Synthetic Aperture Radar System Parameters Research Articles

FPGA-Based Acceleration of Polar-Format Algorithm for Video Synthetic-Aperture Radar Imaging

This paper presents a polar-format algorithm (PFA)-based synthetic-aperture radar (SAR) processor that can be mounted on a small drone to support video SAR (ViSAR) imaging. For drone mounting, it requires miniaturization, low power consumption, and high-speed performance. Therefore, to meet these requirements, the processor design was based on a field-programmable gate array (FPGA), and the implementation results are presented. The proposed PFA-based SAR processor consists of both an interpolation unit and a fast Fourier transform (FFT) unit. The interpolation unit uses linear interpolation for high speed while occupying a small space. In addition, the memory transfer is minimized through optimized operations using SAR system parameters. The FFT unit uses a base-4 systolic array architecture, chosen from among various fast parallel structures, to maximize the processing speed. Each unit is designed as a reusable block (IP core) to support reconfigurability and is interconnected using the advanced extensible interface (AXI) bus. The proposed PFA-based SAR processor was designed using Verilog-HDL and implemented on a Xilinx UltraScale+ MPSoC FPGA platform. It generates an image 2048 × 2048 pixels in size within 0.766 s, which is 44.862 times faster than that achieved by the ARM Cortex-A53 microprocessor. The speed-to-area ratio normalized by the number of resources shows that it achieves a higher speed at lower power consumption than previous studies.

A Simulation Method of Two-Dimensional Sea-Surface Current Field for Trajectory Crossing Spaceborne SAR

The trajectory-crossing method is an important and effective method for spaceborne SAR (synthetic aperture radar) to detect a two-dimensional current field. However, in practical applications, there are few spaceborne SAR data that meet the requirements of close acquisition time and overlapping trajectories, which makes it difficult to comprehensively analyze the impact of different systems and environmental parameters on current measurement results from real data processing. With the proposal of a SAR constellation plan in the future, the data resources will be constantly enriched, and the trajectory-crossing method will be widely used. It is, thus, necessary to lay some theoretical foundation at present. A two-dimensional sea-surface-current-field simulation method for trajectory crossing spaceborne SAR is proposed in this paper. Based on the principles of the trajectory-crossing method, the proposed method can realize the simulation of two-dimensional sea-surface-current field under given spaceborne SAR system and environmental parameters. In this paper, the simulation process of this method is given, and the simulation experiment is performed. Compared with the current measurement results of SAR data, the simulation experiment shows that the current velocity error is less than 0.03 m/s and the direction error is less than 10 degrees, which proves the reliability of the proposed simulation method. The proposed method lays a foundation for analyzing the influence of various parameters in the application of the trajectory-crossing method.

The Influence of the Azimuth RCS Pattern of Calibrator on SAR Absolute Calibration

The realization of radiometric calibration relies on the known artificial point targets as the reference, such as corner reflectors. One of the criteria of the calibrator is that the 3 dB-beamwidth of the azimuth radar cross section (RCS) pattern needs to be larger than the synthetic aperture radar (SAR) antenna 3-dB beamwidth to ensure the SAR antenna, which has a narrow azimuth beamwidth, can align to the calibrator while also making the nominal RCS value of the calibrator approximately constant during the radiometric calibration. However, the RCS of the calibrator is actually inconstant within a synthetic aperture period, especially when the SAR antenna beamwidth is wide. The simplified treatment will introduce errors to calibration. In this letter, the azimuth RCS pattern is taken into account. The error caused by the constant RCS is modeled. Based on the error model, an improved criterion of the calibrator is discussed. The experiments use the known SAR system parameters for numerical simulation based on dihedral corner reflectors (DCRs) with different sizes. The results verify the error model and indicate that when the SAR beamwidth is larger than the beamwidth of the calibrator, and the introduced error cannot be ignored. The relationship between the size of the calibrator and the SAR beamwidth is further analyzed through the experiments.

Dictionary-Based Principal Component Analysis for Ground Moving Target Indication by Synthetic Aperture Radar

This letter addresses an efficient algorithm for ground moving target detection and estimation of motion parameters by synthetic aperture radar (SAR). The proposed method outperforms the conventional robust principal component analysis (RPCA)–based ground moving target indication (GMTI) methods that were proposed in the literature. The ability to estimate the radial and along-track velocities of ground moving targets is provided. The rank constraint in the conventional RPCA problem will be automatically relaxed by employing a dictionary matrix for clutter representation. Thus, the new optimization problem will be solved easier with lower degrees of freedom. Furthermore, this dictionary helps to suppress the clutter of higher Doppler frequencies in case of wind blowing scenarios and intrinsic clutter motion modeling. By employing another dictionary matrix for all possible moving targets with different location and velocity, each solution of the optimization problem will be reasonable as it corresponds to a moving target. Although, the two dictionary matrices impose extra computational burden, this load will be prepared prior to other GMTI processing by the information of the SAR system and scenario parameters. Moreover, the algorithm is proposed for the single-channel SAR configurations and has lower computational load than the conventional RPCA-GMTI methods that have to process the recorded data of multichannel systems. Numerical and experimental results are used to evaluate the performance of the proposed method and validate the theoretical discussions.

Azimuth ambiguity suppression in SAR images using Doppler-sensitive signals

Abstract In the article the problem of the azimuth ambiguity in synthetic aperture radar (SAR) images and its genesis are presented. A method of suppressing the ambiguities by utilization of Doppler-sensitive signals is proposed, and the necessary modifications to the SAR synthesis algorithm are discussed. The SAR system parameters required for an optimal performance of the method are discussed and simulation results are presented.

