantly developed due to improvements in the quality and the availability of the images. Two powerful SAR techniques, namely, polarimetry and interferometry, have further increased the range of applications of the sensed data. Using polarimetry, geometrical properties and geophysical parameters, such as shape, roughness, texture, and moisture content, can be retrieved with considerable accuracy, while interferometric information may be used to extract vertical information with accuracy less than 1 cm. In this paper, the potential of using joint polarimetry and interferometry techniques in SAR data (PolInSAR) for the purpose of SAR image classification is investigated. To achieve this goal, we extend a covariance symmetry detection framework to the PolInSAR scenario. The proposed approach will be shown to be able to exploit the peculiar structures of the covariance matrices of PolInSAR images to discriminate structures within the image. Results using real-SAR data are presented to validate the effectiveness of the proposed approach.

Assessment of the Potential of H/A/Alpha Decomposition for Polarimetric Interferometric SAR Data

This paper presents an extension of H/A/Alpha polarimetric SAR (PolSAR) decomposition for polarimetric interferometric SAR (PolInSAR) images, and introduces new parameters using both polarimetric and interferometric data. These parameters provide more information than extracted parameters from H/A/Alpha PolSAR decomposition. The new parameters significantly increase the potential of PolSAR data for, for example, forest and oriented building discrimination. With the availability of interferometric information in addition to PolSAR information, there is the possibility to reduce the entropy of PolSAR data. The relationship between the entropy of PolInSAR decomposition and coherence between images has also been shown. E-SAR PolInSAR L-band data of Oberpfaffenhofen, Germany, Northern Sweden, and Goermin, Germany are used to validate the H/A/Alpha PolInSAR decomposition. The experimental results on the first data set, including agricultural, forest, and urban areas, show that this decomposition has a better performance than the standard H/A/Alpha decomposition method in oriented urban areas with large orientation angle, for example. Also, the results on the second data set of a forest area show that the PolInSAR decomposition has more reasonable and superior performance over the PolSAR decomposition. The forest and nonforest regions can be correctly discriminated by using the presented PolInSAR parameters. Finally, in the last data set, the better detection of the agricultural crops and fields boundaries is provided by the proposed method.

InSAR imaging based on L1 regularisation joint reconstruction via complex approximated message passing

This Letter presents an interferometric synthetic aperture radar (InSAR) imaging method based on L1 regularisation joint reconstruction model via complex approximated message passing (CAMP). The proposed method enables to ensure the preservation of background information via CAMP and interferometric phase difference information among multiple channels via L1 regularisation joint reconstruction model. Compared with conventional matched filtering results, the proposed method can improve the performance of interferometric phase noise reduction and the continuity of interference fringes, which has broad application prospect in InSAR imaging. Experiments carried out on real data confirmed the effectiveness of the proposed method with improved performance.

Assessment of CryoSat-2 interferometric and non-interferometric SAR altimetry over ice sheets

The launch of CryoSat-2 heralded a new era of interferometric Synthetic Aperture Radar altimetry over the Polar Ice Sheets. The mission’s novel SAR interferometric (SARIn) mode of operation has enabled monitoring of rapidly changing coastal regions, which had been challenging for previous low resolution altimeters. Given the growing requirement to continue the 25-year altimeter record, there is now a need to assess the differences between existing SAR and SARIn altimeter datasets, with a view to understanding the impact on ice sheet retrievals of the different radar hardware and processing methodologies. Uniquely, CryoSat-2 data can be processed both with and without interferometric information, offering the opportunity to directly compare the SAR and SARIn products generated by the current ground segment. Here, we provide a first comparison of these Level-2 datasets, and evaluate their capacity to measure ice sheet elevation and elevation change. We find that the current interferometric product has substantially improved precision, accuracy and coverage compared to its non-interferometric counterpart, yielding a ∼35% improvement in the root-mean-square-difference (RMSD) of elevations recorded at orbital cross-overs, and a ∼30% lower RMSD of elevation rates relative to Operation IceBridge airborne altimeter measurements. This analysis demonstrates the value that the interferometer adds to the current CryoSat-2 configuration, and highlights the importance for non-interferometric SAR Level-2 processing of the auxiliary data used to identify the location of the echoing point. These results provide a benchmark of the relative performance of the Level-2 interferometric and non-interferometric products currently produced by the ground segment, which will help to inform the design and implementation of a future polar radar altimeter mission.

