Spaceborne Spaceborne Synthetic Aperture Radar Research Articles

An Autofocus Approach With Applications to Ionospheric Scintillation Compensation for Spaceborne SAR Images

Spaceborne synthetic aperture radar (SAR) systems, operating at L-band or lower, are very susceptible to ionospheric scintillation. The scintillation phase error (SPE) can bring about serious azimuth decorrelation and resolution loss. Compared with the motion phase error, the SPE takes on a much stronger spatial-variation both in along-track and across-track orientations, and its anisotropic feature makes the compensation more intractable. In this article, the phase gradient autofocus (PGA) is used for the first time to compensate the spatial-varying and anisotropic SPE for spaceborne SAR images. It begins with achieving a reliable SPE estimate by applying PGA to a strong scatterer. According to the preknowledge of the phase screen altitude and the anisotropic elongation heading, the emphasis is then on estimating the SPEs for other pixels from the well-estimated SPE, based on the mutual correlation and overlapping of SPEs. The pixel-by-pixel strategy is adopted for the final compensation. The proposed methodology is very appropriate for SAR images with few corner reflectors, which is validated on a simulated L-band stripmap data and a PALSAR-2 spotlight real data. It shows more powerful utility than the classical PGA. The performance analysis is implemented with regard to two necessary factors, which further confirms the effectiveness of the proposed methodology.

Motion Compensation/Autofocus in Airborne Synthetic Aperture Radar: A Review

Air- and spaceborne synthetic aperture radar (SAR) can provide a large number of high-resolution images for microwave remote sensing applications, such as geoscience and climate change research, environmental Earth system monitoring, and precision agriculture. Unlike spaceborne SAR, the flight trajectory of airborne SAR may deviate from its ideal straight course due to the influence of atmospheric turbulence, resulting in significant motion errors in radar raw data. If a standard imaging algorithm is directly used to process the data, the image focusing quality will be significantly degraded. Therefore, to improve image focusing quality, one typically needs to integrate standard imaging algorithms with an effective motion compensation (MoCo)/autofocus technique. In this article, we present a comprehensive overview of MoCo/autofocus methods for airborne SAR to articulate related research and promote further development.

Multi-Scale Ship Detection Algorithm Based on a Lightweight Neural Network for Spaceborne SAR Images

The current limited spaceborne hardware resources and the diversity of ship target scales in SAR images have led to the requirement of on-orbit real-time detection of ship targets in spaceborne synthetic aperture radar (SAR) images. In this paper, we propose a lightweight ship detection network based on the YOLOv4-LITE model. In order to facilitate the network migration to the satellite, the method uses MobileNetv2 as the backbone feature extraction network of the model. To solve the problem of ship target scale diversity in SAR images, an improved receptive field block (RFB) structure is introduced, enhancing the feature extraction ability of the network, and improving the accuracy of multi-scale ship target detection. A sliding window block method is designed to detect the whole SAR image, which can solve the problem of image input. Experiments on the SAR ship dataset SSDD show that the detection speed of the improved lightweight network could reach up to 47.16 FPS, with the mean average precision (mAP) of 95.03%, and the model size is only 49.34 M, which demonstrates that the proposed network can accurately and quickly detect ship targets. The proposed network model can provide a reference for constructing a spaceborne real-time lightweight ship detection network, which can balance the detection accuracy and speed of the network.

A Novel Imaging Algorithm for High-Resolution Wide-Swath Space-Borne SAR Based on a Spatial-Variant Equivalent Squint Range Model

High-Resolution Wide-Swath (HRWS) is an important development direction of space-borne Synthetic Aperture Radar (SAR). The two-dimensional spatial variation of the Doppler parameters is the most significant characteristic of the sliding spotlight space-borne SAR system under the requirements of HRWS. Therefore, the compensation of the two-dimensional spatial variation is the most challenging problem faced in the imaging of HRWS situations. The compensatory approach is then proposed to address this problem in this paper. The spatial distribution of the Doppler parameters for the HRWS space-borne SAR data in the sliding spotlight working mode is firstly analyzed, based on which a Spatial-Variant Equivalent Slant Range Model (SV-ESRM) is put forward to accurately formulate the range history for the distributed target. By introducing an azimuth-varying term, the SV-ESRM can precisely describe the range history for not only central targets but also marginal targets, which is more adaptive to the HRWS space-borne SAR requirements. Based on the SV-ESRM, a Modified Hybrid Correlation Algorithm (MHCA) for HRWS space-borne SAR imaging is derived to focus the full-scene data on one single imaging processing. A Doppler phase perturbation incorporated with the sub-aperture method is firstly performed to eliminate the azimuth variation of the Doppler parameters and remove the Doppler spectrum aliasing. Then, an advanced hybrid correlation is employed to achieve the precise differential Range Cell Migration (RCM) correction and Doppler phase compensation. A range phase perturbation method is also utilized to eliminate the range profile defocusing caused by range-azimuth coupling for marginal targets. Finally, a de-rotation processing is performed to remove the azimuth aliasing and the residual azimuth-variance and obtain the precisely focused SAR image. Simulation shows that the SAR echoes for a 20 km × 20 km scene with a 0.25 m resolution in both the range and azimuth directions could be focused precisely via one single imaging processing, which validates the feasibility of the proposed algorithm.

