Synthetic Aperture Radar System Design Research Articles

Experimental Demonstration of Nadir Echo Removal in SAR Using Waveform Diversity and Dual-Focus Postprocessing

Synthetic aperture radar (SAR) provides high-resolution images for remote-sensing applications regardless of sunlight and weather conditions. The pulsed operation of SAR may lead to an occurrence of nadir echoes in SAR images that significantly affect the image quality in case the pulse repetition frequency (PRF), which is not properly constrained within the SAR system design. As an alternative, pulse-to-pulse variation of the transmitted waveform and dual-focus postprocessing can be exploited to remove the nadir echo and alleviate the PRF constraints (also in ScanSAR operation). This work provides a demonstration of the latter concept through an experimental acquisition of the TerraSAR-X satellite. The experiment is designed by selecting the scene and the acquisition parameters in order to have the nadir echo appearing in the SAR image. The waveform variation is achieved by alternating up- and down-chirps on transmit. The analysis of the results shows the effectiveness of dual-focus postprocessing for nadir echo suppression.

Method of Range Ambiguity Suppression Combining Sparse Reconstruction and Matched Filter

Synthetic Aperture Radar (SAR) images are often affected by range ambiguity due to antenna sidelobe characteristics and pulse operating mechanism. The work of range ambiguity suppression focuses on both SAR system design and signal processing. On the one hand, ideas have been proposed to modify the transmitting and receiving waveforms to block the ambiguous energy, such as up and down chirp modulation, multiple elevation beams, and azimuth phase coding techniques. On the other hand, signal processing methods in echo and image domains have been used to reduce the range ambiguity energy, such as up and down chirp processing and sparse regularization methods. This paper proposes a range ambiguity suppression method that combines sparse reconstruction and matched filter. There are four main steps: performing the sparse reconstruction to obtain the ambiguity area, estimating the ambiguity signal using the ambiguity area image and reconstruction matrix, separating ambiguity signal from the whole signal to obtain the signal of primary imaging area, using matched filter to the primary signal to obtain the main lobe area image. In this method, sparse reconstruction improves the accuracy of ambiguity signal estimation, and matched filter ensures the efficiency of imaging processing procedure. Simulation results show that the proposed method can effectively suppress range ambiguity. When the ambiguity energy is relatively strong, the Focal Underdetermined System Solver (FOCUSS) algorithm can get better results than the classical Orthogonal Matching Pursuit (OMP) algorithm. Moreover, the weak targets and the details of the main lobe image are well preserved.

Tilt Phenomenon in Bistatic SAR Image

The tilt phenomenon or skew in bistatic synthetic aperture radar (SAR) images has been known. This can be observed from the SAR image of a point-like scatterer, even with a symmetrical bistatic aperture. This letter explains this phenomenon in bistatic SAR images and shows that the phenomenon depends on the initial and the last positions of the transmitter and receiver platforms. A formula to calculate the tilt angle based on a general bistatic geometry is provided. This formula supports bistatic SAR system design and bistatic image quality measurements.

A Waveform-Encoded SAR Implementation Using a Limited Number of Cyclically Shifted Chirps

Synthetic aperture radar (SAR) provides high-resolution images of the Earth’s surface irrespective of sunlight and weather conditions. In conventional spaceborne SAR, nadir echoes caused by the pulsed operation of SAR may significantly affect the SAR image quality. Therefore, the pulse repetition frequency (PRF) is constrained within the SAR system design to avoid the appearance of nadir echoes in the SAR image. As an alternative, the waveform-encoded SAR concept using a pulse-to-pulse variation of the transmitted waveform and dual-focus postprocessing can be exploited for nadir echo removal and to alleviate the PRF constraints. In particular, cyclically shifted chirps have been proposed as a possible waveform variation scheme. However, a large number of distinct waveforms is required to enable the simple implementation of the concept. This work proposes a technique based on the Eulerian circuit for generating a waveform sequence starting from a reduced number of distinct cyclically shifted chirps that can be effectively exploited for waveform-encoded SAR. The nadir echo suppression performance of the proposed scheme is analyzed through simulations using real TerraSAR-X data and a realistic nadir echo model that shows how the number of distinct waveforms and therefore the system complexity can be reduced without significant performance loss. These developments reduce the calibration burden and make the concept viable for implementation in future SAR systems.

