SAR radiometric calibration is an essential step in inferring meaningful physical information about the target. The majority of current calibration processes are directly based on artificial calibrators, but the number of calibrators is always restricted. Cross calibration, which has been widely used for optical and meteorological satellites, performs calibration by another calibrated satellite. Distributed targets are used as the calibration reference, allowing for frequent calibration. However, the potential of introducing cross calibration to SAR satellites has not been confirmed, and two issues must be resolved: 1) The number of calibration targets available for cross calibration is limited to a few known distributed targets; 2) The imaging parameters of calibrated and uncalibrated SARs are different, which may cause errors when cross calibration is applied. In this paper, a method for selecting stable distributed targets using time-series stability analysis was presented firstly. The saline-alkali land and urban areas were selected as the calibration targets with low and high backscattering, respectively. Second, different stable pixel extraction methods were adopt based on the characteristics of different targets. Thirdly, the Oh model was used to correct the scattering difference caused by the incidence angle difference, which greatly improved the accuracy of the backscattering coefficients of the calibration targets. The cross calibration experiments on the same series of satellite (Sentinel-1A/B) data revealed that the accuracy of cross calibration was comparable to the accuracy of the artificial calibrator-based method, with a difference of less than 0.48 dB (1 $\sigma$ ).

This paper presents the first bistatic Synthetic Aperture Radar (SAR) Moon imaging experiment based on the Five-hundred-meter Aperture Spherical radio Telescope (FAST) and the Sanya Incoherent Scatter Radar (SYISR). We obtain 430 MHz radar images of the Moon surface and the highest resolution of the images reaches 560 m × 630 m. The wide-range and high-resolution images lay a solid foundation for related scientific research. Because FAST lacks the ability to actively transmit signals, SYISR is chosen as the transmitting radar. To mitigate the north-south ambiguity, we alternately image Moon surface areas by controlling the pointing direction of FAST in experiments. The bistatic SAR system brings more system errors compared to the monostatic SAR system. To cope with complex system errors, an error analysis method based on echo characteristics is introduced. The core of this analysis method lies in combining error analysis and compensation with the imaging process, using the imaging results and the changes in echoes to calibrate the errors. This method effectively identifies the source of errors exceeding the range gate and enables FAST to flexibly form a bistatic SAR system with any radar without special hardware modifications. For system errors with less impact, an improved phase gradient autofocus technique is introduced, which can mitigate residual unknown component phase errors in the echo. Additionally, in order to image non-ephemeris targets based on FAST such as asteroids, an ephemeris-independent imaging method is introduced and tested with the Moon as the imaging target, which achieved imaging results comparable to that of conventional methods. Finally, mosaic images of Earthside Moon are obtained. The results validate the reliability of the error analysis method and the imaging technique, as well as the feasibility of FAST imaging the celestial bodies, laying the foundation for FAST to cooperate with other radars to conduct a wider range of deep space targets imaging tasks and scientific exploration.

High-resolution wind vector is important to investigate local winds’ variability over the global ocean. Quad-polarization Synthetic Aperture Radar (SAR) can provide wind vector independently without any external wind direction inputs. Although quad-polarization SAR wind retrieval algorithms have been widely studied, improvements are still required. The amplitude and phase imbalance of polarization channel cannot be neglected for improving the wind vector retrieval precision. In this study, rainforest was performed to remove the amplitude and phase imbalance of polarization channel of GF-3 SAR. To explore the applicability of this method for sea surface measurement, the influence of residual amplitude and phase error for GF-3 quad-polarization SAR on wind vector retrieval was assessed. Variation of amplitude and phase imbalance of sea surface for transmit and receive channel were assessed against collocated wind speed and incidence angle. Considering the polarization difference of VV channel relative to HH channel, the residual amplitude and phase error was found to be closely related to wind speed and polarization isolation. Correction of residual amplitude and phase error were employed to improve the retrieval precision of wind vector. It is revealed that the wind speed retrieval precision of VV polarization improved with correction of residual amplitude error. In addition, the influence of residual amplitude and phase error on wind direction retrieval can be neglected. Thus, it is concluded that correction of amplitude and phase error has the potential to improve wind vector retrievals from GF-3 quad-polarization SAR.

