Polarimetric Interferometry Research Articles

Plasma electron density profile tomography for EAST based on integrated data analysis

Abstract Plasma electron density is a crucial parameter in plasma studies. Accurately inverting the plasma electron density profile is vital for plasma control experiments and the investigation of plasma physical mechanisms. This paper proposes an integrated data analysis (IDA) method based on Bayesian inference, which integrates polarimetric interferometry (POINT), hydrogen cyanide (HCN) laser
interferometer, and microwave reflectometer (RFL) diagnostics for inverting the plasma electron density profile. To enhance inversion accuracy, a Gaussian prior probability of the non-stationary hyperparameter is used. This prior probability effectively simulates
situations where there is a large plasma electron density gradient in the pedestal, especially under the condition of high-confinement mode discharge. Compared to the use of Gaussian prior probability for the stationary hyperparameter, the proposed IDA
method based on the non-stationary hyperparameter prior probability achieves higher inversion accuracy.

In‐vivo evaluation of corneal collagen fibrils pattern to detect Keratoconus

Aims/Purpose: The corneal stroma, is formed by fibrous connective tissue containing collagen fibrils that are super‐organized in lamellae. In keratoconus (KC), intra‐lamellar and inter‐lamellar disrupted organization causes a progressive thinning and corneal ectasia. The LUMAXIS is a new medical device specifically designed to evaluate the effects of the interaction between polarized light and corneal stroma. It identifies the orientation of collagen fibrils in the cornea, highlighting ultrastructural changes of the tissue. The purpose of this study was to employ the LUMAXIS to discriminate changes in the pattern of corneal collagen fibrils to detect keratoconus.Methods: Patients with KC and controls were included in this prospective study. Corneal tomography (Pentacam) was acquired as well as polarimetric interferometry (LUMAXIS, Phronema S.r.l., Bari, Italy). Custom software was developed to improve the visualization of the representative cross by extracting the histogram equalized luminance to provide a numerical outcome. We then fit a set of ellipses to the image in a semi‐automatic approach, aiming to capture the boundaries of the iris, pupil, each four quadrants of the cross, and eyelids. Combining this information, we are able to obtain a cross parameter. A correlation between cross outcome and Kmax was calculated.Results: A total of sixty eyes of sixty patients were included: 30 healthy subjects (including 60 eyes, mean age of 38.0 ± 13.2 years) and 30 patients with KC (60 eyes, mean age of 39.2 ± 12.9 years). Maximum keratometry value were 59.4 ± 11.2 D in the KC group and 45.3 ± 0.8 D in the healthy group. The cross parameter was 0.41 ± 0.028 in the KC group and 0.24 ± 0.055 in the healthy group. Using only measures taken from the cross resulting from the Lumaxis scan, we were able to distinguish between KC and healthy eyes.Conclusions: The interferometric analysis of diffractive and polarizing effects related to the birefringent properties provides new morphological information at corneal fibrils level. A different corneal pattern of corneal collagen fibrils can be recognized in keratoconus patients compared to healthy patients.

Forest Height Inversion via RVoG Model and Its Uncertainties Analysis via Bayesian Framework—Comparisons of Different Wavelengths and Baselines