Multi-Channel SAR System Design for HRWS and GMTI in Low PRF

High-resolution and wide-swath (HRWS) is an important challenge in synthetic aperture radar (SAR). Combined SAR with array, the azimuth dual-channel SAR configuration achieves high azimuth resolution and HRWS in low Pulse repetition frequency (PRF) by doppler band synthesizing technology. However, low PRF introduces ambiguity to ground moving target indication (GMTI). Interferometry is performed between two look data in the range frequency domain to resolve the ambiguity by decreasing the interferometry phase. As a result, the phase becomes insensitive to the radial velocity of moving targets. This condition brings difficultly in moving target detection. Two channels together with two equivalent channels are exploited fully to solve these problems. The four-channel interferometry is also conducted to improve the GMTI performance. Parameters, including system and motion parameters, are estimated unambiguously to complete HRWS imaging and GMTI. System parameter design is also considered to satisfy the requirements of HRWS and GMTI simultaneously. Simulations demonstrate the validity of the proposed methods.

Low-bit quantization for UAV SAR data and its complexity analysis

Due to the limitation of size and load, an unmanned aerial vehicle (UAV) can only provide limited hardware computing resources. How to obtain high-quality synthetic aperture radar (SAR) imaging with the lowest computational complexity is an important problem in UAV-based SAR system design. In this paper, the disadvantages of existing algorithms are analyzed. Different quantization approaches are used to quantify the raw data of SAR in low bits. An image quality improvement method based on a single frequency threshold is proposed for low-bit quantized SAR data. On this basis, the computational complexity of SAR imaging matched filtering processing under different quantization strategies is studied, and the corresponding imaging quality is quantitively evaluated. This paper provides a reference for achieving the tradeoff between computational complexity and imaging quality in SAR imaging application based on UAV platform.

Curved-Path SAR Geolocation Error Analysis Based on BP Algorithm

The theoretical modeling and analysis of synthetic aperture radar (SAR) location error play an important role in SAR system design and error source budget. The existing SAR geolocation error models are mainly implicit, which are not easy to do analysis, especially in the curved-path case. In this paper, a theoretical explicit model of the relationship between image geolocation error and the path measurement error is established for curved-path SAR, based on back projection imaging algorithm. The simulations of multiple sets of parameters verify the correctness of the proposed model. The explicit model and the analysis results provide an effective reference for understanding and budgeting the system-level geometric location error for curved-path SAR, such as geosynchronous orbit synthetic aperture radar.

A Deep Collaborative Computing Based SAR Raw Data Simulation on Multiple CPU/GPU Platform

The outstanding computing ability of a graphics processing unit (GPU) brings new vitality to the typical computing intensive issue, so does the synthetic aperture radar (SAR) raw data simulation, which is a fundamental problem in SAR system design and imaging research. However, the computing power of a CPU was underestimated, and the tunings for a CPU-based method were missing in the previous works. Meanwhile, the collaborative computing of multiple CPUs/GPUs was not exploited thoroughly. In this paper, we propose a deep multiple CPU/GPU collaborative computing framework for time-domain SAR raw data simulation, which not only introduces the advanced vector extension (AVX) method to improve the computing efficiency of a multicore single instruction multiple data CPU, but also achieves a satisfactory speedup in the CPU/GPU collaborative simulation by fine-grained task partitioning and scheduling. In addition, an irregular reduction based SAR coherent accumulation approach is proposed to eliminate the memory access conflict, which is the most difficult issue in the GPU-based raw data simulation. Experimental results show that the multicore vector extension method greatly improves the computing power of a CPU-based method through about 70× speedup, thereby outperforming the single GPU simulation. Correspondingly, compared with the baseline sequential CPU approach, the multiple CPU/GPU collaborative simulation achieves up to 250× speedup. Furthermore, the irregular reduction based atomic-free optimization boosts the performance of the single GPU method by 20% acceleration. These results prove that the deep multiple CPU/GPU collaborative method is promising, especially for the case of huge volume raw data simulation with a wide swath and high resolution.

Accelerating Time-Domain SAR Raw Data Simulation for Large Areas Using Multi-GPUs

Large areas synthetic aperture radar (SAR) raw data simulation, which contains various actual system errors, is one of the main tasks in SAR system design and development. The growth of swath and resolution results in a significant increase in data volume as well as the simulation time. This poses a challenge for SAR raw data simulation considering system errors. For recent years, the graphics processing unit (GPU)-based scalable parallel method has been applied to raw data simulation. In this paper, we investigate time-domain SAR raw data simulation for large areas on multi-GPUs architecture, which can not only simulate raw data of large areas by task partitioning and scheduling, but also improve the efficiency of current GPU-based algorithm by access conflict optimization and fine-grained parallel pipeline. Experimental results show that the proposed multi-GPUs-based raw data simulation method achieves a 5× speedup compared to the current GPU-based method on single GPU, and a significant over 500× speedup on 4 GPUs compared to traditional CPU-based simulation. These results verify that multi-GPUs-based time-domain method is very suitable for large data volume raw data simulation, especially for the case of wide swath and high resolution.