BSF: Block Subspace Filter for Removing Narrowband and Wideband Radio Interference Artifacts in Single-Look Complex SAR Images

Radio signals emitted by various sources, such as ground radars and broadcast/communication devices, can unintentionally cause radio frequency interference (RFI) to spaceborne synthetic aperture radar (SAR), degrading SAR image qualities to various degrees. Most existing methods tackle this problem by applying specially designed preprocessing steps to RFI-polluted level-0 SAR data before SAR focusing. However, such preprocessing is not widely used in spaceborne SAR, as there exist radiometric artifacts due to various RFI sources in the level-1 single-look complex (SLC) image products in many spaceborne SAR data, e.g., Sentinel-1 open data archives. To address this problem, in this article, we first propose a generic subspace model for characterizing a variety of RFI types, which reveals a low-dimensional structure of RFI subspace. Based on the proposed model, we next design a block subspace filter (BSF) for removing RFI artifacts in SLC SAR images directly. Experiments with ERS-2, ENVISAT/ASAR, Sentinel-1, and Gaofen-3 data are presented, and quantitative assessments based on numerical simulations are provided, which demonstrates the promising performance and application potentials of the proposed method. BSF is simple yet efficient and does not require performing preprocessing on level-0 raw data, which is helpful for users to obtain clean SAR images. MATLAB/Octave code implementation of BSF is available at <uri>https://github.com/huizhangyang/BSF</uri>.

Characterizing Ancient Channel of the Yellow River From Spaceborne SAR: Case Study of Chinese Gaofen-3 Satellite

The lower reaches of the ancient Yellow River (AYR) migrated very frequently, like a loong swinging its tail on the land of China. As the origin of Chinese civilization, AYR provided natural conditions for the people to thrive. However, the sediment carried by AYR still has a negative impact on local agricultural production. This letter, based on Gaofen-3, extracted scattering characteristics of archeological anomalies, detecting part of AYR during Song and Jin Dynasties, which was confirmed with field investigations. Then, an adaptive irregular convolution kernel U-Net (AICK-U-Net) was proposed to reconstruct the channel of AYR, based on the images obtained by the different polarization decomposition methods in October, and the precision and recall reached 96.21% and 94.45%, respectively. Finally, two decision-level methods were proposed to optimize the reconstruction results, improving the precision and recall to 96.39% and 97.36%, respectively. In summary, Spaceborne synthetic aperture radar (SAR), with the application of polarization decomposition and neural network, provides new insights for detecting archeological anomalies and reconstructing archaeolandscapes.

Retrieval of Sea Ice Drift From the Central Arctic to the Fram Strait Based on Sequential Sentinel-1 SAR Data

Sea ice drift (SID) is crucial for understanding sea ice dynamics and for navigation safety. This study focuses on a comprehensive analysis of SID retrieval in the Arctic based on spaceborne synthetic aperture radar (SAR) data. A state-of-the-art method combining feature tracking and pattern matching techniques was applied to sequential Sentinel-1 (S1) SAR data in 2020 to derive SID from the central Arctic to the Fram Strait. The SAR retrievals were validated with drifting buoys. For temporal intervals of S1 data of approximately 24 hours, 15,254 collocations were collected from January to June and from October to December, yielding a 0.00 cm/s bias for the drift velocity magnitude and 0.27 degrees for direction with corresponding root mean square error (RMSE) of 0.47 cm/s and 4.73 degrees. Using temporal intervals of S1 data of less than 24 hours, we retrieved SID from July to September. A total of 644 collocations yields a comparison with a bias of 0.52 cm/s and 4.62 degrees for the drift magnitude and direction, respectively. The corresponding RMSE values are 1.85 cm/s and 20.73 degrees. The comparisons demonstrate better performance than the operational SAR-based SID product using the MCC method and are consistent with seasonal trends in drift velocity with the coarse-resolution product. We also analyzed the variations in SAR retrievals and further estimated appropriate temporal intervals, making it feasible to conduct long-term SID retrievals based on spaceborne SAR data at high spatial resolution in the Arctic.

