Point Target Simulation Research Articles

High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery

Synthetic Aperture Radar (SAR) raw data missing occurs when radar is interrupted by various influences. In order to cope with this problem, a new method is proposed to focus the azimuth missing SAR raw data via segmented recovery in this paper. A reference function in time domain is designed to make the missing raw data sparser in two dimensional frequency domain. Afterwards, greedy algorithms are available to recover the missing data in two dimensional frequency domain. In addition, in order to avoid range frequency aliasing problem caused by reference function multiplication in time domain, the missing raw data is split into several parts in range direction and is recovered with a segmented recovery strategy. Then, the recovered raw data is available to be focused with traditional SAR imaging algorithms. The range migration algorithm is chosen to deal with the recovered raw data in this paper. Point target and area target simulations are carried out to validate the effectiveness of the proposed method on azimuth missing SAR raw data. Moreover, the proposed method is implemented on real SAR data in order to further provide convincing demonstration.

Novel Motion Sensing Algorithm for Improving SAR Imaging by Parametric Error Modeling

This paper presents a new motion sensing algorithm for airborne synthetic aperture radar (SAR). Image processing in SAR requires highly accurate and precise motion information which is used for matched filter in range and azimuth compression of the range Doppler algorithm (RDA). If an embedded global positioning system and inertial navigation system (EGI) is used for motion sensing, it can sense the motion more accurately than using INS or GPS alone. However, the discontinuity in the position error occurs because GPS updates the measurement periodically, and this discontinuity significantly degrades the SAR image quality. To resolve this problem, a parametric error modeling (PEM) is proposed to mitigate the discontinuity errors. The PEM is a method that estimates polynomial parameters of INS error compared to EGI which can be assumed by a polynomial in short term. Then, when the error estimated by PEM is subtracted from the INS position, the discontinuity error of EGI can be eliminated. Numerical simulation shows that applying PEM perfectly eliminates discontinuity of EGI output; then, point target simulation using RDA shows improvement for impulse response function quality. Experimental result verifies the above result and demonstrates that the image quality is improved in SAR imagery.

Multi-line acquisition with delay multiply and sum beamforming in phased array ultrasound imaging, validation of simulation and in vitro

Increasing the frame rate of medical ultrasound imaging is very important, especially in applications such as cardiac diagnostic imaging, where such an imaging should be able to facilitate the examination of the temporal behaviour of the short cardiac cycle. Frame rate can be increased by the multi-line acquisition (MLA) method, also called parallel receive beamforming (PRB), where several beams are received from a single transmit (Tx) beam. The shortage is that imaging performance would be sacrificed. Filtered-delay multiply and sum (F-DMAS) is a non-linear beamforming technique proven to be able to improve the contrast and resolution of the image compared to traditional delay and sum (DAS) beamforming. In this paper, we proposed to combine MLA and the lower complexity F-DMAS algorithm, and use synthetic transmit beams (STB) to reduce the artifacts of MLA. The simulations of point targets and cyst phantoms were all carried out in Matlab using Field II. The results show that 2 line acquisition with delay multiply and sum (DMAS 2MLA) beamforming presents an equivalent imaging performance to that of traditional DMAS beamforming, and obtains a 7.69% higher resolution and 2 times higher contrast ratio in comparison to DAS beamforming. A real RF data experiment was applied to support the feasibility and validity of our method. The low complexity of F-DMAS (O(N)) would make it easy to implement 2 parallel beamformers. Thus, by combining 2MLA and F-DMAS, the frame rate can be improved to 2-fold higher with a better image quality compared to that of DAS beamforming.

Minimum variance based fusion of fundamental and second harmonic ultrasound imaging: Simulation and experimental study

Harmonic imaging is widely used in clinical ultrasound due to its higher resolution in comparison with fundamental mode. However, the low amplitude of harmonic components in this imaging method is a crucial problem, resulting in a high sensitivity to noise, while the fundamental imaging is more robust against noise. To exploit the benefits of both the fundamental and harmonic imaging, we propose a minimum variance (MV)-based adaptive combination of fundamental and harmonic images. The performance of the proposed mixing-together MV (MTMV) beamformer is evaluated on simulated and experimental RF data. The results of the simulated point targets show that in the regions near of point targets, where the desire signals exist, the proposed MTMV beamformer mostly follows the MV-beamformed harmonic image to retain a better resolution. In the regions far from the point targets, where there is just noise, it follows the MV-beamformed fundamental image to benefit from more robustness. Also, the results of the simulated and experimental cyst phantoms indicate that MTMV reduces the background noise level and improves the contrast without compromising the high resolution of the MV-beamformed harmonic image. In the simulated cyst phantom, in comparison to DAS (fundamental), DAS (harmonic), MV (fundamental), MV (harmonic), and wavelet fusion, the image contrast ratio (CR) is increased, in average, about 5.2 dB, 3.5 dB, 1.5 dB, 3.6 dB, and 2.8 dB, respectively. The contrast-to-noise ratio (CNR) is significantly improved; about 59%, 53%, 41%, 37%, and 24%, respectively. In the experimental cyst phantom, these relative improvements are about 6.6 dB, 3.5 dB, 4.2 dB, 2.1 dB, and 3.8 dB for CR, and about 64%, 52%, 25%, 33%, and 33%, for CNR, respectively.