Information theoretic bounds for compressed sensing in SAR imaging

Compressed sensing (CS) is a new framework for sampling and reconstructing sparse signals from measurements significantly fewer than those prescribed by Nyquist rate in the Shannon sampling theorem. This new strategy, applied in various application areas including synthetic aperture radar (SAR), relies on two principles: sparsity, which is related to the signals of interest, and incoherence, which refers to the sensing modality. An important question in CS-based SAR system design concerns sampling rate necessary and sufficient for exact or approximate recovery of sparse signals. In the literature, bounds of measurements (or sampling rate) in CS have been proposed from the perspective of information theory. However, these information-theoretic bounds need to be reviewed and, if necessary, validated for CS-based SAR imaging, as there are various assumptions made in the derivations of lower and upper bounds on sub-Nyquist sampling rates, which may not hold true in CS-based SAR imaging. In this paper, information-theoretic bounds of sampling rate will be analyzed. For this, the SAR measurement system is modeled as an information channel, with channel capacity and rate-distortion characteristics evaluated to enable the determination of sampling rates required for recovery of sparse scenes. Experiments based on simulated data will be undertaken to test the theoretic bounds against empirical results about sampling rates required to achieve certain detection error probabilities.

Error Analysis of Bistatic SAR Imaging and Stereoscopy Bistatic SAR

The flexible geometry configuration of the bistatic synthetic aperture radar (SAR) has many advantages. However, it causes serious measurement error in the bistatic SAR system, which degrades the quality of the SAR images and the precision of the digital elevation model (DEM) obtained using stereoscopy bistatic SAR. In this paper, the influence of the scene height estimation error, trigger delay, transmitter position measurement error, receiver position measurement error, and transmission line length measurement error are analyzed. These analyses are very useful in bistatic SAR system design. The scene height estimation error, trigger delay, transmitter position measurement error, and synchronization receiver position measurement error affect both the quality of the images and the precision of the DEM obtained by stereoscopy bistatic SAR slightly. The echo receiver position measurement error and transmission line length measurement error affect the quality of the imaging only slightly, but seriously affect the precision of the DEM obtained by stereoscopy bistatic SAR. Luckily, their measurement precision can be quite satisfactory. Simulations and real bistatic experimental results verify the proposed theoretical analysis.

Errata: Digital Beamforming on Receive: Techniques and Optimization Strategies for High-Resolution Wide-Swath SAR Imaging

Synthetic Aperture Radar (SAR) is a well-proven imaging technique for remote sensing of the Earth. However, conventional SAR systems are not capable of fulfilling the increasing demands for improved spatial resolution and wider swath coverage. To overcome these inherent limitations, several innovative techniques have been suggested which employ multiple receive-apertures to gather additional information along the synthetic aperture. These digital beamforming (DBF) on receive techniques are reviewed with particular emphasis on the multi-aperture signal processing in azimuth and a multi-aperture reconstruction algorithm is presented that allows for the unambiguous recovery of the Doppler spectrum. The impact of Doppler aliasing is investigated and an analytic expression for the residual azimuth ambiguities is derived. Further, the influence of the processing on the signal-to-noise ratio (SNR) is analyzed, resulting in a pulse repetition frequency (PRF) dependent factor describing the SNR scaling of the multi-aperture beamforming network. The focus is then turned to a complete high-resolution wide-swath SAR system design example which demonstrates the intricate connection between multi-aperture azimuth processing and the system architecture. In this regard, alternative processing approaches are compared with the multi-aperture reconstruction algorithm. In a next step, optimization strategies are discussed as pattern tapering, prebeamshaping-on-receive, and modified processing algorithms. In this context, the analytic expressions for both the residual ambiguities and the SNR scaling factor are generalized to cascaded beamforming networks. The suggested techniques can moreover be extended in many ways. Examples discussed are a combination with ScanSAR burst mode operation and the transfer to multistatic sparse array configurations.

