Synthetic Aperture Radar Raw Signal Simulator Research Articles

The Open-Source Framework for 3D Synthetic Aperture Radar Simulation

Synthetic Aperture Radar (SAR) simulation is widely used for system design, processing techniques development, and mission planning. However, there is no readily available and free framework for SAR raw signal simulation, and many teams and organizations struggle with developing their own simulator from scratch, repeating work that others have done earlier. This work’s purpose is to create a simple, open-source SAR simulation framework that can be used for many purposes and is available for free to everyone. It is a ready tool for SAR processing techniques verification, and thanks to its open-source nature, it fosters collaboration between scientists, both on the simulation and the tool development. Moreover, as the simulation’s underlying mathematics is described in detail in this article, it may serve as a handbook for the radar’s simulation. The simulator was prepared as a stand-alone, multiplatform software working in the Matlab/Octave environment. It is available in an online software repository that allows others to contribute to the original code or to create forks of it. The simulator supports monostatic, bistatic, and multistatic configurations with shadowing. The surface model includes roughness using the modified Phong model, transparency, and complex reflectivity. The antenna pattern is defined with a general two-dimensional model. The article is concluded with the simulator’s demonstrations, including antenna pattern, Doppler shift, and various surface parameters. It is expected that this simulator will be widely adopted and improved by many collaborators.

Raw Signal Simulator for SAR With Trajectory Deviation Based on Spatial Spectrum Analysis

This paper presents a whole new method for simulating a raw signal of synthetic aperture radar (SAR) with trajectory deviation. In this paper, a SAR raw signal is viewed as a spatial function in terms of radar location, at a fixed range frequency component of the radar signal. It is disclosed and verified that the SAR raw signals is band limited from the perspective of spatial spectrum analysis. Based on this finding, SAR raw signals under condition of trajectory deviation are obtained by interpolating the SAR raw signal along a set of ideally linear trajectories. The unprecedent performance achieved by the new method mainly includes the following. First, it provides a way to update existing simulators designed for ideally linear trajectory, giving them the capability to take trajectory deviation into consideration. Second, it is an efficient SAR raw signal simulator whose validity limit is greatly expanded compared with existing efficient simulators, as many constraints are eliminated without sacrificing computational efficiency or phase accuracy. Third, it is a uniform framework applicable for multiple SAR acquisition modes. Finally, the computational complexity of Monte Carlo experiment under various trajectory deviations is dramatically reduced, at the expense of storage memory requirement. Theoretical analyses are demonstrated by experimental results.

A Unified Multimode SAR Raw Signal Simulation Method Based on Acquisition Mode Mutation

Raw signal simulators for synthetic aperture radar (SAR) in different acquisition modes have been studied individually. This letter is dedicated to presenting a method for simulating multimode SAR raw signal in a unified framework. To this end, we first simulate stripmap SAR raw signal, and then mutate the raw signal from stripmap mode into the desired acquisition mode. The acquisition mode mutation is implemented by azimuth-time-variant and range-frequency-dependent bandpass filtering. While processing in range-frequency domain brings forth high accuracy, processing in azimuth-time domain makes the method applicable for flexible antenna steering laws specified by multiple SAR acquisition modes, such as staring spotlight mode, sliding spotlight mode, and terrain observation by progressive scans mode. The proposed method is validated by the simulation results.

A new metric for measuring structure-preserving capability of despeckling of SAR images

In this paper, a new metric called despeckling structure loss (DSL) is proposed for performance assessment of despeckling algorithms with a focus on the preservation of structural features such as edges and textures. The ratio image of a synthetic aperture radar (SAR) image to its despeckled result can clearly indicate the loss of structural features caused by the despeckling process. By taking into account characteristics of the best and worst structure preservation in despeckling, the DSL metric examines the presence of structural features in ratio images by using local correlations between the ratio image and the noise-free reference image at edge points. The DSL is shown to be a monotonic function of structure loss bounded between the best and worst cases, leading an objective and quantitative measure of the structure-preserving capability of despeckling algorithms. Experimental evaluations of the proposed metric have been carried out on simulated SAR images including one generated by SAR raw signal simulator. Despeckled results using five typical algorithms clearly demonstrate the efficiency of the DSL metric. In comparison, the commonly used despeckling metrics including the signal-to-mean-square error ratio, the edge correlation index, the Pratt’s figure of merit, the structural similarity and the equivalent number of looks of ratio images, fail to keep a consistency with the structure loss shown in despeckled results as well as ratio images.

Efficient strip-mode SAR raw signal simulation of mixed targets based on accurate 2-D spectrum

An accurate and efficient Synthetic Aperture Radar (SAR) raw data generator is of considerable value for testing system parameters and verifying imaging algorithms. Nevertheless, the existing simulator cannot exactly handle the case of the fast moving targets in high squint geometry. As for the issue, the analytical expression for the two Dimensional (2-D) signal spectrum of moving targets is derived and a fast raw echo simulation method is proposed in this study. The proposed simulator can accommodate the moving targets in the high squint geometry, whose processing steps of the simulation are given in detail and its computational complexity is analyzed. The simulation data for static and moving targets are processed and analyzed, and the results are given to validate the effectiveness of the proposed approach.