Since multichannel sliding spotlight synthetic aperture radar (SAR) can simultaneously achieve high-resolution and wide-swath (HRWS) remote sensing observations, the large volume of data collected from multiple channels increases the burden on the data link, while the estimation and compensation of channel errors further complicate the signal processing. To reduce hardware costs and algorithm complexity while ensuring HRWS capabilities, this letter proposes a novel single-channel ultrahigh-resolution and wide-swath sliding spotlight SAR imaging approach based on a Poisson disk sampling strategy. First, the proposed method adopts a Poisson disk sampling strategy to collect nonuniform azimuth sampling echo data, which has well anti-aliasing effects for the sparsity-driven reconstruction. Second, a modified Chirp Scaling algorithm, which integrates a fourth-order range model (FORM4) to precisely account for the spaceborne SAR curved orbit, is presented to achieve full-aperture focusing of ultrahigh resolution sliding spotlight SAR data across the entire scene. Then, the complete imaging reconstruction process is given, which mainly involves the operation of Deramp preprocessing based on nonuniform sampling sliding spotlight SAR data, as well as threshold iterative processing. Simulation results powerfully demonstrate the capability of the proposed MCSA to achieve a 0.3m resolution over a 4km×4km swath in non-uniformly sampled sliding spotlight SAR, with a 20% reduction in data acquisitiion compared to traditional approaches.

The estimation and correction of antenna patterns are essential for ensuring the relative radiometric quality of SAR images. Traditional methods for antenna pattern estimation rely on artificial calibrators or specific stable natural scenes like the Amazon rainforest, which are limited by cost, complexity, and geographic constraints, making them unsuitable for frequent imaging demands. Meanwhile, general natural scenes are imaged frequently using SAR systems, but their true scattering characteristics are unknown, posing a challenge for direct antenna pattern estimation. Therefore, it is considered to use the calibrated SAR to obtain the scattering characteristics of these general scenarios; that is, introducing the concept of cross-calibration. Accordingly, this paper proposes a novel method for estimating the SAR range antenna pattern based on cross-calibration. The method addresses three key challenges: (1) Identifying pseudo-invariant natural scenes suitable as reference targets through spatial uniformity and temporal stability assessments using standard deviation and amplitude correlation analyses; (2) Achieving pixel-level registration of heterogeneous SAR images with an iterative method despite radiometric imbalances; (3) Extracting stable power values by segmenting images and applying differential screening to minimize outlier effects. The proposed method is validated using Gaofen-3 SAR data and shows robust performance in bare soil, grassland, and forest scenarios. Comparing the results of the proposed method with the tropical forest-based calibration method, the maximum shape deviation between the range antenna patterns of the two methods is less than 0.2 dB.

The range-dependence on polarization distortion of spaceborne polarimetric synthetic aperture radar (SAR) affects the accuracy of wide-swath polarization applications, such as environmental monitoring, sea ice classification and ocean wave inversion. Traditional calibration methods, assessing the distortion mainly based on ground experiments, suffer from tedious active calibrator deployment work, which are time-consuming and cost-intensive. This paper proposes a novel polarimetric assessment and calibration method for the quad-polarized wide-swath ScanSAR imaging mode. Firstly, by using distributed target data that satisfy the system reciprocity requirement, we assess the polarization distortion matrices for a single beam in the mode. Secondly, we transfer the matrix results from one beam to another by analyzing data from the overlapping region between beams. Thirdly, we calibrate the quad-polarized data and achieve an overall assessment and calibration results. Compared to traditional calibration methods, the presented method focuses on using cross-beam (overlapping area) data to reduce the dependence on active calibrators and avoid conducting calibration work beam-by-beam. The assessment and calibration experiment is conducted on Gaofen-3 quad-polarized ScanSAR experiment mode data. The calibrated images and polarization decomposition results are compared with those from well-calibrated quad-polarized Stripmap mode data located in the same region. The results of the comparison revealed the effectiveness and accuracy of the proposed method.