Efficient Motion Compensation of a Moving Object on SAR Imagery Based on Velocity Correlation Function

Current motion compensation algorithms for a moving object on synthetic aperture radar (SAR) imagery by refocusing are accurate, but they suffer from a severe computational efficiency problem. If the step size of an assumed target velocity is too large, one could miss the true target velocity, whereas too small a step size would lead to a considerable computation load. To address this issue, the way motion error affects a compressed signal should be understood. In this paper, we introduce the concept of velocity correlation function (VCF) to describe the sensitivity of an SAR compressed signal to motion error. We propose its analytical model by straightforwardly tackling conventional matched filtering, and then we thoroughly compare the model with the experimentally obtained VCF for each static and moving object on real L-band airborne/spaceborne SAR imagery. The analytically derived VCF is well validated, as it shows excellent agreement with those experiments. Finally, the VCF is generalized to a velocity correlation map to visualize a sensitivity of SAR system parameters to target motion in both the range and the azimuth directions simultaneously.

SAR IMAGE SIMULATION WITH APPLICATION TO TARGET RECOGNITION

This paper presents a novel synthetic aperture radar (SAR) image simulation approach to target recognition, which consists of two frameworks, referred to as the satellite SAR images simulation and the target recognition and identiflcation. The images simulation makes use of the sensor and target geo-location relative to the Earth, movement of SAR sensor, SAR system parameters, radiometric and geometric characteristics of the target, and target radar cross section (RCS), orbital parameters estimation, SAR echo signal generation and image focusing to build SAR image database. A hybrid algorithm that combines the physical optics, physical difiraction theory, and shooting and bouncing rays was used to compute the RCS of complex radar targets. Such database is vital for aided target recognition and identiflcation system Followed by reformulating the projection kernel in an optimization equation form, the target's re∞ectivity fleld can be accurately estimated. Accordingly, the target's features can be efiectively enhanced and extracted, and the dominant scattering centers are well separated. Experimental results demonstrate that the simulated database developed in this paper is well suited for target recognition. Performance is extensively tested and evaluated from real images by Radarsat-2 and TerraSAR-X. Efiectiveness and e-ciency of the proposed method are further conflrmed.

고해상도 위성 SAR 영상품질 성능 분석 툴 개발

본 연구에서는 영상레이다 (SAR)의 영상품질 분석 변수 및 확장 보간법, 배경레벨 제거 기법 등의 분석 기법을 정의하고 이를 바탕으로 SAR 영상품질 분석 툴을 개발하였다. 개발된 SAR 영상품질 분석 툴은 크게 점 표적 분석 (PTA) 모듈, 분산 표적 분석 (DTA) 모듈, 모호성 분석 (AMA) 모듈, NESZ 분석 (NESZA) 모듈, 총 4개의 주요 모듈로 구성된다. 개발 툴은 SAR 제품 파일 포맷에서 다양한 시스템 파라미터 추출하고, 이를 바탕으로 임펄스 응답 특성, 방사 성능, 모호성 등의 SAR 영상 품질 변수를 계산한다. In this paper, the typical Synthetic Aperture Radar (SAR) image quality parameters and analysis method are defined, and the SAR image analysis tool is presented for SAR image evaluation. The structure of the developed SAR image analysis tool consists of four key modules; point target analysis (PTA) module, distributed target analysis (DTA) module, ambiguity analysis (AMA) module, and NESZ analysis (NESZA) module. The developed tool is able to extract the various SAR system parameters from standard SAR product format files. Based on these extracted system parameters, typical SAR image quality parameters are derived from SAR image data.

A noise model for estimated synthetic aperture radar look cross spectra acquired over the ocean

It is well known that look cross spectra processed from synthetic aperture radar (SAR) contain valuable information on ocean waves. With the launch of the European satellite ENVISAT, SAR look cross spectra (SLCS) have become available on an operational basis. Activities therefore exist at different European weather centres to use the data for assimilation into numerical wave models. Furthermore there is scientific interest in SLCS, e.g., concerning the estimation of the phase speed of ocean waves. For the estimation of ocean wave parameters, it is important to have information about the accuracy of SLCS. In this paper, errors of estimated SLCS due to SAR image speckle, spectral estimation errors, and image pattern decorrelation associated with ocean wave motion are analyzed. A probability model is proposed for the estimated SLCS based on the respective cross-spectrum coherence. The model is used to calculate signal-to-noise ratios and confidence limits for the SLCS phase and magnitude, as well as the real and imaginary part. The coherence is factored into a component describing look decorrelation due to SAR image speckle and a second factor describing the effect of sea surface motion. It is shown that the ocean-wave-dependent decorrelation can be simulated using existing nonlinear integral transforms for the look variance spectrum and the SLCS. The decorrelation effect associated with speckle noise is related to SAR system parameters, e.g., the spatial SAR resolution. The probability model is used to investigate the optimal choice of look processing parameters like the look separation time. A statistical analysis based on a global dataset of a reprocessed dataset of European Remote Sensing 2 satellite SLCS is presented confirming the applicability of the probability model. The implications of the results for the retrieval of two-dimensional wave spectra from SLCS are summarized. Possible future applications of the model like, for example, the investigation of the turbulent air flow over waves, are discussed.