A Digital Filter Bank Based Method for Data Reduction in Spaceborne SAR Electronics

On-board data reduction is a major concern in designing of a spaceborne synthetic aperture radar (SAR) system since the volume of acquired SAR data is generally much higher than the downlink capability to the ground-station. The dechirp-on-receive (DoR) method is considered the state-of-the-art SAR data reduction technique. If there is deramping hardware in the SAR instrument, DoR is an effective method to reduce the volume of images for high resolution modes. In this paper, we use a digital signal processing method which applies a modified discrete Fourier transform (MDFT) filter bank for SAR data reduction. We call this method MDFT band selection filter (MDFT-BSF). This paper presents a quantitative analysis of the MDFT-BSF on data reduction performance. In addition, we provide a relationship between the data reduction performance and the number of sub-bands (M), and show that there is an optimal value of M that minimizes the volume of on-board SAR data. An evaluation of MDFT-BSF including a comparison with the DoR method presents that MDFT-BSF has an advantage for SAR data reduction. We show that MDFT-BSF can be implemented and operated on commercial space-grade FPGAs by the development of a spaceborne SAR digital receiver.

A Modified PGA for Spaceborne SAR Scintillation Compensation Based on the Weighted Maximum Likelihood Estimator and Data Division

The P-band spaceborne synthetic aperture radar (SAR) is significantly affected by ionospheric scintillation. Although the traditional phase gradient autofocus (PGA) can estimate and compensate the scintillation phase of the single polarization SAR data, the quality of the refocused image will degrade at the scene edge. In this paper, a modified PGA based on the weighted maximum likelihood (WML) estimator and data division is proposed for full-scene image refocusing. First, a data division strategy for scintillation corrupted image is introduced, which is based on the prior scintillation information including its power spectral density (PSD) and autocorrelation function (ACF). Then, some pre-processing steps including data selection, circular shifting and windowing are performed for suppressing the noise and clutter. Finally, the scintillation phase is estimated by the WML estimator with fewer iterations, and after the scintillation phase of all data blocks are obtained, the distorted full-scene image is refocused. Using the generated wide-band ionospheric scintillation model (WBMOD) phase screen, numerical simulations based on point targets and scenes derived from real spaceborne SAR data are carried out. The evaluation results about resolution, peak side-lobe ratio (PSLR), integral side-lobe ratio (ISLR), correlation coefficient and image entropy demonstrate the effectiveness of the proposed algorithm.

Two-Dimensional Spectral Analysis Filter for Removal of LFM Radar Interference in Spaceborne SAR Imagery

Radio spectrum bands allocated to spaceborne synthetic aperture radar (SAR) imagery are shared by multiple missions. In practical radio spectrum environments, these bands are also used by some ground radars, e.g., C-band weather radar. Due to this fact, radio frequency interference (RFI) may occur for a spaceborne SAR when its received signals contain the transmitted waveforms from another SAR or radar operating at the same frequency band. This particular class of RFI is usually linear-frequency-modulation (LFM) signals, which can cause bright radiometric artifacts in focused SAR images. Most existing signal processing approaches designed for addressing this problem belong to the class of preprocessing methods, which removes RFI in level-0 raw radar data before SAR focusing. In this article, we propose a postprocessing kernel&#x2014;2-D SPECtral ANalysis (2-D SPECAN) filter, for removing the class of LFM RFI in level-1 SLC images. The filtering consists of three main steps: Step 1: focus LFM RFI artifacts in SLC images as point-like responses in the spectral domain via 2-D SPECAN; Step 2: perform 2-D notch filtering in the spectral domain to remove the most contribution of the RFI responses; and Step 3: transform the filtered spectrum back into the SLC image domain using the inverse operation of the 2-D SPECAN. For computation efficiency, we design a simplified processing flow and adopt a blockwise processing strategy. Experiments with several Sentinel-1 SLC images demonstrate that severe RFI artifacts in SLC images can be removed significantly by the proposed method.