RMA를 이용한 Spotlight SAR 영상형성 및 품질평가를 위한 시뮬레이터 개발 및 구현

합성 개구면 레이다(SAR: synthetic aperture radar)는 날씨 및 주/야간에 관계없이 고해상도의 영상을 형성할 수 있기 때문에 다양한 분야에서 활용되고 있다. 본 논문에서는 영상 형상 및 품질 평가, 분석을 위한 Spotlight SAR 시뮬레이터를 제안한다. SAR 영상 품질의 예측은 초기 개념 설계 단계부터 최종적인 비행 검증 및 보정 단계에 걸쳐 필수적이다. 제안된 SAR 시뮬레이터는 시스템 설계 변수들에 기반을 두고 있어 전체 시스템 개발과정에서 SAR 영상의 품질을 예측 분석할 수 있다. 이를 위해 영상 획득 기하구조와 다양한 SAR 시스템 설계변수들을 고려하여 이상적인 점표적에 대한 시뮬레이션 원시 데이터를 생성하고 Spotlight 영상 형성 알고리듬을 구현함으로서 점표적 응답특성을 추정한다. 마지막으로 공간 해상도, 최대 부엽 수준, 누적 부엽 수준 등의 주요 품질변수들을 중심으로 생성된 원시 데이터의 영상 품질을 분석한다. Synthetic aperture radar (SAR) is widely used because of high resolution imaging capability in all weather and day/night condition. In this paper development of Spotlight SAR simulator is proposed for image quality analysis. Proposed SAR simulator is based on the SAR system design parameters so that SAR image performance can be expected which is essential throughout the full system development procedure from the initial concept design stage to the final in-flight calibration and validation stage. The raw data of ideal point target is first generated by taking account of the flight and imaging geometry and the various SAR system design parameters, and the Spotlight image formation algorithm is implemented in order to obtain the point target response. Finally the image quality of the generated raw data is analyzed in terms of spatial resolution, peak to sidelobe ratio and integrated sidelobe ratio.

Digital Beamforming on Receive: Techniques and Optimization Strategies for High-Resolution Wide-Swath SAR Imaging

Synthetic Aperture Radar (SAR) is a well-proven imaging technique for remote sensing of the Earth. However, conventional SAR systems are not capable of fulfilling the increasing demands for improved spatial resolution and wider swath coverage. To overcome these inherent limitations, several innovative techniques have been suggested which employ multiple receive-apertures to gather additional information along the synthetic aperture. These digital beamforming (DBF) on receive techniques are reviewed with particular emphasis on the multi-aperture signal processing in azimuth and a multi-aperture reconstruction algorithm is presented that allows for the unambiguous recovery of the Doppler spectrum. The impact of Doppler aliasing is investigated and an analytic expression for the residual azimuth ambiguities is derived. Further, the influence of the processing on the signal-to-noise ratio (SNR) is analyzed, resulting in a pulse repetition frequency (PRF) dependent factor describing the SNR scaling of the multi-aperture beamforming network. The focus is then turned to a complete high-resolution wide-swath SAR system design example which demonstrates the intricate connection between multi-aperture azimuth processing and the system architecture. In this regard, alternative processing approaches are compared with the multi-aperture reconstruction algorithm. In a next step, optimization strategies are discussed as pattern tapering, prebeamshaping-on-receive, and modified processing algorithms. In this context, the analytic expressions for both the residual ambiguities and the SNR scaling factor are generalized to cascaded beamforming networks. The suggested techniques can moreover be extended in many ways. Examples discussed are a combination with ScanSAR burst mode operation and the transfer to multistatic sparse array configurations.

AN OPTIMAL ANTENNA PATTERN SYNTHESIS FOR ACTIVE PHASED ARRAY SAR BASED ON PARTICLE SWARM OPTIMIZATION AND ADAPTIVE WEIGHTING FACTOR

This paper shows that an optimal antenna pattern for active phased array synthetic aperture radar (SAR) has been synthesized to meet the best performances based on particle swarm optimization (PSO) and adaptively selected weighting factors. Because the antenna radiation pattern has a very close relation with the performance of an active phased array SAR system, the authors derived the multi-objective cost functions on the basis of the system performance measures such as the range-to-ambiguity ratio, noise equivalent sigma zero, and radiometric accuracy. The antenna mask templates were derived from the SAR system design parameters in order to optimize the system requirements. To efiectively minimize the cost functions and to search for the amplitude and phase excitations of an active phase array SAR antenna, the authors applied the PSO technique to SAR antenna pattern design and also carefully selected weighting factors to improve the fltness of the cost functions on the basis of the SAR performance.

