Yinan Li

The fully polarimetric aperture synthesis radiometer (FPASR) is capable of acquiring the fully polarimetric brightness temperature (BT), which has become increasingly significant in remote sensing. Antenna pattern errors can introduce significant errors to the reconstructed image of the FPASR. Analyzing and correcting the antenna pattern errors is crucial for obtaining high-quality BT images. In this paper, the antenna pattern errors are analyzed and classified into additive and multiplicative errors. A two-step correction method is proposed to reduce the influence of antenna pattern errors on the reconstructed BT. An end-to-end simulator for FPASR has been developed to assess both the antenna pattern errors and the effectiveness of the correction method. The simulation results show that the two-step correction method can reduce the brightness temperature error caused by the antenna pattern errors by over 70%. The successful image of the flight experiment validates the correction method as well.

Correction for the impact of direct Sun contamination is a crucial task in the data processing of interferometric microwave radiometer (IMR). The evident presence of solar radiation is observed in the brightness temperature images derived from the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) payload onboard the Soil Moisture and Ocean Salinity (SMOS) satellite, significantly impacting the data quality to retrieve sea surface salinity. This paper introduces a novel sinusoid correction method for correcting the direct Sun contamination. By leveraging the characteristics of the solar disk, the proposed method simulates and compensates for the contribution of direct solar impact in the spatial frequency domain based on the response pattern of small point sources within the solar disk. The proposed method exhibits a reduced dependency on the precise solar position information and demonstrates resistance to radio frequency interference, and validations through a simulated IMR and data from in-orbit SMOS confirm the reduction of the direct solar impact in brightness temperature images. The proposed sinusoid correction method outperforms the single and multiple source methods, used in the SMOS operational data processing, especially for the central regions around the location of direct Sun.

The Airborne Terahertz Ice Cloud Imager (ATICI) is an airborne demonstration prototype of an ice cloud imager (ICI), which will be launched on the next generation of Fengyun satellites and plays an important role in heavy precipitation detection, typhoon, and medium-to-short-term meteorological/ocean forecasting. At present, it has 13 frequency channels covering 183–664 GHz, which are sensitive to scattering by cloud ice. This paper provides an overview of ATICI and proposes a receiving front-end design scheme using a planar mirror and a quasi-optical feed network which improves the main beam efficiency of each frequency band, with measured values better than 95.5%. It can detect factors such as ice particle size, ice water path, and ice water content in clouds by rotating the circular scanning of the antenna feed system. A high-sensitivity receiver system has been developed and tested for verification. The flight verification results show that the quasi-optical feed network subsystem works well and performs stably under vibration and temperature changes. The system sensitivity is better than 1.5 K, and the domestically produced high-frequency receiver has stable performance, which can meet the conditions of satellite applications. The ATICI performs well and meets expectations, verifying the feasibility of the Fengyun-5 ICI payload.

For synthetic aperture microwave radiometers, the problem of Radio Frequency Interference (RFI) is becoming more and more serious, which affects both the scientific retrieval of remote sensing data and the imaging quality of brightness temperature (BT) images. In the visibility data domain, the array factor synthesis algorithm is commonly employed to mitigate RFI sources and their Gibbs trailing. In the BT image domain, the CLEAN algorithm is typical applied to mitigate RFI sources and their Gibbs trailing. However, the array factor synthesis algorithm can result in anomalous BT points near the “zero trap” region, and the CLEAN algorithm will miss some BT points below a certain threshold. In this paper, a Bi-domain combined mitigation algorithm is proposed to mitigate RFI sources and their Gibbs trailing. Following initial mitigation in the visibility data domain, dual thresholds are applied to normalize anomalous BT points near the “zero trap” region, thereby enhancing imaging quality. The effectiveness of the Bi-domain combined mitigation algorithm is verified by using both measured data from SMOS L1A and simulated data. The experimental results demonstrate that the Bi-domain combined mitigation algorithm is superior to the array factor synthesis algorithm and the CLEAN algorithm in mitigating RFI sources and their Gibbs trailing.

For an aperture synthesis radiometer (ASR), the visibility and the modified brightness temperature (BT) are related to the Fourier transform when the distance between the system and the source is in the far-field region. BT reconstruction can be achieved using G-matrix imaging. However, for ASRs with large array sizes, the far-field condition is not satisfied when performing performance tests in an anechoic chamber due to size limitations. Using far-field imaging methods in near-field conditions can introduce errors in the images and fail to correctly reconstruct the BT. Most of the existing methods deal with visibilities, converting near-field visibilities to far-field visibilities, which are suitable for point sources but not good for extended source correction. In this paper, two near-field imaging methods are proposed based on the near-field distance. These methods enable BT reconstruction in near-field conditions by generating improved resolving matrices: the near-field G-matrix and the F-matrix. These methods do not change the visibility measurements and can effectively image both the point source and the extended source in the near field. Simulations of point sources and extended sources in near-field conditions demonstrate the effectiveness of both methods, with F-matrix imaging outperforming near-field G-matrix imaging. The feasibility of both near-field imaging methods is further validated by carrying out experiments on a 10-element Y-array system.