Eddies in the Marginal Ice Zone of Fram Strait and Svalbard from Spaceborne SAR Observations in Winter

Here we investigate the intensity of eddy generation and their properties in the marginal ice zone (MIZ) regions of Fram Strait and around Svalbard using spaceborne synthetic aperture radar (SAR) data from Envisat ASAR and Sentinel-1 in winter 2007 and 2018. Analysis of 2039 SAR images allowed identifying 4619 eddy signatures. The number of eddies detected per image per kilometer of MIZ length is similar for both years. Submesoscale and small mesoscale eddies dominate with cyclones detected twice more frequently than anticyclones. Eddy diameters range from 1 to 68 km with mean values of 6 km and 12 km over shallow and deep water, respectively. Mean eddy size grows with increasing ice concentration in the MIZ, yet most eddies are detected at the ice edge and where the ice concentration is below 20%. The fraction of sea ice trapped in cyclones (53%) is slightly higher than that in anticyclones (48%). The amount of sea ice trapped by a single ‘mean’ eddy is about 40 km2, while the average horizontal retreat of the ice edge due to eddy-induced ice melt is about 0.2–0.5 km·d–1 ± 0.02 km·d–1. Relation of eddy occurrence to background currents and winds is also discussed.

Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

The spaceborne synthetic aperture radar (SAR) sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture, and achieve the third dimensionality recognition. In this paper, combined with the actual triple star orbits, a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis (PCA) is presented. Firstly, interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain. Secondly, as a method with simple principle and fast calculation, the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics. Finally, the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA. The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49% and random noise introduced by the receiver. Meanwhile, due to the influence of orbit distribution of the actual triple star orbits, the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results. This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.

Combined Block Adjustment for Optical Satellite Stereo Imagery Assisted by Spaceborne SAR and Laser Altimetry Data

To ensure the accuracy of large-scale optical stereo image bundle block adjustment, it is necessary to provide well-distributed ground control points (GCPs) with high accuracy. However, it is difficult to acquire control points through field measurements outside the country. Considering the high planimetric accuracy of spaceborne synthetic aperture radar (SAR) images and the high elevation accuracy of satellite-based laser altimetry data, this paper proposes an adjustment method that combines both as control sources, which can be independent from GCPs. Firstly, the SAR digital orthophoto map (DOM)-based planar control points (PCPs) acquisition is realized by multimodal matching, then the laser altimetry data are filtered to obtain laser altimetry points (LAPs), and finally the optical stereo images’ combined adjustment is conducted. The experimental results of Ziyuan-3 (ZY-3) images prove that this method can achieve an accuracy of 7 m in plane and 3 m in elevation after adjustment without relying on GCPs, which lays the technical foundation for a global-scale satellite image process.

Optimal Design of Antenna for Spaceborne SAR Based on Differential Evolution Algorithm

An important feature of future spaceborne synthetic aperture radar (SAR) is the adoption of large mesh reflectors fed by arrays. The main advantage of this SAR sensor is the provision of large antenna apertures and reconfigurable feed excitation. A large deployable mesh-reflector antennas combinaed with feed arrays is designed for the application of spaceborne SAR on geosynchronous orbit. To decrease the transmit power of feed element and increase the flexibility, a large scale of two-dimensional feedarray is adopted. An approach based on defocused reflector is used to broaden the beams from feed element, so almost all the feed elements can participate in the pattern synthesis in the complete angular domain. This paper presents a new optimization method of the defocused reflector system. The method aims at getting high gain and low sidebobes by optimizing the reflector parameters together with the feed array. The differential evolution algorithm(DE) is used to get globally optimal solution. The performance of the reflector after optimization is computed to demonstrate the effective of the method presented.

Real-Time Processing of Spaceborne SAR Data With Nonlinear Trajectory Based on Variable PRF

Spaceborne synthetic aperture radar (SAR) real-time imaging is especially important for disaster emergencies and real-time monitoring applications with highly desired real-time requirements. Therefore, the continuous improvement of real-time imaging efficiency is an important development trend. At present, traditional real-time imaging algorithms based on constant pulse repetition frequency (PRF) have low accuracy when processing spaceborne SAR data with nonlinear trajectory. For this problem, the existing methods usually introduce some complex signal processing steps, such as scaling or interpolation processing, to improve the accuracy of the real-time imaging, but this will reduce its efficiency. Therefore, this article proposes a new real-time imaging algorithm based on variable PRF for nonlinear trajectory spaceborne SAR. By introducing the variable PRF, the proposed algorithm is equivalent to complete the complex signal processing steps in the radar signal transmission stage, which can greatly improve the efficiency of real-time imaging. Simulation experiments verify the effectiveness of the algorithm.

