Simulated Raw Data Research Articles

Reproducibility of the adaptive thresholding calibration procedure for the delineation of 18F-FDG-PET-positive lesions

The aim of the study was to evaluate the robustness of the calibration procedure against the counting statistics and lesion volumes when using an adaptive thresholding method for the delineation of 2-[18F]fluoro-2-deoxyglucose (18F-FDG)-PET-positive tissue. Three data sets obtained from physical and simulated images of a phantom containing hot spheres of known volume and contrast were used to study the robustness of the calibration procedure against the counting statistics and range of volumes and contrasts for a given PET model. The mathematical expression of the adaptive thresholding method used corresponds to a linear relationship between the optimal threshold value and the inverse of the local contrast. Robustness was evaluated by testing whether the slopes and intercepts of the linear expression found under two experimental conditions were significantly different (P<0.05). It was found that the calibration step was not sensitive to the PET device for the studied PET model, nor to the counting statistics for a signal-to-noise ratio higher than 5.7. No statistical difference was found in the calibration step when using a wide range of volumes (0.2-200 ml) and contrasts (2.0-20.6) or more restricted ones (0.43-97.3 ml and 2.0-7.7, respectively). Therefore, a calibration procedure using limited experimental conditions can be applied to a wider range of volumes and contrasts. These results show that the manufacturer could propose simulated or experimental raw data corresponding to a given PET model with high counting statistics, allowing each clinical center to reconstruct calibration images according to the algorithm parameters used in the clinic.

EFFICIENT STRIP-MODE SAR RAW DATA SIMULATOR OF EXTENDED SCENES INCLUDED MOVING TARGETS

An accurate and e-cient 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 e-cient 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 !-• algorithm is proposed in this paper, where the inverse STOLT interpolation is applied to simulate the range-azimuth couple. So it is more e-cient 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 efiectiveness.

NEW DEVELOPMENT OF TWO-STEP PROCESSING APPROACH FOR SPOTLIGHT SAR FOCUSING IN PRESENCE OF SQUINT

This paper analyzes the azimuth spectrum folding problem which arises from the dependence of the Doppler centroid on range frequency in squinted spotlight synthetic aperture radar (SAR). Based on the analysis, a novel approach for squinted spotlight SAR is proposed in this paper. In this approach, an azimuth preprocessing step including a deramping operation and an operation of azimuth spectrum replicating and flltering is introduced to eliminate spectrum folding problem. Then, a modifled Range Migration Algorithm (RMA) is adopted to process the preprocessed data. This approach extends the focusing capacity of traditional two-step processing approach from broadside spotlight SAR to squinted case. Moreover, this approach is e-cient due to a limited azimuth data extension to resolve the spectrum aliasing problem. Experimental results on simulated raw data validate the proposed approach.

TOPS Mode Raw Data Generation From Wide-Beam SAR Imaging Modes

A synthetic aperture radar (SAR) raw data simulator of distributed target scenes is an important tool for testing the system parameters, imaging algorithms, and so on, particularly for these recently proposed novel imaging modes. The Terrain Observation by Progressive Scans (TOPS) mode achieves the wide-swath imaging coverage and overcomes major drawbacks in ScanSAR by electronically steering the azimuth beam along track during the whole acquisition time. In this letter, a novel TOPS mode raw data generation approach from conventional wide-beam SAR imaging modes is proposed, by invoking the fact that the TOPS raw data can be considered as a part of the stripmap/spotlight raw data with the exploited wide azimuth beam interval. In this approach, an azimuth-varying filter is introduced to obtain the desired TOPS raw data and set others to zero. Moreover, the conventional stripmap and spotlight mode raw data can be efficiently generated in the 2-D Fourier transformed domain. Therefore, a fast raw data simulator can be easily achieved by taking this approach. Simulation results validate the proposed simulation approach.