Multi-layer topography measurement using a new hybrid single-shot technique: Chromatic Confocal Coherence Tomography (CCCT).

Often measurement tasks occur, where specimens consist of multiple layers or topography shall be examined through contaminations. Especially for unknown layer materials, it is important to measure the layer's refractive index to compensate for the errors induced on the measurement of underlying surfaces. Chromatic Confocal Coherence Tomography is proposed as a new hybrid single-shot scheme for a simultaneous measurement of thickness and refractive index of semitransparent layers, combining chromatic confocal and interferometric information. As a proof of concept, first measurements are presented along with a short discussion about their uncertainties, where minimal layer thickness and resolution are dominated by the confocal part of the signal, that is mainly influenced by the chosen microscope objective.

MuLoG, or How to Apply Gaussian Denoisers to Multi-Channel SAR Speckle Reduction?

Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric, or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.

Potential of TerraSAR-X and Sentinel 1 imagery to map deforested areas and derive degradation status in complex rain forests of Ecuador

This study explores the use of TerraSAR-X (X-Band) and Sentinel-1 (C-Band) SAR data for detecting degraded forests and deforestation in the Sumaco Biosphere Reserve, Ecuador. The study area shows a complex topography and permanent cloud cover, which complicates forest monitoring from optical remote sensing. Thresholds of canopy cover for degraded forest were identified by field data. Then a straightforward object-based approach was applied. Statistics on SAR backscatter were estimated from the objects and used as input to a random forest classification to map forest and non-forest areas. Finally, forest degradation was assessed using a moving window procedure applying the earlier identified thresholds on the forest / non-forest map. The SAR data were found adequate to map deforestation (overall accuracy of 81% for forest/non forest maps) but less accurate to fully assess forest degradation. However, multi-temporal SAR data can be useful to construct baseline data of the forest extent. Polarization and interferometric information could enhance the presented results for classifying forest / non forest areas and mapping forest degradation.

Ship Detection With TanDEM-X Data Extending the Polarimetric Notch Filter

Synthetic aperture radar plays a vital role in ship detection due to the possibility of acquiring high-resolution images at nighttime and under cloud cover. This letter is focused on improving ship detection, exploiting the capability of TanDEM-X to collect interferometric data. Currently, along-track interferometry is used to estimate the speed of ocean surface currents or vessels. The detection of ships plays an important role in the retrieval of vessel speed and is mostly executed exploiting only one of the TanDEM-X images (i.e., not taking advantage of the availability of a second interferometric image). The aim of this study is to extend the capabilities of a ship detector previously developed by the authors, namely, geometrical perturbation-polarimetric notch filter (GP-PNF), to include single-pass interferometric information acquired by TanDEM-X. Interestingly, such enhancement makes it possible to employ the GP-PNF with single-polarization data as well. The proposed algorithms and their statistical behavior are tested on five Tandem-X dual-polarimetric HH/VV scenes acquired in the North Sea. The detection results are validated, exploiting the Automatic Identification System location of vessels. All of the new GP-PNF versions show good performance and provide larger vessel–sea contrast compared with single-channel detectors.

Extracting DEM from airborne X-band data based on PolInSAR

Abstract. Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) is a new trend of SAR remote sensing technology which combined polarized multichannel information and Interferometric information. It is of great significance for extracting DEM in some regions with low precision of DEM such as vegetation coverage area and building concentrated area. In this paper we describe our experiments with high-resolution X-band full Polarimetric SAR data acquired by a dual-baseline interferometric airborne SAR system over an area of Danling in southern China. Pauli algorithm is used to generate the double polarimetric interferometry data, Singular Value Decomposition (SVD), Numerical Radius (NR) and Phase diversity (PD) methods are used to generate the full polarimetric interferometry data. Then we can make use of the polarimetric interferometric information to extract DEM with processing of pre filtering , image registration, image resampling, coherence optimization, multilook processing, flat-earth removal, interferogram filtering, phase unwrapping, parameter calibration, height derivation and geo-coding. The processing system named SARPlore has been exploited based on VC++ led by Chinese Academy of Surveying and Mapping. Finally compared optimization results with the single polarimetric interferometry, it has been observed that optimization ways can reduce the interferometric noise and the phase unwrapping residuals, and improve the precision of DEM. The result of full polarimetric interferometry is better than double polarimetric interferometry. Meanwhile, in different terrain, the result of full polarimetric interferometry will have a different degree of increase.