Accurate estimation of forest height over a large area is beneficial to reduce the uncertainty of forest carbon sink estimation, which is of great significance to the terrestrial carbon cycle, global climate change, forest resource management, and forest-related scientific research. Forest height inversion using polarimetric interferometry synthetic aperture radar (PolInSAR) data through Random volume over ground (RVoG) models has demonstrated great potential for large-area forest height mapping. However, the wavelength and baseline length used for the PolInSAR data acquisition plays an important role during the forest height estimation procedure. In this paper, X–, C–, L–, and P–band PolInSAR datasets with four different baseline lengths were simulated and applied to explore the effects of wavelength and baseline length on forest height inversion using RVoG models. Hierarchical Bayesian models developed with a likelihood function of RVoG model were developed for estimated results uncertainty quantification and decrease. Then a similar procedure was applied in the L– and P–band airborne PolInSAR datasets with three different baselines for each band. The results showed that (1) Wavelength showed obvious effects on forest height inversion results with the RVoG model. For the simulated PolInSAR datasets, the L– and P–bands performed better than the X– and C–bands. The best performance was obtained at the P–band with a baseline combination of 10 × 4 m with an absolute error of 0.05 m and an accuracy of 97%. For the airborne PolInSAR datasets, an L–band with the longest baseline of 24 m in this study showed the best performance with R2 = 0.64, RMSE = 3.32 m, and Acc. = 77.78%. (2) It is crucial to select suitable baseline lengths to obtain accurate forest height estimation results. In the four baseline combinations of simulated PolInSAR datasets, the baseline combination of 10 × 4 m both at the L– and P–bands performed best than other baseline combinations. While for the airborne PolInSAR datasets, the longest baseline in three different baselines obtained the highest accuracy at both L– and P–bands. (3) Bayesian framework is useful for estimation results uncertainty quantification and decrease. The uncertainties related to wavelength and baseline length. The uncertainties were reduced obviously at longer wavelengths and suitable baselines.

Three-Dimensional Polarimetric InISAR Imaging of Non-Cooperative Targets

A new Polarimetric Interferometry Inverse Synthetic Aperture Radar (Pol-InISAR) 3D imaging method for non-cooperative targets is proposed in this paper. 3D imaging of non-cooperative targets becomes possible by combining additional information of interferometric phase along with conventional 2D ISAR imaging. In the previously reported single-polarimetry InISAR based 3D imaging, only a single-channel based interferometric phase is available that can be exploited to reconstruct the 3D ISAR image. This limits the ability to obtain a full target's scattering response and therefore limits the estimation of an accurate interferometric phase. To overcome this constraint, full-polarimetry information is being exploited in this paper, which allows to select the optimal polarimetric combination through which the highest coherence can be obtained. A higher coherence leads to a reduction (optimally a minimization) of the phase estimation error. Consequently, with an optimal phase estimation, an accurate 3D imaging of the target is possible. To validate this proposed Pol-InISAR based 3D imaging approach, both simulated and real datasets are taken under consideration.

Miniaturized optical polarization rotator on a microfiber loop using Berry’s phase

Control of optical polarization plays a key role in various fields of optical science and engineering. Light propagating along an out-of-plane path acquires a Berry's phase, which rotates the polarization of the incident light. Herein, a miniaturized optical polarization rotator based on a microfiber loop is proposed and demonstrated with large polarization deflection angle (∼85°) with low insertion loss (∼1 dB). It operates over a wide bandwidth from 1400 nm to 1650 nm, because the Berry’s phase only depends on the optical path. Moreover, the influence of geometric structures on the performance of the microfiber-loop device, including mode cross-talk, birefringence and working bandwidth, are systematically explored. This work provides an alternative scheme to realize optical microfiber polarization rotators, which can be readily used in optical fiber sensors and polarimetric interferometry.

A New Strategy for Forest Height Estimation Using Airborne X-Band PolInSAR Data

Because the penetration depth of electromagnetic waves in forests is large in the longer wavelength band, most traditional forest height estimation methods are carried out using polarimetric interferometry synthetic aperture radar (PolInSAR) data of the L or P band, and the estimation method is a three-stage method based on the random volume over ground (RVoG) model. For X-band electromagnetic waves, the penetration depth of radar waves in forests is limited, so the traditional forest height estimation method is no longer applicable. In view of the above problems, in this paper we propose a new forest height estimation strategy for airborne X-band PolInSAR data. Firstly, the sub-view interferometric SAR pairs obtained via frequency segmentation (FS) in the Doppler domain are used to extend the polarimetric interferometry coherence coefficient (PolInCC) range of the original SAR image under different polarization states, so as to obtain the accurate ground phase. For the determination of the effective volume coherence coefficient (VCC), part of the fitting line of the extended-range PolInCC distribution that is intercepted by the fixed extinction coherence coefficient curve (FECCC) of the fixed range is averaged to obtain the accurate effective VCC. Finally, the high-precision forest canopy height in the X-band is estimated using the effective VCC with the ground phase removed in the look-up table (LUT). The effectiveness of the proposed method was verified using airborne-measured data obtained in Shaanxi Province, China. The comparison was carried out using different strategies, in which we substituted one step of the process with the conventional method. The results indicated that our new strategy could reduce the root mean square error (RMSE) of the predicted canopy height vastly to 1.02 m, with a lower estimation height error of 12.86%.