Unlike the traditional multi-channel synthetic aperture radar (SAR) three-dimensional (3-D) reconstruction technology, the single-channel SAR with two synthetic apertures in the vertical and horizontal planes, realized by curved trajectory, has advantages of requiring less acquisition data, lower device cost, and fewer limitations on trajectories. However, due to the complex aerodynamic configuration and flight characteristics, critical challenges are faced including the mathematical model establishment, signal property analyses and reconstruction approach design. In this paper, to address these issues, a 3-D vector geometry model of curvilinear SAR (CLSAR) system is presented and its properties, including elevation bandwidth and resolution, are studied in detail. Then, a novel 3-D reconstruction approach for single-channel CLSAR system based on azimuth pre-focusing is presented, in which the cylindrical symmetry of SAR system is utilized to provide accurate azimuth information of targets in observing scene. With the assisted azimuths, the scene imaged in vertical plane can be performed, and the 3-D reconstruction of interested targets can be obtained. Numerical results using simulated data demonstrate the effectiveness of the proposed approach.

This study develops a new sea surface temperature (SST) retrieval algorithm based on statistical regression that utilizes WindSat satellite data and in-situ SST Quality Monitor (iQuam) buoy data. The proposed algorithm introduces new rules to remove abnormal brightness temperatures (TB) due to land, sea ice, radio frequency interference (RFI), and sun glint. Besides, SST data from 2019 to 2022 are generated from the HY-2B satellite’s Scanning Microwave Radiometer (SMR) using a two-step retrieval method. Our study reveals that wind speed, cloud liquid water, and wind direction have significant crosstalk effects on SST retrieval, which increases exponentially when the cloud liquid water exceeds 0.1mm. The crosstalk effect can be significantly reduced by incorporating wind speed fitting in the SST retrieval algorithm. By fitting iQuam SST data, the multiple localizing sea surface wind speed (WS) and latitude algorithms are developed, significantly reducing the impact of crosstalk parameters on SST retrieval and improving the SST retrieval accuracy. And the algorithm also performed well in correcting the non-linear response of TB and SST. The results reveal that the retrieval algorithm eliminates bias across different wind speeds, water vapor, and cloud liquid water ranges and performs consistently on ascending and descending orbits. The overall bias of the SMR 4-year SST product is -0.004°C, with a standard deviation of 0.588 °C, posing a substantial improvement over the existing product with a bias of -0.022C and a standard deviation of 0.803°C. Moreover, the 4-year fluctuation of standard deviation is very small, indicating excellent stability of the retrieval algorithm.

Airborne synthetic aperture radar (SAR) is susceptible to atmospheric disturbance and other factors that cause the position offset error of the antenna phase center and motion error. In close-range detection scenarios, the large elevation angle may make it impossible to directly observe areas near the underlying plane, resulting in observation blind spots. In cases where the illumination elevation angle is extremely large, the influence of range variant envelope error and phase modulations becomes more serious, and traditional two-step motion compensation (MOCO) methods may fail to provide accurate imaging. In addition, conventional phase gradient autofocus (PGA) algorithms suffer from reduced performance in scenes with few strong scattering points. To address these practical challenges, we propose an improved phase-weighted estimation PGA algorithm that analyzes the motion error of UAV SAR under a large elevation angle, providing a solution for high-order range variant motion error. Based on this algorithm, we introduce a combined focusing method that applies a threshold value for selection and optimization. Unlike traditional MOCO methods, our proposed method can more accurately compensate for spatially variant motion error in the case of scenes with few strong scattering points, indicating its wider applicability. The effectiveness of our proposed approach is verified by simulation and real data experimental results.

In mirrored aperture synthesis (MAS), the antenna array determines the rank of the transformation matrix connecting the cross-correlations to the cosine visibilities. However, the transformation matrix is rank-deficient, resulting in errors in the reconstructed brightness temperature (BT) image. In this paper, the signal propagations for the vertically polarized wave and horizontally polarized wave are analyzed. Then, the optimization model of the antenna array based on dual-polarization is established. The optimal array configurations are presented, with the corresponding transformation matrices being almost column full ranks. Simulation results demonstrate the validity of the proposed optimization model.

The medium- and large- scale global sea surface temperature (SSTs), which is an important ocean parameter, are mainly measured by the space-borne microwave radiometry. However, the resolution and sensitivity are greatly limited by antenna size, orbit altitude, and flight speed. In this paper, an airborne C-band one-dimensional (1-D) microwave interferometric radiometer (ACMIR) is developed to obtain the SSTs with a high resolution and sensitivity. The spatial resolution of the ACMIR ranges from 40.7m to 612m, corresponding to the flight height of 500m to 8000m, while the sensitivity varies from 0.25K to 0.36K, associating with the boresight to the edge of the field of view. In order to evaluate the performance of the ACMIR, an ocean aviation experiment was conducted in the coastal area of the Yellow Sea in September 2020. The land observation results indicate that typical ground objects can be clearly distinguished. Furthermore, thesea surface brightness temperatures acquired by the ACMIR are compared with the estimates based on the radiative transfer model, with SST retrieval error of 0.77°C. The ACMIR can offer a high-resolution and accuracy of SST especially in coastal areas, and can meet several application requirements related to SSTs.