Point Target Simulation Research Articles

Weighted Capon beamformer combined with coded excitation in ultrasound imaging.

Capon-based beamformers are well-known methods to improve the SNR and quality of medical ultrasound images. Furthermore, they can improve the resolution of the images unexpectedly more than conventional DAS beamformers. Another method used in radar, sonar, and ultrasound imaging to increase the SNR is coded excitation with linear frequency-modulated signal (chirp). In this paper, we illustrate that the combination of coded excitation with a Capon beamformer provides better resolution and higher SNR. However, this combination suffers from high sidelobe levels. We propose a weighted Capon beamformer (WCB) with chirp excitation to suppress the sidelobes and obtain a higher contrast with approximately the same resolution as the standard Capon beamformer (SCB). The weights of the WCB are obtained using element-wise multiplication of the weights of the SCB and a desired window (Hanning) with the same dimension. The results show a 20 dB reduction in the sidelobe levels in simulated point targets and a 6 dB increase in background contrast in simulated cyst phantoms.

Comparison of two‐step and one‐step motion compensation algorithms for airborne synthetic aperture radar

Airborne synthetic aperture radar (SAR) image quality considerably degrades because of motion errors. High-precision motion compensation (MOCO) is necessary in an advanced SAR data processing scheme. In the case of ultra-high resolution, the conventional two-step MOCO algorithm introduces significant range cell migration correction (RCMC) error which causes a loss to resolution. Another method named one-step MOCO can avoid RCMC error, improving image quality obviously. Meanwhile, one-step MOCO can well integrate with the standard Omega-K algorithm succinctly. A comparison of the two MOCO algorithms is demonstrated by analysing the RCMC error. Point targets simulation has validated the proposed research.

Adaptive diagonal loaded minimum variance beamforming applied to medical ultrasound imaging

In order to enhance the robustness and contrast in the minimum variance (MV) beamformer, adaptive diagonal loading method was proposed. The conventional diagonal loading technique has already been used in the MV beamformer, but has the drawback that its level is specified by predefined parameter and without consideration of input-data. To alleviate this problem, the level of diagonal loading was computed appropriately and automatically from the given data by shrinkage method in the proposed adaptive diagonal loaded beamformer. The performance of the proposed beamformer was tested on the simulated point target and cyst phantom was obtained using Field II. In the point target simulation, it is shown that the proposed method has higher lateral resolution than the conventional delay-and-sum beamformer and could be more robust in estimating the amplitude peak than the MV beamformer when acoustic velocity error exists. In the cyst phantom simulation, the proposed beamformer has shown that it achieves an improvement in contrast ratio and without distorting the edges of cyst.

Ultrasound imaging algorithm based on generalized sidelobe canceller

The traditional delay and sum (DAS) algorithm is the most widely adopted method in medical ultrasound imaging; although it can produce images quickly, it sacrifices the resolution and the contrast ratio. The adaptive method such as the minimum variance (MV) continuously updates the apodization weighting vectors according to the received signals, so that the variance of the weighted signals is minimized, and thus the quality of the ultrasound imaging can be improved, especially its resolution. Although the image quality may be improved in the contrast ratio as well as the resolution after combining the minimum variance with the coherence factor (MV-CF), it complicates the algorithm, and the robustness against noise is enhanced but a little. An improved ultrasound imaging algorithm based on the generalized side lobe canceller (GSC) is proposed, which is constructed according to the minimum variance principle. The canceller is designed to classify the signal into desired and noise signals, combined with wiping off the big interferential eigenvectors, so that the robustness against noise can be enhanced. Firstly, the canceller divides the weighting vector into non-adaptive and adaptive weights, then the eigenstructure subspace is established according to the covariance matrix of the received signals, and the renewed weighting vector is achieved finally by projecting the weighting vector into the left singular space of the eigenstructure subspace. Simulations of the point targets and the cyst phantom through the simulation tool Field II demonstrate that the ultrasound image acquired through the proposed method is better than the traditional DAS and MV-CF algorithms in terms of the contrast ratio and resolution. In practice, the contrast ratio increases by roughly 7 dB compared to DAS and 5 dB to MV-CF. Furthermore, the proposed method gives a more satisfactory lateral resolution as well as the lowest side lobe peak level. From the sound-absorbing speckle simulation, the contrast ratio increases by 3 dB more than that of DAS and over 4 dB than that of MV-CF when noise exists. In addition, MV-CF performs the worst in the robustness aspect while the proposed GSC method makes improvement on the basis of it. Besides, the image quality can be further improved by combining the proposed method with sign coherence factor (GSC-SCF). After such a combination, the noise added to the data sets is almost invisible in point targets simulation. It also possesses the maximum mean power in cyst region in sound-absorbing speckle simulation. Finally, an experiment is conducted on the basis of the complete data sets which are offered by the University of Michigan. Results indicate that the proposed methods can perform better than the conventional DAS and MV-CF in resolution, contrast ratio and the robustness against noise.