Multi-Rotor UAV-Borne PolInSAR Data Processing and Preliminary Analysis of Height Inversion in Urban Area

Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) has many useful applications, especially in forest areas. With the development of SAR miniaturization technology, researchers can install PolInSAR on small unmanned aerial vehicles (UAV), which can reduce flight costs. Limited by size and power, UAV-borne SAR usually works in a high-frequency band, which restricts its application to such things as vegetation height inversion. While on the other hand, the high resolution acquired under a short wavelength promises its application in urban areas. However, there are fewer studies on the application of PolInSAR in urban areas compared with that in forest areas. In this paper, we propose a processing method for a Ku-band multi-rotor-UAV-borne PolInSAR and provide a preliminary analysis of height inversion results on its data from the Fudan campus in Shanghai. We obtain the digital surface model (DSM) of different polarization modes and the DSM of polarimetric interferometry optimal decomposition in this area, whose RMSE is 2.88 m. On this basis, the elevation inversion results of targets such as buildings, lampposts, and trees are compared and analyzed. We preliminarily explore and analyze the reasons for the different results of different targets. To this end, we propose a mathematical derivation of the relationship between the interferometric phase between PolInSAR and InSAR of Pauli decomposition. We also perform a simulation to analyze the relationship between the phase center height of Pauli decomposition and PolInSAR under different cases. It provides a reference for the application of small UAV-borne PolInSAR in urban areas.

Theory of Radar Polarimetric Interferometry and Its Application to the Retrieval of Sea Ice Elevation in the Western Weddell Sea, Antarctic

AbstractSea ice elevation plays a crucial role in sea ice dynamic processes driven by winds and waves, for which satellite radar remote sensing becomes indispensable to monitor snow‐covered sea ice across the vast polar regions regardless of darkness and clouds. To measure sea ice elevation, a theory of polarimetric interferometry for both monostatic and bistatic radars is developed based on analytic solutions of Maxwell's equations, accounting for realistic and complicated properties of snow, sea ice, and seawater. This analytic method inherently preserves phase information that is imperative for radar polarimetry and interferometry. Among a multitude of complex radar coefficients in the general polarimetric interferometric covariance matrix, the symmetry group theory is utilized to identify and select appropriate terms pertaining to the retrieval of sea ice elevation while avoiding radar parameters that may inadvertently introduce non‐uniqueness and excessive uncertainty. Theoretical calculations compare well with field observations for rough and old sea ice encountered in the Operation‐IceBridge and TanDEM‐X Antarctic Science Campaign over the Western Weddell Sea. The results show that the magnitude of the coefficient of normalized correlation between co‐polarized horizontal and co‐polarized vertical radar returns is inversely related to sea ice elevation, while the associate phase term is nonlinear and noisy and should be excluded. From these analyses, a protocol is set up to measure Antarctic sea ice elevation to be presented in the next companion paper.

Invariants in Polarimetric Interferometry: A Non-Abelian Gauge Theory.

The discovery of magnetic fields close to the M87 black hole using very long baseline interferometry by the Event Horizon Telescope collaboration utilized the novel concept of "closure traces," that are immune to element-based aberrations. We take a fundamentally new approach to this promising tool of polarimetric very long baseline interferometry, using ideas from the geometric phase and gauge theories. The multiplicative distortion of polarized signals at the individual elements are represented as gauge transformations by general 2×2 complex matrices, so the closure traces now appear as gauge-invariant quantities. We apply this formalism to polarimetric interferometry and generalize it to any number of interferometer elements. Our approach goes beyond existing studies in the following respects: (1)we use triangular combinations of correlations as basic building blocks of invariants, (2)we use well-known symmetry properties of the Lorentz group to transparently identify a complete and independent set of invariants, and (3)we do not need autocorrelations, which are susceptible to large systematic biases, and therefore unreliable. This set contains all the information, immune to corruption, available in the interferometer measurements, thus providing important robust constraints for interferometric studies.