Efficient and precise frequency-modulated continuous wave synthetic aperture radar raw signal simulation approach for extended scenes

Frequency-modulated continuous wave (FMCW) synthetic aperture radar (SAR) system is widely used for earth observation and space detection, where short revisits time at low cost are desirable, or small size is required. Therefore a FMCW SAR raw signal simulator is required to quantitatively support the design of a SAR mission operating in the FMCW mode, to help mission planning, test processing algorithms and analyse jamming and noises. Time-domain SAR raw signal simulation can be easily conceived, but it is extremely time and memory consuming. In this study, an efficient FMCW SAR raw signal simulation approach for extended scene is proposed based on chirp-Z transform (CZT). This is the first time that a FMCW SAR simulator is proposed in the two-dimensional frequency domain. By taking advantage of fast Fourier transform, the proposed approach highly reduces the computational load with respect to the time domain approach. Furthermore, CZT algorithm can accurately simulate the range-variation of the range cell migration term, which guarantees the precision of the proposed approach. Wavenumber domain algorithm is applied to focus the conceived raw signal. Finally, point targets, the electromagnetic imaging and real FMCW image are used to validate the proposed simulation approach.

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).

Real extended scene and moving target multi-channel SAR raw signal simulation

A real extended scene and moving targets multi-channel Synthetic Aperture Radar (SAR) raw signal simulator accounting for Inertial Navigation System (INS) errors and antenna patterns is presented in this paper. INS errors are obtained by solving INS error differential equations with Runge-Kutta method. A high resolution SAR image is used to estimate the complex reflectance of real extended scene. Extended scene and moving target are simulated separately and then are superposed in time domain. The simulated multi-channel SAR data can be used for development of multi-channel SAR Ground Moving Target Indication (SAR-GMTI) and also can be used for development of SAR motion compensation.

A Novel Approach for Disaster Monitoring: Fractal Models and Tools

In this paper, we present a complete framework to support the monitoring of natural and man-made disasters by means of synthetic aperture radar (SAR) images. The fractal geometry is the most appropriate mathematical instrument in describing the irregularity of a natural observed scene, by means of few effective and reliable parameters. Therefore, fractal concepts can be used to model and identify geometrical changes that occurred in areas hit by disasters. We present an overall framework employing fractal-based models, algorithms, and tools to support the identification of natural area changes due to natural or man-made disasters. Such a framework includes an algorithm used to extract fractal parameters from a 2-D signal, a fractal interpolation tool, and a SAR raw-signal simulator. The combined use of these tools provides an innovative instrument for disaster monitoring applications. In this paper, we implement the fractal framework to obtain a relation between the fractal parameters of a SAR image and those of the relative imaged area. In addition, a case study is discussed, showing the potentiality of our framework for flooding detection

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

Efficient spotlight sar raw signal simulation of extended scenes

Synthetic aperture radar (SAR) raw signal simulation is a powerful tool for designing new sensors, testing processing algorithms, planning missions, and devising inversion algorithms. In this paper, a spotlight SAR raw signal simulator for distributed targets is presented. The proposed procedure is based on a Fourier domain analysis: a proper analytical reformulation of the spotlight SAR raw signal expression is presented. It is shown that this reformulation allows us to design a very efficient simulation scheme that employs fast Fourier transform codes. Accordingly, the computational load is dramatically reduced with respect to a time-domain simulation and this, for the first time, makes spotlight simulation of extended scenes feasible.

SAR raw signal simulation for urban structures

A synthetic aperture radar (SAR) raw signal simulator for urban scenes is presented along with models it employs to compute the backscattered field and to account for the imaging radar sensor characteristics. Urban areas are represented as a set of dielectric buildings placed over a random rough nonflat dielectric terrain. The adopted models allow evaluation of the raw signal on a sound physical and mathematical background: the scattering model employs the Kirchhoff approach appropriately extended to include multiple-reflection effects, and the radar model operates in the two-dimensional Fourier transformed domain. Details to assess how and why the simulator is also efficient with respect to the computational time are provided. In addition, relevant examples are discussed to show the simulator potentialities and assess the validity of the main results. It is shown that the simulator is able to quantitatively assess performances of SAR sensors over urban structures. The proposed simulator turns out to be also useful to train numerical schemes devoted to feature extraction, and to test any specific SAR processing technique. Comments for further developments of the simulation tool are presented.

SAR raw signal simulation of oil slicks in ocean environments

Synthetic aperture radar (SAR) raw signal simulation is a powerful tool for design of oil slick detection and interpretation systems. In this paper, the ocean simulation issues are presented, and the main problems relating to the oil presence on the sea surface are treated. Attention is focused on the electromagnetic side of the problem, taking account of the sensor signatures, the dielectric, physical-chemical, and geometric nature of the oil slick, and the environmental conditions. The presented SAR simulator is based on an ocean model and an oil slick model. The former makes use of multiscale description of the ocean surface: the distributed surface model for the SAR-ocean interaction is considered by taking into account the nonlinear hydrodynamic effect for the water particle movement. The latter model implements a modification of the ocean spectrum, based on the Marangoni theory and accounting for the nonlinear wave interaction mechanism. However, the proposed SAR raw signal simulator is modular and flexible, thus allowing other possible physical models for modeling the oil slick effect over the ocean spectrum. Meaningful SAR simulation experiments are presented and discussed, elucidating the role of difference on pollutants, oil thickness, wind speed and direction, incident wavelength and angle and other radar parameters. Validation of the simulator is also presented by comparison with experimental data. A striking conclusion of the paper is that higher order moments (from the second on) of oil slick SAR image statistics are quite different compared to those pertinent to an equivalent wind speed decrease on the imaged area. This suggests a convenient way to define new appropriate oil slick signatures.

SAR raw signal simulation of actual ground sites described in terms of sparse input data

Deals with the simulation of synthetic aperture radar (SAR) raw signal of actual ground sites described in terms of sparse input data. Since in most cases the input data reference system does not match SAR requirements, it is necessary to adopt appropriate interpolation schemes. The authors focus their attention on elevation input data, noting that natural surfaces exhibit fractal properties. Fractal and nonfractal interpolation schemes are discussed and applied. Simulated images are shown and compared to actual examples. Subjective and objective tests validate the simulation and support the fractal-based elevation interpolation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>