SARAS: a synthetic aperture radar (SAR) raw signal simulator

Franceschetti, G.; Migliaccio, M.; Riccio, Daniele; Schirinzi, Gilda

doi:10.1109/36.124221

Cited by 326 publications

(175 citation statements)

References 14 publications

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“…We recommend point targets simulation to be used for imaging index (e.g., PSLR and ISLR) computation, with the heterogeneous parallel time domain correlation echo generation method, although the truncated error with heterogeneous parallel frequency domain correlation is very small and can be ignored in most instances. For large scale 3-D distributed imaging scene simulation, heterogeneous parallel frequency domain correlation echo generation method is the best choice [32,33].…”

Section: Heterogeneous Parallel Echo Generation Simulation Applicabilitymentioning

confidence: 99%

“…This is caused by the sample depth computation and judgment for so many targets in the imaging scene. We perform wave propagation dimensional FFT to Equation (2) with variable t. Then the echo signal is modeled in wave propagation frequency domain [32,33]. (3) where, is the carrier frequency, is the baseband frequency, S( ) = exp (−j ) × exp (j ) is the FFT of the chirp transmitted signal.…”

Section: Heterogeneous Parallel Echo Generation Simulation With Frequmentioning

confidence: 99%

“…The time domain correlation method for echo generation is precise and easy, while being quite time consuming, which is suitable for point targets simulation. The frequency domain correlation method for DLSLA 3-D SAR echo generation is computation efficient, which is very suitable for 3-D distributed scene simulation [32,33]. The heterogeneous parallel DLSLA 3-D SAR image reconstruction simulation, with the 3-D polar format algorithm [34], polar formatting and an L1 regularization algorithm [35], is performed with wave front curvature phase error compensation.…”

Section: Introductionmentioning

confidence: 99%

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Airborne Downward Looking Sparse Linear Array 3-D SAR Heterogeneous Parallel Simulation

et al. 2013

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Abstract:The airborne downward looking sparse linear array three dimensional synthetic aperture radar (DLSLA 3-D SAR) operates nadir observation with the along-track synthetic aperture formulated by platform movement and the cross-track synthetic aperture formulated by physical sparse linear array. Considering the lack of DLSLA 3-D SAR data in the current preliminary study stage, it is very important and essential to develop DLSLA 3-D SAR simulation (echo generation simulation and image reconstruction simulation, including point targets simulation and 3-D distributed scene simulation). In this paper, DLSLA 3-D SAR imaging geometry, the echo signal model and the heterogeneous parallel technique are discussed first. Then, heterogeneous parallel echo generation simulation with time domain correlation and the frequency domain correlation method is described. In the following, heterogeneous parallel image reconstruction simulation with two imaging algorithms, e.g., 3-D polar format algorithm, polar formatting and L1 regularization algorithm is discussed. Finally, the point targets and the 3-D distributed scene simulation are demonstrated to validate the effectiveness and performance of our proposed heterogeneous parallel simulation technique. The 3-D distributed scene employs airborne X-band DEM and P-band Circular SAR image of the same area as simulation scene input.

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Section: Heterogeneous Parallel Echo Generation Simulation Applicabilitymentioning

confidence: 99%

Section: Heterogeneous Parallel Echo Generation Simulation With Frequmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Airborne Downward Looking Sparse Linear Array 3-D SAR Heterogeneous Parallel Simulation

et al. 2013

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“…The speckle can be directly applied to the image, but it does not consider the filtering properties of the SAR system [30]. Franceschetti et al [31,32] used a statistical model for considering speckle in the simulation. Some moving target simulation methods neglected the range dependence of the signal model for non-stationary targets [33] or the azimuth component of the target velocity [34].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Method for Simulation of Synthetic Aperture Radar (SAR) Raw Data in Moving Target Detection

Rahmanizadeh

Amini

2017

Remote Sensing

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SAR (Synthetic Aperture Radar) raw data simulation has a significant role in the evaluation of newly-proposed methods for the estimation of moving target parameters. The evaluation of methods in different cases emphasizes the importance of the need to have fast simulators. Using reverse SAR imaging methods for the raw data simulations has achieved good results in the simulation of the static targets, but for the simulation of moving targets these methods have a few shortcomings. In this paper, we propose a method to simulate a speckled scene with moving targets in the hybrid domain. First, the scene is simulated, including speckle, which is statistically in accordance with real SAR image behavior. Then, a reverse imaging algorithm (inverse chirp scaling) was applied on the scene to generate the SAR raw data. The moving target simulation was also done in the time-domain as the next step. Finally, the results from two prior steps were superposed to generate the SAR raw data with moving targets. All steps of the proposed method were evaluated separately. The speckle procedure was evaluated by comparing the speckled SAR image before the simulation and the image of the SAR simulated raw data. The results show similar variations in real and imaginary parts of these data. The correlation between the reflectivity map and the SAR images after the simulation was calculated and the obtained correlation coefficient was about 0.95 for different images. The final data were further analyzed for the displacement of moving targets' positions. The results show similar displacement between moving target SAR raw data with a background and without a background.

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“…The ground moving targets indication (GMTI) is one of the most important applications for synthetic aperture radar [7][8][9][10], and the performance of the GMTI system can be analyzed and evaluated by modeling the whole system through simulation method. SAR raw data generator is essential for designing the new sensor, testing the imaging algorithm and devising inversion algorithm, so the raw data simulator is a hot issue in the research of SAR [11][12][13][14][15][16][17][18][19][20][21]. However, only static targets are taken into account in existing simulators while the moving targets are rarely discussed.…”

Section: Introductionmentioning

confidence: 99%

Efficient Strip-Mode Sar Raw Data Simulator of Extended Scenes Included Moving Targets

Yang¹,

Yu²,

Luo³

et al. 2013

PIER B

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Abstract-An accurate and efficient SAR raw data generator is of considerable value for testing system parameters and the imaging algorithms. However, most of the existing simulators concentrate on the raw signal simulation of the static extended scenes and targets. Actually the raw signal simulator of the moving targets is highly desired to quantitatively support the application of the ground moving targets indication. The raw data simulation can be exactly realized in the time domain but not efficient especially when simulating an extended scene. As for the issues, the analytical expression for the 2-D signal spectrum of moving targets with constant acceleration is derived and a fast raw data simulation method in the 2-D frequency domain based on inverse ω-κ algorithm is proposed in this paper, where the inverse STOLT interpolation is applied to simulate the range-azimuth couple. So it is more efficient than the time domain one by making use of Fast Fourier Transform (FFT). Simulation results for a man-made scene and a real SAR scene are provided to demonstrate its validity and effectiveness.

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SARAS: a synthetic aperture radar (SAR) raw signal simulator

Cited by 326 publications

References 14 publications

Airborne Downward Looking Sparse Linear Array 3-D SAR Heterogeneous Parallel Simulation

Airborne Downward Looking Sparse Linear Array 3-D SAR Heterogeneous Parallel Simulation

An Integrated Method for Simulation of Synthetic Aperture Radar (SAR) Raw Data in Moving Target Detection

Efficient Strip-Mode Sar Raw Data Simulator of Extended Scenes Included Moving Targets

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