Hybrid general-purpose computation on GPU (GPGPU) and computer graphics synthetic aperture radar simulation for complex scenes

In this paper, a new hybrid general-purpose computation on GPU (GPGPU) and computer graphics synthetic aperture radar (SAR) simulation method for complex scenes is proposed. Previous SAR simulations for complex scenes only use GPU’s graphics capabilities for scattering calculation in graphical electromagnetic computing (GRECO) algorithm. The new hybrid method use GPU’s graphics and parallel computing capabilities for geometry modeling, scattering map and raw data calculation in SAR simulation of complex scenes. The advantages of the new method rely on the three contributions: GPU hardware provides lots of stream processors for threads calculating, common unified device architecture (CUDA) environment runs thousands of threads working in parallel for assigned task, raw data simulation adopts the fine-grained task parallelism. Compared with classical algorithms, the method not only ensures the accuracy of scattering calculation with GRECO algorithm, but also improves the computational efficiency greatlyfor complex scenes consideration. The results show that the method is able to obtain the speedup about 30 times on entry-level GPU. Key words: Synthetic aperture radar (SAR), raw data simulation, parallel processing, general-purpose computation on GPU (GPGPU), computer graphics.

Efficient Spaceborne TOPS Mode SAR Raw Signal Simulation of Extended Scenes

The SAR raw signal simulator in the time domain by the target-by-target method is inefficient, while the simulator in the two-dimensional (2-D) frequency domain can not be directly used to generate the Terrain Observation by Progressive Scans (TOPS) raw data. As for this issue, an efficient TOPS raw data simulation approach is proposed. In the range direction, the 1-D convolution between echoes of referenced point target and scattering coefficient of the imaged scene is introduced, while raw data is simulated and stored by the pulse-by-pulse method in azimuth. The processing steps of the simulator are given in detail, and its computational complexity is analyzed. Simulated echoes of the proposed simulator and the accurate time domain simulator are compared. Finally, the imaging and interferometry results of the simulated data are given to validate the effectiveness of the proposed approach.

EFFICIENT GEOSYNCHRONOUS CIRCULAR SAR RAW DATA SIMULATION OF EXTENDED 3-D SCENES

Geosynchronous Circular Synthetic Aperture Radar (GeoCSAR) has the Circular SAR conflguration and undergoes a near- ellipse geosynchronous track rather a \8-like track of conventional GeoSAR. It could produce three dimensional (3-D) images of extended Earth scenes. GeoCSAR raw data simulator is of vital for predicting system performance, developing suitable data processing algorithms, etc.. It should include degrading conditions such as motion instability, angular deviations and orbit perturbations in order to approach the real situation. The common generation algorithm of raw data in time domain is precise but time-consuming for extended 3-D scene. In this paper, a novel raw data simulation algorithm based on inverse Improved Polar Format Algorithm (IPFA) for GeoCSAR was proposed, which possessed both the advantages of precision of time domain simulator and e-ciency of frequency domain simulator. Implementation details were presented, and several simulation results were provided and analyzed to validate the algorithm.

BISTATIC FMCW SAR RAW SIGNAL SIMULATOR FOR EXTENDED SCENES

By mounting the transmitter and receiver of Frequency Modulated Continuous Wave (FMCW) Synthetic Aperture Radar (SAR) system on separate platforms, bistatic FMCW SAR ofiers more considerable capabilities, reliability and ∞exibility while maintaining the small size, low cost and agile reaction. The bistatic FMCW SAR raw signal simulator is highly required to quantitatively support the design of bistatic FMCW SAR, to help mission planning, test processing algorithms, and analyze jamming and noises. Bistatic FMCW SAR raw signal can be exactly simulated target-by-target in time domain but with extremely time and memory consuming, especially when extended scenes are considered. In this paper, bistatic FMCW SAR signal model and Bistatic Point Target Reference Spectrum (BPTRS) is proposed, based on which a raw signal simulator is developed in the 2-D frequency domain for the flrst time, where Chirp-Z Transform (CZT) is used to formulate the range migration terms. By taking advantage of Fast Fourier Transform (FFT), the proposed raw signal simulator highly reduces the computational load with respect to the time domain approach. The simulated raw data is verifled by analyzing the corresponding images focused by Range Doppler Algorithm (RDA).

Symdas - Raw Data Simulator for the Radar with Electronically Controlled Beam

Symdas - Raw Data Simulator for the Radar with Electronically Controlled Beam The subject of the paper is the software simulator of baseband signals received in a radar. These synthetic signals are sent to the DSP unit responsible for target detection and estimation. The software has been developed in Warsaw University of Technology as a part of R&amp;D project, and its main purpose is to allow flexible testing and validation of the algorithms running in DSP processors of the new radar.