Invariants in copolar interferometry: An Abelian gauge theory

An $N$-element interferometer measures correlations among pairs of array elements. Closure invariants associated with closed loops among array elements are immune to multiplicative, element-based ("local") corruptions that occur in these measurements. Till recently, it has been unclear how a complete set of independent invariants can be analytically determined. We view the local, element-based corruptions in co-polar correlations as gauge tranformations belonging to the gauge group $\textrm{GL}(1,\mathbb{C})$. Closure quantities are then naturally gauge invariant. We use this to provide a simple and effective formalism, and identify the complete set of independent closure invariants from co-polar interferometric correlations using only quantities defined on $(N-1)(N-2)/2$ elementary and independent triangular loops. The $(N-1)(N-2)/2$ closure phases and $N(N-3)/2$ closure amplitudes (totaling $N^2-3N+1$ real invariants), familiar in astronomical interferometry, naturally emerge from this formalism, which unifies what has required separate treatments until now. We do not require auto-correlations, but can easily include them if reliably measured. This unified view clarifies issues relating to noise and inference of object model parameters. It also allows us to extend the rule of parallel transport associated with Pancharatnam phase in optics to apply to amplitudes as well. The framework presented here extends to $\textrm{GL}(2,\mathbb{C}$) for full polarimetric interferometry as presented in a companion paper, which generalizes and clarifies earlier work. Our findings are relevant to state of the art co-polar and full polarimetric very long baseline interferometry measurements to determine features very near the event horizons of blackholes at the centers of M87, Centaurus~A, and the Milky Way.

Volume coherence function optimization method for extracting vegetation and terrain parameters from polarimetric synthetic aperture radar interferometry images

An advanced algorithm is introduced to enhance the efficiency in measuring vegetation parameters using L-band polarimetric synthetic aperture radar interferometry data. In this method, the combination of the eigenvalue decomposition technique and the coherence matrix optimization method is to achieve higher accuracy for ground phase estimation. Then an exhaustive search method based on the optimal polarization coherence channel is developed to retrieve the forest parameters. To evaluate the effectiveness of this method, we first apply it to simulated data obtained from PolSARProSim software. Next, the experimental L-band single-baseline single-frequency polarimetric interferometric data are used to assess the applicability of the proposed method for the actual forest topography in Malaysia and Kudara, Lake Baikal, Russia. The obtained results indicate that the proposed algorithm significantly overcomes the disadvantages of the recently published methods.

Polarimetric SAR Interferometry: A Tutorial for Analyzing System Parameters

Polarimetry synthetic aperture radar (SAR) interferometry (PolInSAR) is a promising technology for globalscale forest-height mapping. Many PolInSAR space missions have been proposed or are under development. To ensure the performance of forest-height estimation, a critical study of the required system and platform parameters for the planned mission must be carried out. This involves theoretical modeling of wave scattering of the forest canopy, SAR imaging-simulation of polarimetric interferometry, implementation of a parameter-inversion algorithm, and errorbudget analysis of forest-height retrieval.

PORTAL: Three-dimensional polarized (sub)millimeter line radiative transfer

Context. Magnetic fields are important to the dynamics of many astrophysical processes and can typically be studied through polarization observations. Polarimetric interferometry capabilities of modern (sub)millimeter telescope facilities have made it possible to obtain detailed velocity resolved maps of molecular line polarization. To properly analyze these for the information they carry regarding the magnetic field, the development of adaptive three-dimensional polarized line radiative transfer models is necessary. Aims. We aim to develop an easy-to-use program to simulate the polarization maps of molecular and atomic (sub)millimeter lines in magnetized astrophysical regions, such as protostellar disks, circumstellar envelopes, or molecular clouds. Methods. By considering the local anisotropy of the radiation field as the only alignment mechanism, we can model the alignment of molecular or atomic species inside a regular line radiative transfer simulation by only making use of the converged output of this simulation. Calculations of the aligned molecular or atomic states can subsequently be used to ray trace the polarized maps of the three-dimensional simulation. Results. We present a three-dimensional radiative transfer code, POlarized Radiative Transfer Adapted to Lines (PORTAL), that can simulate the emergence of polarization in line emission through a magnetic field of arbitrary morphology. Our model can be used in stand-alone mode, assuming LTE excitation, but it is best used when processing the output of regular three-dimensional (nonpolarized) line radiative transfer modeling codes. We present the spectral polarization map of test cases of a collapsing sphere and protoplanetary disk for multiple three-dimensional magnetic field morphologies.