High-Resolution SAR Image Generation by Subaperture Processing of FMCW Radar Signal

In this letter, we present a subaperture-based processing scheme for synthetic aperture radar (SAR) imaging using frequency-modulated continuous-wave (FMCW) radar transmission. An efficient two-stage azimuth subaperture processing scheme is proposed for high-resolution SAR image generation. A new bulk range-cell-migration-correction technique is proposed. The algorithms are validated with point target simulations at the X-band and also using real data samples at the C-band. The results show that subaperture-based processing can be used to image extended ground scenes without mosaicing.

On the Processing of Very High Resolution Spaceborne SAR Data

This paper addresses several important aspects that need to be considered for the processing of spaceborne synthetic aperture radar (SAR) data with resolutions in the decimeter range. In particular, it will be shown how the motion of the satellite during the transmission/reception of the chirp signal and the effect of the troposphere deteriorate the impulse response function if not properly considered. Further aspects that have been investigated include the curved orbit, the array pattern for electronically steered antennas, and several considerations within the processing itself. For each aspect, a solution is proposed, and the complete focusing methodology is expounded and validated using simulated point targets and staring spotlight data acquired by TerraSAR-X with 16-cm azimuth resolution and 300-MHz range bandwidth.

Efficient Evaluation of Fourier-Based SAR Focusing Kernels

This contribution addresses the efficient evaluation of Fourier-based kernels for synthetic aperture radar (SAR) image formation. The goal is to evaluate the quality of the focused impulse response function and the residual phase errors of the kernel without having to implement the processor itself nor perform a costly point-target simulation followed by the processing. The proposed methodology is convenient for situations where the assumption of a hyperbolic range history does not hold anymore, and hence a compact analytic expression of the point target spectrum is not available. Examples where the hyperbolic range history does not apply include very high-resolution spaceborne SAR imaging or bistatic SAR imaging. The approach first computes numerically the two-dimensional (2D) spectrum of a point target and then uses the transfer function of the focusing kernel to match it, and hence obtain the impulse response function (IRF). The methodology is validated by comparing the matched IRFs with the ones obtained using point-target simulations.

A Novel Rapid SAR Simulator Based on Equivalent Scatterers for Three-Dimensional Forest Canopies

Synthetic aperture radar (SAR) simulation of 3-D forest canopies is a powerful tool for studying the interaction between radar and forest, for testing new applications, and for devising inversion algorithms of forest structures. SAR raw-signal generation is frequently used in point-target simulation but is rarely used in 3-D forest simulation. The existing simulators directly produce SAR images based on an impulse response function (IRF) without involving raw-signal generation and various nonideal factors. In this paper, a novel simulator to produce SAR images of 3-D forest canopies is proposed. It incorporates a SAR raw-signal generation process taking account of various nonideal factors such as trajectory deviation of radar platforms and complexity of natural environments, which is more faithful to realistic remote sensing systems. Furthermore, an approach to speed up the raw-signal generation is put forward based on the equivalent scattering model consisting of a few virtual scatterers with specially calculated positions and backscattering matrices. Thus, the raw signals received from the entire forest canopy can be equivalent to those from virtual scatterers in the case of tiny slant-range errors. The error sensitivity of equivalent conditions is analyzed, and the optimum selection of equivalent parameters is derived considering the compromise between precision and efficiency. The results of simulation and forest height inversion demonstrate the feasibility and potential utilities of the proposed simulator.

Research on Sub-Band Synthesis Algorithm of MIMO-SAR

Multiple-Input and Multiple-Output Synthetic Aperture Radar (MIMO-SAR) can achieve high resolution and wide swath at the same time, which has a wide horizon of development in the future. An azimuth frequency-diversity MIMO-SAR is presented, and overlapped effective phase center sampling is obtained while the pulse repetition frequency (PRF) is appropriate. This paper derives an improved sub-band synthesis algorithm which reduces the complexity of conventional sub-band synthesis algorithms and improves the range resolution. The feasibility of this imaging algorithm is proved by point target simulation experiments.

