Search Results (89)

Polarimetric radar systems play a crucial role in enhancing microwave remote sensing and target identification by providing a refined understanding of electromagnetic scattering mechanisms. This study introduces the concept of polarization scattering regions as a novel tool for describing the polarization characteristics across three spectral regions: the polarization Rayleigh region, the polarization resonance region, and the polarization optical region. By using ellipsoidal models, we simulate and analyze scattering across varying electrical sizes, demonstrating how these sizes influence polarization characteristics. The research leverages Cameron decomposition to reveal the distinctive scattering behaviors within each region, illustrating that at higher-frequency bands, scattering approximates spherical symmetry, with minimal impact from the target shape. This classification provides a comprehensive view of polarization-based radar cross-section regions, expanding upon traditional single-polarization radar cross-section regions. The results show that polarization scattering regions are practical tools for interpreting polarimetric radar data across diverse frequency bands. The applications of this research in radar target recognition, weather radar calibration, and radar polarimetry are discussed, highlighting the importance of frequency selection for accurately capturing polarization scattering features. These findings have significant implications for advancing weather radar technology and target recognition techniques, particularly as radar systems move towards higher frequency bands. Full article

Quad-polarization synthetic aperture radar (SAR) satellites are important detection tools in Earth observation and remote sensing; in particular, they are of great significance for accurately interpreting radar data and inverting geophysical parameters. Polarimetric calibration is particularly critical to eliminate the effects of distortion in polarized SAR data. The C-SAR/02 satellite launched by China is an important part of the C-band synthetic aperture radar (SAR) constellation, and the quad-polarization strip I (QPSI) is an important imaging mode for its sea–land observation. The relevant research on its polarimetric calibration is still lacking. This study’s polarimetric calibration of C-SAR/02 was performed based on the active radar calibrator (ARC) method using four independently developed L/S/C multi-band ARCs and several trihedral corner reflectors (CRs). The polarimetric calibration distortion matrix varies along the range direction; the polarimetric calibration distortion matrix and polarimetric calibration accuracy along the range direction were analyzed, incorporating the devices in different range directions to calculate the distortion matrix. This approach improved the accuracy of the polarimetric calibration results and the effect of the quantization application of the C-SAR satellites. Moreover, our experimental results indicate that the method presented herein is suitable for the C-SAR/02 satellite and may also be more universally applicable to C-SAR-series satellites. Full article

To solve the problems of channel crosstalk and edge jitter caused by the Fourier transform demodulation of polarimetric-spectral intensity modulation in polarization spectral data, this paper proposes a Four-Channel Polarimetric Spectrometer (FCPS) with two groups of polarimetric-spectral intensity modulation (PSIM). FCPS can demodulate the full Stokes spectra information by system matrix calibration in the spatial domain. The traditional channel filtering method and the FCPS data demodulation method are simulated, and their results are compared. The simulated results show that the FCPS does not have the problem of the edge jitter, and the demodulation accuracy is higher. It is confirmed that the angle error of phase retarders has little influence on the data reconstruction, and the maximum allowable angle error of the calibration light linear polarizer cannot exceed 0.4°. Full article

Grazing lands are crucial for agricultural productivity, ecological stability, and carbon sequestration, underscoring the importance of monitoring vegetation biomass for the effective management of these ecosystems. Remote sensing data, including optical vegetation indices (VIs) like the Normalized Difference Vegetation Index (NDVI), are widely used to monitor vegetation dynamics due to their simplicity and high sensitivity. In contrast, radar-based VIs, such as the Polarimetric Radar Vegetation Index (PRVI), offer additional advantages, including all-weather imaging capabilities, a wider saturation range, and sensitivity to the vegetation structure information. This study introduces an enhanced form of the PRVI, termed the Normalized PRVI (NPRVI), which is calibrated to a 0 to 1 range, constraining the minimum value to reduce the background effects. The calibration and range factor were derived from statistical analysis of PRVI components across vegetated regions in the Contiguous United States (CONUS), using dual-polarization C-band Sentinel-1 and L-band ALOS-PALSAR data on the Google Earth Engine (GEE) platform. Machine learning models using NPRVI and NDVI demonstrated their complementarity with annual herbaceous biomass data from the Rangeland Analysis Platform. The results showed that the Random Forest Model outperformed the other machine learning models tested, achieving R² ≈ 0.51 and MAE ≈ 498 kg/ha (relative MAE ≈ 32.1%). Integrating NPRVI with NDVI improved biomass estimation accuracy by approximately 10% compared to using NDVI alone, highlighting the added value of incorporating radar-based vegetation indices. NPRVI may enhance the monitoring of grazing lands with relatively low biomass compared to other vegetation types, while also demonstrating applicability across a broad range of biomass levels and in diverse vegetation covers. Full article