Internal Calibration for Stepped-Frequency Chirp SAR Imaging

For synthetic aperture radar imaging, stepped-frequency chirp signals are widely used to obtain high range resolution. One advantage of the approach is the reduction of the instantaneous bandwidth and sampling rate requirements of the radar system. To reconstruct the spectrum of a wideband signal, the amplitude and phase discontinuity between contiguous pulses should be removed. Otherwise, the discontinuity will defocus the range profile and degrade the range resolution. In this letter, a detailed internal calibration technique combined with stepped-frequency mode is proposed to eliminate the discontinuity and thus improve the focusing quality of the final image. The simulation and real raw data experiments are performed to validate the proposed method.

Efficient Stripmap SAR Raw Data Generation Taking Into Account Sensor Trajectory Deviations

In this letter, a simulation procedure for airborne stripmap synthetic aperture radar with zero squint angle is proposed. The procedure is based on the idea of inverse processing and 1-D summation. It utilizes narrow bandwidth approximation and is more efficient compared to a time-domain simulator. Moreover, it allows for the simulation of raw data for higher aperture angle configurations compared to existing approaches. The effectiveness of the approach is demonstrated by means of examples for point scatterers.

Fast Algorithms for SAR Raw Data Simulation with Large Squint Angles

Fast Algorithms for SAR Raw Data Simulation with Large Squint Angles

PO/MEC-BASED SCATTERING MODEL FOR COMPLEX OBJECTS ON A SEA SURFACE

In this contribution a model based on asymptotic methods is proposed to compute the scattered fleld from complex objects on a sea surface. The scattering model combines the geometrical optics, the physical optics and the method of equivalent currents. It includes the shadowing efiects and multiple-bounce up to order 3. This model is used, in the following, for Radar Cross Section (RCS) estimation and to generate Synthetic Aperture Radar (SAR) raw data for imaging applications. The theoretical aspects are reviewed in this paper and the proposed model is detailed. Numerical results are provided to validate the approach through the computation of RCS for canonical objects and complex scenes. Both the bistatic and the monostatic conflgurations are studied in this work. Finally some flrst results dealing with SAR imaging of objects on a sea surface are provided. These images are constructed from the simulated raw data thanks to a chirp scaling-based algorithm.

A study of spaceborne SAR raw data compression error based on a statistical model of quantization interval transfer probability

SAR raw data signal to noise ratio (SNR) after compression is of great importance since the choice of compression ratio is dependent on it during SAR system design and application analysis. The signal to quantization noise ratio (SQNR) generally used may not precisely indicate the relationship between signal and noise. Considering the thermal noise, a statistical model of quantization interval transfer probability is proposed in this paper. SNR mapping between SAR raw data before analog to digital converter (ADC) and after block adaptive quantization (BAQ) over the whole set of saturation degree is obtained using this model. When the power of echo is small with low SNR, after 1, 2, 3 or 4 bits BAQ compression, SNR has tiny difference among the four compression levels. When the power of the echo is medium with higher SNR, the SNR degradation after BAQ is about 5 dB with each bit decreasing from 4 bits. If voltage of the echo is higher than the clipping point of ADC, SNR after ADC and BAQ degrades stepwise. The higher the saturation degree of SAR raw data, the worse the SNR is. Simulated Gaussian data and real SAR raw data are used to verify the theoretical results, which are useful in the choice of BAQ compression ratio and further application analysis.

Time Domain SAR Raw Data Simulation of Distributed Targets

In this paper, a time domain stripmap mode Synthetic Aperture Radar (SAR) raw data simulation including both the terrain and the targets is proposed. The simulator generates SAR raw data of a scene, involving both single and double reflections in a computationally efficient manner. The inputs of the simulator are the digital elevation model of the terrain, the 3D target model, and the parameters of the SAR system. The simulator extracts a geometrically accurate reflectivity map and generates the SAR raw data in time domain. The disadvantage of time domainmethod is justified to be tolerable by presenting experiments onmodularity performance of the simulator. Also a novel method to decrease the time domain computational complexity of the SAR raw data generation is proposed. Our method has showed very promising results in representing the scattering characteristics, the raw data, and the time domain simulation flexibility.

Using fit functions in computational dielectric spectroscopy.