Wide swath FMCW SAR data processing in squint mode

This paper concentrates on the data processing of Frequency Modulation Continuous Wave (FMCW), Synthetic Aperture Radar (SAR) in the case of wide swath and squint mode. In the mode, the Doppler centroid dramatically varies along slant range compared to conventional pulsed-SAR. This poses a challenge for system design and signal processing since a very large azimuth bandwidth would be introduced. In the paper, we accommodate the Doppler centroid variations with range by an improved spectral-length extension method, where a bulk range shift and updated Doppler centroid variations are introduced to greatly reduce the azimuth aliasing with respective to the existing methods. Moreover, an image formation approach that integrates wave number domain algorithm is presented to focus the raw data of FMCW SAR in the case of wide swath and squint mode. Point target simulation experiment demonstrates the advantages of the presented method.

MIMO-Based Forward-Looking SAR Imaging Algorithm and Simulation

Multiple-input multiple-output (MIMO) radar imaging can provide higher resolution and better sensitivity and thus can be applied to targets detection, recognition, and tracking. Missile-borne forward-looking SAR (MFL-SAR) is a new and special MIMO radar mode. It has advantage of two-dimensional (2D) imaging capability in forward direction over monostatic missile-borne SAR and airborne SAR. However, it is difficult to obtain accurate 2D frequency spectrum of the target echo signal due to the high velocity and descending height of this platform, which brings a lot of obstacles to imaging algorithm design. Therefore, a new imaging algorithm for MFL-SAR configuration based on the method of series reversion is proposed in this paper. This imaging method can implement range compression, secondary range compression (SRC), and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.

A HYBRID SAR AUTOFOCUS TECHNIQUE BY TWO METHODS OF SUB-APERTURE ESTIMATION AND ITERATIVE GOLDEN SECTION SEARCH

In a real airborne synthetic aperture radar (SAR), its major phase errors are usually composed of two categories, such as slow-time varying phase errors (less than several cycles of change in phase during synthetic aperture time) and fast-time varying phase errors (otherwise, including wide band random) according to the motion of aircraft. If the fast errors are no more negligible compared to the slow errors, they should be estimated and then compensated accurately to obtain a well focused image. However, it is not proper to estimate all phase errors at the same time like conventional autofocus techniques because the estimation of the fast-time varying phase errors are seriously affected by blurring in image due to the slow-time varying phase errors. In this paper, we presents an accurate hybrid phase estimation technique using two independent estimation stages of sub-aperture and an iterative golden section search method, which has advantages over several existing methods, because of its better estimation accuracy and less sensitive to the quality of extracted range bins as well as requiring less computation time. The performance of our method is illustrated by simulations of point targets and an experiment with real SAR data.

Dual-/tri-apodization techniques for high frequency ultrasound imaging: a simulation study.

BackgroundIn the ultrasound B-mode (Brightness-mode) imaging, high side-lobe level reduces contrast to noise ratio (CNR). A linear apodization scheme by using the window function can suppress the side-lobe level while the main-lobe width is increased resulting in degraded lateral resolution. In order to reduce the side-lobe level without sacrificing the main-lobe width, a non-linear apodization method has been suggested.MethodsIn this paper, we computationally evaluated the performance of the non-linear apodization method such as dual-/tri-apodization focusing on the high frequency ultrasound image. The rectangular, Dolph-Chebyshev, and Kaiser window functions were employed to implement dual-/tri-apodization algorithms. The point and cyst target simulations were conducted by using a dedicated ultrasound simulation tool called Field-II. The center frequency of the simulated linear array transducer was 40 MHz and the total number of elements was 128. The performance of dual-/tri-apodization was compared with that of the rectangular window function focusing on the side-lobe level and the main-lobe widths (at -6 dB and -35 dB).ResultsIn the point target simulation, the main-lobe widths of the dual-/tri-apodization were very similar to that of the rectangular window, and the side-lobe levels of the dual-/tri-apodization were more suppressed by 9 ~ 10 dB. In the cyst target simulation, CNR values of the dual-/tri-apodization were improved by 41% and 51%, respectively.ConclusionsThe performance of the non-linear apodization was numerically investigated. In comparison with the rectangular window function, the non-linear apodization method such as dual- and tri-apodization had low side-lobe level without sacrificing the main-lobe width. Thus, it can be a potential way to increase CNR maintaining the main-lobe width in the high frequency ultrasound imaging.

Signal Processing for Digital Beamforming FMCW SAR

According to the limitations of single channel Frequency Modulation Continuous Wave (FMCW) Synthetic Aperture Radar (SAR), Digital Beamforming (DBF) technology is introduced to improve system performance. Combined with multiple receive apertures, DBF FMCW SAR can obtain high resolution in low pulse repetition frequency, which can increase the processing gain and decrease the sampling frequency. The received signal model of DBF FMCW SAR is derived. The continuous antenna motion which is the main characteristic of FMCW SAR received signal is taken into account in the whole signal processing. The detailed imaging diagram of DBF FMCW SAR is given. A reference system is also demonstrated in the paper by comparing with a single channel FMCW SAR. The validity of the presented diagram is demonstrated with a point target simulation results.