Bistatic and multistatic SAR technology, with its multi-dimensional, ultra-wide swath, and high-resolution advantages, is widely used in earth observation, military reconnaissance, deep space exploration, and other fields. The LuTan-1 (LT-1) mission employs two full-polarimetric L-band SAR satellites for the BiSAR system. The bistatic mode introduces phase errors in echo reception paths due to different transmission links, making echo compensation a key factor in ensuring BiSAR performance. This paper proposes a novel bistatic internal calibration strategy that combines ground temperature compensation, in-orbit internal calibration, and pulsed alternate synchronization to achieve echo compensation. Prior to launch, temperature compensation data for the internal calibration system are obtained via temperature experiments. During in-orbit operation, calibration data are acquired by executing the internal calibration pulse sequence and noninterrupted pulsed alternate synchronization. In ground processing, echo compensation is completed based on the above two parts of calibration data. A comprehensive analysis of the entire calibration chain reveals a temperature compensation accuracy of 0.10 dB/1.38°. Additionally, a ground verification system is established to conduct BiSAR experiments, achieving a phase synchronization accuracy of 0.16°. Furthermore, the in-orbit test obtained DSM products with an average error of 1.3 m. This strategy provides a valuable reference for future spaceborne bistatic and multistatic SAR systems. Full article

Soil moisture is one of the main factors affecting microwave radar backscatter from the ground. While there are other factors that affect backscatter levels (for instance, surface roughness, vegetation, and incident angle), relative variations in soil moisture can be estimated using space-based, medium resolution, multi-temporal synthetic aperture radar (SAR). Understanding the distribution and identification of water-saturated areas using SAR soil moisture can be important for wetland mapping. The SAR soil moisture retrieval algorithm provides a relative assessment and requires calibration over wet and dry periods. In this work, relative soil moisture indicators are derived from a time series of the RADARSAT Constellation Mission (RCM) SAR compact polarimetric (CP) data over reclaimed areas of an oil sands mine in Alberta, Canada. An evaluation of the soil moisture product is performed using in situ measurements showing agreement from June to September. The surface scattering component of m-chi CP decomposition and the RL SAR products demonstrated a good agreement with the field data (low RMSE values and a perfect alignment with field-identified wetlands). Full article

To date, various methods have been proposed for calibrating polarimetric synthetic aperture radar (SAR) using distributed targets. Some studies have utilized the covariance matching estimation technique (Comet) for SAR data calibration. However, practical applications have revealed issues stemming from ill-conditioned problems due to the analytical solution in the iterative process. To tackle this challenge, an improved method called Comet IS is introduced. Firstly, we introduce an outlier detection mechanism which is based on the Quegan algorithm’s results. Next, we incorporate an initial search approach which is based on the interior point method for recalibration. With the outlier detection mechanism in place, the algorithm can recalibrate iteratively until the results are correct. Simulation experiments reveal that the improved algorithm outperforms the original one. Furthermore, we compare the improved method with Quegan and Ainsworth algorithms, demonstrating its superior performance in calibration. Furthermore, we validate our method’s advancement using real data and corner reflectors. Compared with the other two algorithms, the improved performance in crosstalk isolation and channel imbalance is significant. This research provides a more reliable and effective approach for polarimetric SAR calibration, which is significant for enhancing SAR imaging quality. Full article

The GaoFen (GF)-5-02 satellite is one of the new generations of hyperspectral observation satellites launched by China in 2021. The directional polarimetric camera (DPC) is an optical sensor onboard the GF-5-02 satellite. The precipitable water vapor (PWV) is a key detection parameter of DPC. However, the existing PWV data developed using DPC data have significant errors due to the lack of the timely calibration of the two bands (865, 910 nm) of DPC used for PWV retrieval. In order to acquire DPC PWV data with smaller errors, a calibration method is developed for these two bands. The method consists of two parts: (1) calibrate the 865 nm band of the DPC using the cross-calibration method, (2) calibrate the 910 nm band of the DPC according to the calibrated 865 nm band of the DPC. This method effectively addresses the issue of the absence of a calibration method for the water vapor absorption band (910 nm) of the DPC. Regardless of whether AERONET PWV data or SuomiNET PWV data are used as the reference data, the accuracy of the DPC PWV data developed using calibrated DPC data is significantly superior to that of the DPC PWV data retrieved using data before recalibration. This means that the calibration method for the NIR bands of the DPC can effectively enhance the quality of DPC PWV data. Full article