An FPGA-Based Four-Channel 128k-Point FFT Processor Suitable for Spaceborne SAR

Spaceborne synthetic aperture radar (SAR) plays an important role in many fields of national defense and the national economy, and the Fast Fourier Transform (FFT) processor is an important part of the spaceborne real-time SAR imaging system. How to meet the increasing demand for ultra-large-scale data processing and to reduce the scale of the hardware platform while ensuring real-time processing is a major problem for real-time processing of on-orbit SAR. To solve this problem, in this study, we propose a 128k-point fixed-point FFT processor based on Field-Programmable Gate Array (FPGA) with a four-channel Single-path Delay Feedback (SDF) structure. First, we combine the radix-23 and mixed-radix algorithms to propose a four-channel processor structure, to achieve high efficiency hardware resources and high real-time performance. Secondly, we adopt the SDF structure combined with the radix-23 algorithm to achieve efficient use of storage resources. Third, we propose a word length adjustment strategy to ensure the accuracy of calculations. The experimental results show that the relative error between the processor and the MATLAB calculation result is maintained at about 10−4, which has good calculation accuracy.

A Robust Stereo Positioning Solution for Multiview Spaceborne SAR Images Based on the Range–Doppler Model

In recent years, the stereo positioning technology based on multiview spaceborne synthetic aperture radar (SAR) images has been widely applied in digital surface model extraction. In this letter, problems of the existing methods based on the range–Doppler (RD) model in a multiview stereo solution are pointed out. A robust stereo positioning solution for multiview spaceborne SAR images based on the RD model is proposed. In the proposed method, the traditional RD model is normalized to reduce the model errors caused by the different scales of the range equation and Doppler equation. A weighting strategy is also proposed to improve the positioning accuracy. This strategy is useful for multiview stereo positioning when using images of different satellites with orbital data of different accuracies. The experiments based on GaoFen-3 and TerraSAR-X satellite data sets validate the effectiveness of the proposed method.

Suppression of Range Ambiguity in Spaceborne SAR With Elevation Beam Pattern Mask Design

In this letter, we present a method to design an elevation beam pattern mask for spaceborne synthetic aperture radar (SAR) to reduce the range ambiguity. The proposed two-way elevation beam pattern mask, which requires relatively low sidelobe levels only in the direction of strong range ambiguous echoes, can be highly suitable for enhancing the range ambiguity to signal ratio (RASR). The power levels of the different ambiguous echoes are estimated based on the backscattering coefficient model and satellite geometry. To meet the two-way beam pattern mask, both transmit and receive beam patterns are synthesized simultaneously through the minimax algorithm. To confirm the effectiveness of this mask design method, the RASR performance is evaluated by using various swaths.

On the Mutual Interference Between Spaceborne SARs: Modeling, Characterization, and Mitigation

Since by the International Telecommunications Union (ITU) regulatory the radio spectrum available to spaceborne synthetic aperture radar (SAR) is restricted to certain limited frequency intervals, there are many different spaceborne SAR systems sharing common frequency bands. Due to this reason, it is reported that two spaceborne SARs at orbit cross positions can potentially cause severe mutual interference. Specifically, the transmitting signal of a SAR, typically linear frequency modulated (LFM), can be directly received by the side or back lobes of another SAR's antenna, causing radiometric artefacts in the focused image. This paper tries to model and characterize the artefacts, and study efficient methods for mitigating them. To this end, we formulate an analytical model for describing the artefact, which reveals that the mutual interference can introduce a two-dimensional LFM radiometric artefact in image domain with a limited spatial extent. We show that the artefact is low-rank based on range-azimuth decoupling analysis and two-dimensional high-order Taylor expansion. Based on the low rank model, we show that two methods, i.e., principle component analysis and its robust variant, can be adopted to efficiently mitigate the artefact via processing in image domain. The former method has the advantage of fast processing speed, for example, a sub-swath of Sentinel-1 interferometric wide swath image can be processed within 70 seconds via block-wise operation, whereas the latter provides improved accuracy for sparse point-like scatterers. Experiment results demonstrate that the radiometric artefacts caused by mutual interference in Sentinel-1 level-1 images can be efficiently mitigated via the proposed methods.

Deep convolutional neural network for P-band spaceborne synthetic aperture radar imaging through the ionosphere

The dispersion characteristics of the background ionosphere and the random fluctuations of the ionospheric irregularities are an important source of phase error that seriously damages the quality of radar images. To mitigate the ionospheric distortions of P-band spaceborne synthetic aperture radar (SAR) images, a super-resolution deep learning method is proposed in this paper. Different from the traditional imaging method based on the prior knowledge of imaging, the method proposed in this paper directly trains the ionospheric implicit imaging model of spaceborne SAR without complicated iterative processes. First, the phase errors, which are caused by the dispersion and the scintillation in the range and azimuth directions, respectively, are analyzed. Second, an improved u-net structure that embeds the residual network between the encoder and decoder is briefly proposed. Finally, the range doppler algorithm is used to preprocess radar image as the input of the convolutional neural network (CNN) and is compare with the predicted output of the CNN. Experimental results prove the effectiveness of the proposed method in radar image focusing.