This work deals with the development of an appropriate set of fit functions for describing dielectric spectra based on simulated raw data. All these fit functions are of exponential character with properly chosen cofunctions. The type of the cofunctions is different for translation, rotation and their coupling. As an alternative to multiexponential fits we also discuss Kohlrausch-Williams-Watts functions. Since the corresponding Fourier-Laplace series for these stretched exponentials has severe convergence problems, we represent their Fourier-Laplace spectrum as a Havriliak-Negami expression with properly chosen parameters. A general relation between the parameter of the Kohlrausch-Williams-Watts and the Havriliak-Negami parameters is given. The set of fit functions is applied to the concrete simulation of the hydrated ionic liquid 1-ethyl-3-methyl-imidazolium triflate with H(2)O. The systematic variation of the water mole fraction permits to study the gradual transition from a neutral molecular liquid to molecular ionic liquids.

A Bistatic SAR Raw Data Simulator Based on Inverse $ \omega{-}k$ Algorithm

A synthetic aperture radar (SAR) raw data simulator is an important tool for testing the system parameters and the imaging algorithms. In this paper, a scene raw data simulator based on an inverse ω-k algorithm for bistatic SAR of a translational invariant case is proposed. The differences between simulations of monostatic and bistatic SAR are also described. The algorithm proposed has high precision and can be used in long-baseline configuration and for single-pass interferometry. Implementation details are described, and plenty of simulation results are provided to validate the algorithm.

Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body $^{18}{\hbox{F-FDG}}$ Distributions for Oncology Applications

The purpose of the work described in this paper was the development of a framework for the creation of a realistic positron emission tomography (PET) simulated database incorporating patient-specific variability. The ground truth used was therefore based on clinical PET/computed tomography (CT) data of oncology patients. In the first step, the NURBS-based cardiac-torso phantom was adapted to the patient's CT acquisitions to reproduce their specific anatomy while the corresponding PET acquisitions were used to derive the activity distribution of each organ of interest. Secondly, realistic tumor shapes with homogeneous or heterogeneous activity distributions were modeled based on segmentation of the PET tumor volume and incorporated in the patient-specific models obtained at the first step. Lastly, patient-specific respiratory motion was also modeled. The derived patient-specific models were subsequently combined with the PET SORTEO Monte Carlo simulation tool for the simulation of the whole-body PET acquisition process. The accuracy of the simulated datasets was assessed in comparison to the original clinical patient images. In addition, a couple of applications for such simulated images were also demonstrated. Future work will focus on the creation of a comprehensive database of simulated raw data and reconstructed whole-body images, facilitating the rigorous evaluation of image-processing algorithms in PET for oncology applications.

A RESIDUE-PAIRING ALGORITHM FOR INSAR PHASE UNWRAPPING

Phase unwrapping is a key problem to generate digital elevation maps (DEMs) by synthetic aperture radar (SAR) interfer- ometry. A lot of phase unwrapping algorithms have been proposed to solve this problem. However, in noisy region, many unwrapping algo- rithms are inoperative because of the denseness of residues. In this paper, we propose a path following phase unwrapping method, namely Residue-Pairing (RP) algorithm. The algorithm starts from residues, based on the aggregate of coordinates of each positive residues (or neg- ative residues), to search the nearest opposite polar residue and con- nect them. Compared to the Goldstein's algorithm, the brunch cuts produced by this algorithm can efiectively decrease their total length and contract the isolated region especially in noisy region. With raw data simulation, the results conflrm the validity of RP algorithm in dense-residues region.

Comparison of One-Dimensional and Two-Dimensional Least-Squares Strain Estimators for Phased Array Displacement Data

In this study, the performances of one-dimensional and two-dimensional least-squares strain estimators (LSQSE) are compared. Furthermore, the effects of kernel size are examined using simulated raw frequency data of a widely-adapted hard lesion/soft tissue model. The performances of both methods are assessed in terms of root-mean-squared errors (RMSE), elastographic signal-to-noise ratio (SNRc) and contrast-to-noise ratio (CNRc). RMSE analysis revealed that the 2D LSQSE yields better results for phased array data, especially for larger insonification angles. Using a 2D LSQSE enabled the processing of unfiltered displacement data, in particular for the lateral/horizontal strain components. The SNRc and CNRc analysis showed an improvement in precision and almost no loss in contrast using 2D LSQSE. However, the RMSE images for different kernel sizes revealed that the optimal 2D kernel size depends on the region-of-interest and showed that the LSQ kernel size should be limited to avoid loss in resolution.