The unique P-band synthetic aperture radar (SAR) instrument, BIOMASS, is scheduled for launch in 2024. This satellite will enhance the estimation of subcanopy topography, owing to its strong penetration and fully polarimetric observation capability. In order to conduct global-scale mapping of the subcanopy topography, it is crucial to calibrate systematic errors of different strips through interferometric SAR (InSAR) DEM (digital elevation model) block adjustment. Furthermore, the BIOMASS mission will operate in repeat-pass interferometric mode, facing the atmospheric delay errors introduced by changes in atmospheric conditions. However, the existing block adjustment methods aim to calibrate systematic errors in bistatic mode, which can avoid possible errors from atmospheric effects through interferometry. Therefore, there is still a lack of systematic error calibration methods under the interference of atmospheric effects. To address this issue, we propose a block adjustment model considering atmospheric effects. Our model begins by employing the sub-aperture decomposition technique to form forward-looking and backward-looking interferograms, then multi-resolution weighted correlation analysis based on sub-aperture interferograms (SA-MRWCA) is utilized to detect atmospheric delay errors. Subsequently, the block adjustment model considering atmospheric effects can be established based on the SA-MRWCA. Finally, we use robust Helmert variance component estimation (RHVCE) to build the posterior stochastic model to improve parameter estimation accuracy. Due to the lack of spaceborne P-band data, this paper utilized L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR data, which is also long-wavelength, to emulate systematic error calibration of the BIOMASS mission. We chose climatically diverse inland regions of Asia and the coastal regions of South America to assess the model’s effectiveness. The results show that the proposed block adjustment model considering atmospheric effects improved accuracy by 72.2% in the inland test site, with root mean square error (RMSE) decreasing from 10.85 m to 3.02 m. Moreover, the accuracy in the coastal test site improved by 80.2%, with RMSE decreasing from 16.19 m to 3.22 m. Full article

The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design. Full article

The synthetic aperture radar (SAR) is a type of active radar that can obtain polarization scattering information of ground objects, which is an important supplement to optical remote sensing. This paper designs a high-precision quantitative SAR system that combines radiation and polarization calibration processing to achieve a subtle perception of the changes in soil moisture and straw coverage. In Yushu, Jilin, we conducted the first S-band agricultural remote sensing application experiment. The backscattering coefficient was measured under different water content and straw coverage conditions, and the results showed that the backscattering coefficient increased by about 2 dB and 6 dB, respectively. We estimated that the soil water content increased by about 0.01 cm³/cm³, which was consistent with the theoretical analysis. The polarization scattering characteristics also showed significant differences under different straw coverage. The results indicated that S-band quantitative SAR had an excellent response ability to water content and straw coverage, which provided a technical basis for further radar agricultural applications in the future. Full article

A polarization analysis method based on a multi-parameter model is proposed to address the polarization effect analysis and calibration requirements of a dual-coded snapshot spectral polarization imaging system. A full-link polarization effect model for a spectral polarization imaging system is established that includes a digital micromirror array (DMD), prism grating prism (PGP), micro-polarizer array detector (MPA), and multi-film. The influence of parameters such as the refractive index, incident angle, grating refractive index, constant, prism refractive index, vertex angle, multi-layer film complex refractive index, and film thickness on the optical transmittance of the system are analyzed. Using a dynamic data exchange mechanism to perform full-link, full-FOV, and full-pupil ray tracing on the optical system, the polarization effect distribution of the system under different degrees of polarization (DOP) and wavelengths is obtained. A calibration experiment for the controllable incident wavelength and DOP using narrowband filters and glass stacks is established. The experimental results show that in the 420 nm, 532 nm, and 635 nm wavelength bands, the MSEs of the calibrated values are 1.3924 × 10⁻⁴, 1.6852 × 10⁻⁴, and 1.6735 × 10⁻⁴, respectively. It is proven that the calibration method based on a multi-parameter model is feasible. Finally, the spectral polarization image at 532 nm is calibrated. The contrast ratio of metallic aluminum is calibrated from 7.13 to 15.33. This study provides a theoretical basis for the analysis and calibration of polarization effects in a dual-coded snapshot spectral polarization imaging system. Full article

