Synthetic Aperture Radar Echo Data Research Articles

High-resolution SAR optoelectronic processor based on sensor-less adaptive optics

Studying phase error is central to synthetic aperture radar (SAR) research. Phase error due to the real motion status of the SAR platform and propagation effects can reduce the utility of high-resolution SAR images even with theoretical estimation-based phase error correction. Adaptive optics (AO) can be used to correct optical aberrations. This study proposes an advanced, high-resolution SAR optoelectronic processor by integrating conventional processors with sensor-less AO techniques. This processor provides accurate adaptive phase error correction capabilities. The processing results of SAR echo data demonstrate the effectiveness of the proposed system in adaptive phase error correction and imaging improvement.

Pulse RFI Mitigation in Synthetic Aperture Radar Data via a Three-Step Approach: Location, Notch, and Recovery

In complex electromagnetic environments, synthetic aperture radar (SAR) is severely affected by radio frequency interference (RFI) from other systems, such as ground-based radar, cellular networks, and global positioning systems, and this interference cannot be neglected. Pulse RFI (PRFI), a common form of RFI, can hinder SAR signal processing and image interpretation to varying degrees. The time-domain notch filtering method designed for mitigating PRFI can locate and mitigate the evident PRFI covered in SAR echo data, but it is helpless against PRFI hidden in a strong echo signal. In this article, a three-step approach is proposed to tackle the PRFI problem. In the proposed approach, the first step is to detect and locate PRFI; this is based on eigenvalue decomposition (EVD) and the short-time Fourier transform (STFT). The second step is to notch PRFI, and this is based on a time-domain notch filter. The third step is to recover the notched signal using a novel matrix completion strategy, which integrates with a robust low-rank matrix completion (LRMC) technique—i.e.,the singular value thresholding (SVT) algorithm—and a well-known Lagrange interpolation technique. Experimental results via simulated SAR data, Sentinel-1 level-0 raw data, and L-band airborne SAR raw data demonstrate the performance of the proposed approach.

SAR Image Formation Method with Azimuth Periodically Missing Data Based on RELAX Algorithm

Synthetic aperture radar (SAR) is a widely used remote sensing observation technique. However, SAR raw echo data may be lost during the process of data acquisition by radar platform. In this paper, the imaging problem of SAR echo signal with periodically missing data along the azimuth is analyzed and a novel imaging method is proposed. Firstly, the problem of artificial artifact targets caused by periodically missing data is explained in detail, and the corresponding mathematical model is established. Then, the recovery method based on the RELAX algorithm with periodic notches data is proposed. In addition, when the size of two-dimensional (2D) echo data are large, block restoration along the azimuth is proposed to reduce the amount of calculation. Finally, the advantages of the algorithm proposed in this paper is demonstrated by the points target simulated SAR echo data processing and the real raw SAR echo data processing. When the azimuth periodically missing data rate is 50%, the SAR echo data can be recovered and the well-focused image can be obtained. Comparing the image entropy value and structural similarity index (SSIM) of the focused image, it proves the superiority of the proposed algorithm in solving the imaging problem of SAR azimuth periodically missing data.

Improved SAR imaging algorithm with azimuth periodically missing data

Aiming at the periodically missing data of synthetic aperture radar (SAR) in azimuth, a reconstruction and imaging algorithm based on L p -alternating direction method with compressed sensing theory is proposed. The algorithm can effectively suppress ghosting and aliasing caused by azimuth missing data, and improve the imaging quality. To reduce memory consumption and lower computational complexity, approximate observation model based on SAR raw data simulator is utilised to rapid reconstruction imaging. Compared to the traditional iterative shrinkage thresholding algorithm, the proposed algorithm has better reconstruction image quality. Simulation and raw SAR echo data processing demonstrate the effectiveness of the proposed method in solving the problem of imaging with periodically missing data in SAR azimuth.

A Novel Doppler Chirp Rate and Baseline Estimation Approach in the Time Domain Based on Weighted Local Maximum-Likelihood for an MC-HRWS SAR System

In this letter, a novel estimation approach for the Doppler chirp rate and baseline in azimuth is proposed for the multichannel in azimuth high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system. First, a range-invariant Doppler chirp rate estimation approach is developed based on a map drift algorithm and correlation function method. Then, a weighted local maximum-likelihood approach is adopted to obtain an accurate estimation of the range-variant Doppler chirp rate. With an accurate Doppler chirp rate, the baseline in azimuth can be estimated, which is developed from the correlation function between the echoes of adjective channels. The proposed approaches are successfully applied to process real five-channel HRWS SAR echo data, demonstrating the efficacy of the proposed methods.

2D SAR imaging scheme based on compressive sensing

Synthetic aperture radar (SAR) processing is assumed to start with a demodulated baseband signal and attempt to solve ground reflectivity. An expression of two-dimensional SAR echo data in the discrete domain is presented. To meet the requirements of the processing power and reduce the storage, a compressive sensing framework is adopted to solve the ground reflectivity. By a small number of signal samplings, the imaging is constructed efficiently and has a higher resolution. Promising results were obtained by several experiments.

Interference Suppression Algorithm for SAR Based on Time–Frequency Transform

The goal of this paper is to suppress the narrowband interference (NBI) and wideband interference (WBI) in synthetic aperture radar (SAR) by using a nonparametric method. The method is based on the analysis of time-frequency characteristic of NBI and WBI from which an interference suppression filter combined with the constant false alarm rate algorithm is designed. In this approach, the short-time Fourier transform (STFT) is used to estimate the instantaneous frequency of the SAR echo data with interference. In the STFT domain, the instantaneous frequency spectrum is represented by wavelet, and then, the designed filter filters the corresponding wavelet coefficients of the interference components. In addition, this algorithm is robust to time-varying NBI and WBI. The performance of the proposed approach is evaluated by the simulated and measured data, and the effectiveness is demonstrated.

Radiometric calibration analysis of SIR-B imagery

The second flight of the NASA Spaceborne Imaging Radar (SIR-B) collected nearly 8 hours of digital synthetic-aperture radar (SAR) data of the earth's surface. This paper analyzes the performance of the SAR to determine the accuracy of the relative radiometric calibration of these data. Procedures are presented for deriving accuracy estimates as well as limitations under which these estimates are valid. The impact on calibration of an RF breakdown in the primary antenna feed system cable is evaluated. An analysis of the platform stability based on the SAR echo data is also presented in conjunction with its resultant effect on the calibration accuracy. Finally, numerical error bounds are derived with guidelines on their utilization.