Performance Comparison of Reflector- and Planar-Antenna Based Digital Beam-Forming SAR

The trend in the conception of future spaceborne radar remote sensing is clearly toward the use of digital beamforming techniques. These systems will comprise multiple digital channels, where the analog-to-digital converter is moved closer to the antenna. This dispenses the need for analog beam steering and by this the used of transmit/receive modules for phase and amplitude control. Digital beam-forming will enable Synthetic Aperture Radar (SAR) which overcomes the coverage and resolution limitations applicable to state-of-the-art systems. On the other hand, new antenna architectures, such as reflectors, already implemented in communication satellites, are being considered for SAR applications. An open question is the benefit of combining digital beam-forming techniques with reflector antennas. The paper answers this question by comparing the system architecture and digital beam-forming requirements of a planar and a reflector antenna SAR. Further elaboration yields the resulting SAR performance of both systems. This paper considers multiple novel aspects of digital beam-forming SAR system design, which jointly flow into the presented system performance.

SAR Sensor Trajectory Deviations: Fourier Domain Formulation and Extended Scene Simulation of Raw Signal

Synthetic aperture radar (SAR) raw signal simulation is a useful tool for SAR system design, mission planning, processing algorithm testing, and inversion algorithm design. A two-dimensional (2-D) Fourier domain SAR raw signal simulator, exploiting the efficiency of fast Fourier transform algorithms, has been presented some years ago and is able to generate the raw signal corresponding to extended scenes. However, it cannot account for the effects of sensor trajectory deviations with respect to the nominal straight-line path. This paper explores the possibility of extending the efficient Fourier domain simulation approach to the case of sensor trajectory deviations, which is more realistic for airborne SAR systems. We first of all obtain a general and compact Fourier domain formulation of the SAR raw signal in the presence of arbitrary trajectory deviations, and show that in this general case no efficient simulation scheme can be devised. However, we demonstrate that, if a narrow beam and slow trajectory deviation assumption is made, a full 2-D Fourier domain simulation can be used. This approach can be applied only to some SAR systems and/or trajectory deviations, but it has the advantage that processing time is practically not increased with respect to the nominal trajectory case. The validity limits of the approach are analytically evaluated. Some simulation results are finally presented in order to verify the effectiveness of the proposed simulation scheme. In another paper, which is the second part of this work, it will be shown that the narrow beam-slow deviation assumption can be relaxed, at the expense of computation efficiency, if a one-dimensional azimuth Fourier domain processing followed by a range time-domain integration is used

Suppressing the azimuth ambiguities in synthetic aperture radar images

A method for removing the azimuth ambiguities from synthetic aperture radar (SAR) images is proposed. The basic idea is to generate a two-dimensional reference function for SAR processing which provides, in addition to the matched filtering for the unaliased part of the received signal, the deconvolution of the azimuth ambiguities. This approach corresponds to an ideal filter concept, where an ideal impulse response function is obtained even in the presence of several phase and amplitude errors. Modeling the sampled azimuth signal shows that the absolute phase value of the ambiguities cannot easily be determined due to their undersampling. The concept of the ideal filter is then extended to accommodate the undefined phase of the ambiguities and also the fading of the azimuth signal. Raw data from the E-SAR system have been used to verify the improvement in image quality obtained by the new method. It has a substantial advantage in enabling the pulse-repetition frequency (PRF) constraints in the SAR system design to be relaxed and also for improving SAR image quality and interpretation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Synthetic Aperture Radar System Design for Random Field Classification

The optimum design of synthetic aperture radar (SAR) systems intended to classify randomly reflecting areas, such as agricultural fields, characterized by a reflectivity density spectral density is studied. Assuming areas of known shape and location, the binary case, and a certain Gaussian signal field property, and ignoring interfield interference, the problem solution is given. The optimum processor includes conventional matched filter processing, but is nonlinear; a coherent optical system realization is outlined. The performance is approximated using a x2 assumption and bounded by the Cernov bound. A fundamental design problem involves the system bandwidth analogously, in a special case, as in diversity communication systems; a solution is given based on the Cernov bound. A set of summary design curves is given and exemplified by a satellite SAR system design. Also discussed is the measurement of reflectivity spectral density amplitude with imaging sidelooking (synthetic or "brute-force") radars and the maximum likelihood estimator's accuracy and realization with a coherent optical system. It is also shown that a CW modulation is useable if the random reflectivity is, effectively, isotropic. Finally, the reflectivity density spectral density amplitude, when constant over the spatial bandpass of the measuring system, is related to the scattering cross-section density commonly measured.