Forest Height Estimation Using PolInSAR Optimal Normal Matrix Constraint and Cross-Iteration Method

A novel method based on the optimal normal matrix constraint and cross-iteration algorithm is proposed in this letter to estimate the forest height using the polarimetric interferometry synthetic aperture radar (PolInSAR) data. First, to avoid the null ground-to-volume ratio assumption of the three-stage method, we use the PolInSAR optimal normal matrix constraint method to find out the pure volume coherence. This method can also provide a more accurate initial value for the least-squares iteration. Second, the cross-iteration is used for the forest height inversion, which provides better selection of the best polarization channel and solves the ill-conditioned matrix in the traditional least-squares iteration algorithm. This new method is validated using the BioSAR 2008 P-band data. The results show that the proposed method achieves an average accuracy of 2.6 m, which is better than that of the three-stage inversion method [root-mean-square error (RMSE) = 5.89 m] and the 6-D nonlinear iteration method (RMSE = 4.42 m).

A new algorithm for forest height estimation based on the varied extinction random volume over ground (VERVoG) model using PolInSAR data

ABSTRACT This paper examines a simple geometrical method for forest height estimation using single-baseline single frequency polarimetric synthetic aperture radar interferometry (PolInSAR) data. The suggested method estimates the forest biophysical parameters based on the varied extinction random volume over ground (VERVoG) model with top layer extinction greater than zero. We approach the problem using a geometrical method without the need for any auxiliary data or prior information. The biophysical parameters, i.e. top layer extinction value, forest height and extinction gradient are estimated in two separate stages. In this framework, the offset value of the extinction is estimated in an independent procedure as a function of a geometrical index based on the signal penetration in the volume layer. As a result, two remaining biophysical parameters can be calculated in a geometrical way based on the observed volume coherence. The proposed algorithm was evaluated using the L-band PolInSAR data of the European Space Agency (ESA) BioSAR 2007 campaign. A pair of experimental SAR (ESAR) images was acquired over the Remningstorp test site in southern Sweden. The selected images were employed for the performance analysis of the proposed approach in the forest height estimation application based on the VERVoG model. The experimental result shows that the proposed inversion method based on the VERVoG model with top layer extinction greater than zero estimates the volume height with an average root mean square error (RMSE) of 2.08 m against light detection and ranging (LiDAR) heights. It presents a significant improvement of forest height accuracy, i.e. 4.1 m compared to the constant extinction RVoG model result, which ignores the forest heterogeneity in the vertical direction.

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

The primary objective of the European Space Agency's 7th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where “global” is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR L- and S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations needed for ionospheric correction of the data will allow very sensitive estimates of ionospheric Total Electron Content and its changes along the dawn-dusk orbit of the mission.

Pol-InSAR for Forest Biomass Estimation with the Transformation of the Polarization Basis

An improved method that uses polarimetric and Pol-InSAR information at the L-band and P-band was proposed in this study for estimating forest biomass. In the first phase, various polarimetric and polarimetric interferometry indicators were extracted via transformation of the polarization basis. In the second phase, the particle swarm optimization method is applied to identify optimal parameter values for biomass estimation. According to the results, the correlations between the polarimetric indicators and the biomass were stronger at the P-band compared to the L-band. Polarimetric indicators that involve HV and HH–VV show the maximum correlation with biomass prior to optimization. It is demonstrated that changing the polarization basis can significantly improve the correlations of estimators with the biomass, especially at the P-band. The globally optimal estimators involve the same scattering mechanisms (volume and double-bounce scattering), and the optimal polarization bases differ slightly among most of the cases, due to the adaptation to the forest natural geometry and/or the acquisition configuration. Regarding Pol-InSAR, several tree height retrieval estimators that are based on various assumptions have been analyzed under multiple polarization basis rotations. According to the results, the RVoG phase method, which represents the forest as a low-extinction structured volume, yielded the best accuracy, with R = 0.73 and RMSE = 4.30 m. The identification of the optimum polarization indicators via binary PSO could improve the biomass estimation accuracy by 2% and 6% at the P-band and L-band, respectively. It is demonstrated that such an approach can be employed to accurately estimate biomass via extrapolation of in situ measurements over an entire region.