Channel Phase Error Compensation for MIMO-SAR

Multi-input multioutput (MIMO) is a novel technique to achieve high-resolution as well as wide swath in synthetic aperture radar (SAR) systems. Channel imbalance is inevitable in multichannel systems that it declines the imaging quality. Generally, the imbalance cannot be fully compensated by simple internal calibration in a MIMO-SAR system. In this paper, a new algorithm based on raw data is presented to remove the channel phase error. Based on the error source, this approach models the phase error as two parts: the transmit phase error and the receive phase error. The receive phase error is removed using cost function at the azimuth processing stage, whereas the transmit phase error is estimated with correlation. Point target simulations confirm the influence of channel phase error and the validation of the proposed approach. Besides, the performance is also investigated.

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

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.

Towards Three-Dimensional Millimeter-Wave Radar With the Bistatic Fast-Factorized Back-Projection Algorithm—Potential and Limitations

In this paper, we report on a time-domain approach for 3-D synthetic image reconstruction at stand-off distances called the bistatic fast-factorized back-projection (BiFFBP) algorithm. Although the algorithm is suited for multiple purposes, it is applied in this paper to a millimeter-wave radar system that operates in a frequency-modulated continuous-wave mode between 234 and 306 GHz. After initially mapping the bistatic to a quasi-monostatic configuration, the algorithm recursively factorizes both, the aperture positions and the target area. Three-dimensional reconstructions are shown for a simulated point-target in order to evaluate the point-spread-function of the system. In addition, 2-D-imaging is performed on real objects at stand-off distances using a scanner system that consists of 8 transmitters and 16 receivers. Reconstructions with the BiFFBP-algorithm are compared with the global back-projection (GBP) algorithm that serves as a benchmark. The results show that the BiFFBP-approach yields similar results to the GBP with respect to dynamic range in the image and the overall image quality. It is also shown that a resolution of 2 cm can be achieved with relatively few elements, no scanning, and over a large field-of-view.

A novel spaceborne SAR wide-swath imaging approach based on Poisson disk-like nonuniform sampling and compressive sensing

Since the range swath width in the conventional single channel spaceborne synthetic aperture radar (SAR) is restricted by the system parameters, there is a trade-off between the azimuth resolution and the swath width in order to satisfy the Nyquist sampling criterion. In this paper, we propose a novel spaceborne SAR wide-swath imaging scheme based on compressive sensing (CS) for the sparse scene. The proposed method designs a Poisson disk-like nonuniform sampling pattern in the azimuth direction, which meets the demand of wider swath by restricting the smallest time interval between any two azimuth samples, with the conventional sampling pattern preserved in the range direction. By a similar way to the processing procedure of spectral analysis (SPECAN) algorithm, the linear range migration correction (RMC) is realized while carrying out range compression, which can meet the demand for focusing with middle level resolution. To reduce the computation load of CS reconstruction, we propose a novel fast reconstruction algorithm based on nonuniform fast Fourier transform (NUFFT), which greatly reduces the computation complexity from O(2MN) to O(4N logN). Experiment results validate the effectiveness of the proposed methods via the point target simulation and the Radarsat-1 raw data processing in F2 mode.

Polar Format Algorithm Wavefront Curvature Compensation Under Arbitrary Radar Flight Path

An improved space-variant postfiltering approach to compensate for the wavefront curvature effect in polar format imagery is presented in this letter. The main contribution of this new method is the construction of a space-variant filter, which is based on exploiting the endomorphism property of the polar format transformation. The new approach provides an accurate and general solution to wavefront curvature compensation under arbitrary radar flight path. Finally, point target simulation has validated the effectiveness of the new approach.

SVD-based Method for Radio Frequency Interference Suppression Applied to SAR

Synthetic aperture radar (SAR) is a special type of active microwave sensor, which has got a wide range of applications in remote sensing. However, the performance of SAR systems may be affected by radio frequency interference (RFI) in several geographic regions. A novel singular value decomposition method is proposed for radio frequency interference suppression applied to SAR. This method decomposes the singular vectors of the received signal with RFI into interference subspace and signal subspace. The orthogonality of the two subspaces is used to suppress the RFI. The point-target simulation is used to show the working principle of the proposed algorithm. The experimental results based on SAR real data are also shown to verify the proposed algorithm. Defence Science Journal, 2012, 62(2), pp.132-136 , DOI:http://dx.doi.org/10.14429/dsj.62.1144