Understanding the characteristics of the raindrop size distribution (DSD) is crucial to improve our knowledge of the microphysical processes of precipitation and to improve the accuracy of radar quantitative precipitation estimation (QPE). In this study, the spatial variability of DSD in different regions of Beijing and its influence on radar QPE are analyzed using 11 disdrometers. The DSD data are categorized into three regions: Urban, suburban, and mountainous according to their locations. The DSD exhibits evidently different characteristics in the urban, suburban, and mountain regions of Beijing. The average raindrop diameter is smaller in the urban region compared to the suburban region. The average rain rate and raindrop number concentration are lower in the mountainous region compared to both urban and suburban regions. The difference in DSD between urban and suburban regions is due to the difference in DSD for the same precipitation types, while the difference in DSD between mountain and plains (i.e., urban and suburban regions) is the combined effect of the convection/stratiform ratio and the difference of DSD for the same precipitation types. Three DSD-based polarimetric radar QPE estimators were retrieved and estimated. Among these three QPE estimators, R(Z_H), R(K_dp), and R(K_dp, Z_DR), R(K_dp, Z_DR) performs best, followed by R(K_dp), and R(Z_H) performs worst. R(K_dp) is more sensitive to the representative parameters, while R(Z_H) and R(K_dp, Z_DR) are more sensitive to observational error and systematic bias (i.e., calibration). Full article

The L-band geosynchronous synthetic aperture radar (GEO-SAR) has been widely praised for its advantages of short revisit time, wide coverage and stable backscattering information acquisition. However, due to the ultra-long integrated time, the echo will be affected by the time-variant background ionosphere, leading in particular to defocusing in the azimuth direction. Existing compensation methods suitable for low Earth orbit SAR (LEO-SAR) are based on the SAR image or the semi-focused image at the ionospheric phase screen, assuming that the ionosphere is time-frozen for a short integrated period; thus, accurate reconstruction of the time-variant characteristics for the ionosphere in GEO-SAR cannot be achieved. In this paper, a compensation method of background ionospheric effects on L-band GEO-SAR with fully polarimetric data is proposed. Considering the continuous variation of the ionosphere within the synthetic aperture, a decompression processing is proposed to reconstruct the echo by recovering the temporal sampling according to the imaging geometry. By virtue of the Faraday rotation angle, the time-variant total electron content (TEC) is accurately estimated with the reconstructed echo. Based on the established error model, the ionospheric effects are well compensated with the estimated TEC. Simulations with the real SAR data from ALOS-2 and the measured time-variant TEC from USTEC validate the effectiveness and performance of the proposed method. The impacts from thermal noise and polarimetric calibration error are also quantitatively analyzed. From this, the error thresholds are given to guarantee compensation accuracy, namely 18.96 dB for SNR, −15.63 dB for crosstalk and −1.02 dB to 0.31 dB for the amplitude of the channel imbalance, and the argument of the channel imbalance is suggested to be maintained as close to zero as possible. Full article

This study is aimed at the design, calibration, and development of a near-infrared (NIR) liquid crystal multifunctional automated optical polarimeter, which is aimed at the study and characterization of the polarimetric properties of polymer optical nanofilms. The characterization of these novel nanophotonic structures has been achieved, in terms of Mueller matrix and Stokes parameter analyses. The nanophotonic structures of this study consisted of (a) a matrix consisting of two different polymer domains, namely polybutadiene (PB) and polystyrene (PS), functionalized with gold nanoparticles; (b) cast and annealed Poly (styrene-b-methyl methacrylate) (PS-PMMA) diblock copolymers; (c) a matrix of a block copolymer (BCP) domain, PS-b-PMMA or Poly (styrene-block-methy methacrylate), functionalized with gold nanoparticles; and (d) different thicknesses of PS-b-P2VP diblock copolymer functionalized with gold nanoparticles. In all cases, backscattered infrared light was studied and related to the polarization figures-of-merit (FOM). The outcome of this study indicates that functionalized polymer nanomaterials, depending upon their structure and composition, exhibit promising optical characteristics, modulating and manipulating the polarimetric properties of light. The fabrication of technologically useful, tunable, conjugated polymer blends with an optimized refractive index, shape, size, spatial orientation, and arrangement would lead to the development of new nanoantennas and metasurfaces. Full article