Differential speckle polarimetry at Cassegrain and Nasmyth foci

Polarimetric interferometry is a method allowing the study of the distribution of polarized flux at diffraction-limited resolution. Its basic observable is the ratio $\mathcal{R}$ of the visibilities of the object in two orthogonal polarizations. Here, we demonstrate how this observables can be measured with the SPeckle Polarimeter (SPP) of the 2.5-m telescope. The SPP is a combination of a dual-beam polarimeter and an EMCCD-based visible-range speckle interferometer. We propose a simple method for the correction of $\mathcal{R}$ for the instrumental polarization and polarization differential aberrations of the telescope. The polarized intensity image can be estimated from $\mathcal{R}$ under the assumption that the object is a point-like unpolarized source plus a faint extended polarized envelope. The phase of $\mathcal{R}$ can be used for measurement of the polaroastrometric signal - the difference between the photocentres of orthogonally polarized images of the object. We investigate both possibilities using observations of unpolarized stars and stars with a significant polarized circumstellar environment - $\mu$~Cep and RY~Tau.

An improved adaptive decomposition method for forest parameters estimation using polarimetric SAR interferometry image

ABSTRACT Forest parameters estimation using polarimetric synthetic aperture radar interferometry (PolInSAR) images is one of the greatest interests in remote sensing applications. Applying the model-based decomposition concept to PolInSAR data opened a new way for forest parameters estimation. However, the method tends to underestimate the forest height due to reflection symmetry assumption and required the numerical solution of nonlinear equation system. In order to overcome these limitations, an improved adaptive decomposition technique with PolInSAR data is proposed. In this approach, an accurate topographical phase and asymmetry volume scattering model are applied to the model-based decomposition technique for polarimetric SAR interferometry image. The accurate topographical phase is first estimated and then used as the initial input parameter to our numerical method. This approach is not only avoiding large error generated by the constant topographical phase in fluctuating forest areas but also improve the accuracy of forest height estimation and the magnitude associated with each mechanism. The performance of proposed method is demonstrated with simulated data from PolSARproSim software and SIR-C/X-SAR spaceborne PolInSAR images over the Tien-Shan areas, China. Experimental results indicate that forest parameters could be effectively extracted by proposed method.

Real-Time Polarimetric Optical High-Voltage Sensor Using Phase-Controlled Demodulation

Modern smart grid designs demand reliable sensors throughout the power delivery systems, not only to monitor the quality of the electrical energy generated by different technologies (wind, solar, hydroelectric, thermoelectric, nuclear), but also as an integral part of the generation, transmission, and distribution networks control systems. Laser polarimetric interferometry is a very suitable technique for the implementation of high sensitivity measurement instruments for various physical quantities, in particular, for high-voltage sensing. However, because the polarimetric technique is extremely sensitive to small refractive indexes variations induced in electro-optic materials by the electric field or voltage to be measured, it is also sensitive to spurious environmental quantities such as temperature variations. In this work, a novel optical voltage sensor (OVS) in conjunction with an efficient real-time method for optical phase demodulation and a PI feedback control method for signal fading suppression is demonstrated. Linearity for sinusoidal voltages having amplitudes up to 8.2 kV was evaluated, with an accuracy of 0.2% in the OVS nominal operating range. The OVS bandwidth of 5 kHz is sufficient for most electrical power quality sensor applications. Nonsinusoidal signals with high harmonic content were tested resulting in a total harmonic distortion that differed by only 0.12% from that measured by an HV reference probe. Responses to transient disturbances were also determined, showing the capability of the system to detect spikes.