Mobile Radar Mapping—Subcentimeter SAR Imaging of Roads

In this paper, we present a strategy for focusing ultrahigh-resolution synthetic aperture radar (SAR) data for mobile radar mapping. We illustrate the related theoretical background and required extensions on the imaging method based on backprojection techniques. The influence of potential errors in estimating a correct geometry with respect to the imaging quality is investigated in detail by point target simulations. As backprojection techniques require precise knowledge of the topography in close range, the new strategy instantly uses the GPS/INS data of the trajectory to define a suitable digital elevation model of the illuminated scene. We have tested the strategy by driving on conventional roads with an active frequency-modulated continuous wave radar system operating at 300 GHz. Different reference targets were placed in the scene, and the accuracy of the method was evaluated. The results experimentally reveal that the lower terahertz band is capable of subcentimeter SAR imaging in mobile mapping scenarios at very high quality. We have shown that narrow cracks in the asphalt of roads can be detected and fine-scale objects on millimeter size can be displayed. Geometric distortions in the SAR images are significantly reduced allowing the measurements of infrastructure. The output data can at last be transferred to the conventional 3-D Point Cloud Software for further processing.

Scene Size Limits for Bistatic Polar Format Algorithm

In this paper, the distortion and defocus effects due to residual phase errors that are inherent in bistatic polar format algorithm are analyzed using time-domain Taylor series decomposition. A two-dimensional interpolation-based distortion correction method is developed, and accurate scene sizes limits are derived to mitigate the effects of defocus. The phase analysis is conducted with respect to arbitrary geometries, and examples are demonstrated for ideal linear and circular flight trajectories using a point target simulation.

High‐resolution SAR imaging from azimuth periodically gapped raw data via generalised orthogonal matching pursuit

Occurrence of periodical gapping in synthetic aperture radar (SAR) raw data poses a challenge in obtaining focused images. Traditional SAR imaging algorithms fail to process the periodically gapped raw data. A method is proposed to solve this problem. The presented method consists of phase compensation and recovering raw data in range Doppler domain via generalised orthogonal matching pursuit. Then, the recovered raw data is capable of being processed with the traditional SAR imaging algorithms. The Omega-K algorithm is selected to focus the reconstructed raw data. The presented method is validated on performing better in comparison with the spectral method periodically gapped amplitude and phase estimation by point target simulation and analysis. In simulation, the raw data loses 50% by the form of azimuth periodical gapping. The resolution of point targets can reach 0.25 m in both azimuth and range direction. In addition, real SAR raw data is utilised to verify the effectiveness of the proposed method.

Diverging wave compounding with spatio-temporal encoding using orthogonal Golay pairs for high frame rate imaging

Golay coded excitation for diverging wave compounding (DWC) has been demonstrated to increase the signal-to-noise ratio (SNR) and contrast for high frame rate cardiac imaging. However, the complementary codes need to be transmitted in two consecutive firings for decoding, which reduces the frame rate by 2 folds. This paper proposes an orthogonal Golay pairs coded (OGPs-coded) DWC sequence to overcome this problem, which implements spatio-temporal encoding for DWC. Two diverging waves (DWs) at different steering angles coded by an orthogonal Golay pair are transmitted simultaneously, thus compensating the frame rate reduction caused by transmissions of complementary codes. The two DWs can be separated based on the orthogonality of Golay pairs. To test the feasibility of the proposed sequence, we performed simulations of point targets and tissue phantoms in both static and moving states. Compared with non-coded DWC at the same frame rate, OGPs-coded DWC obtains comparable resolution, SNR gains of 7.5–10 dB and contrast gains of 3–5 dB. The OGPs-coded DWC sequence was also tested experimentally on a tissue-mimicking phantom. Compared with non-coded DWC, OGPs-coded DWC achieves improvements in the SNR (3–6 dB) and contrast (1–2 dB). Preliminary in vivo results show brighter myocardium and larger penetration depth with the proposed method. The proposed OGPs-coded DWC sequence has potential for high frame rate and high quality cardiac imaging.

SAR Signal Recovery and Reconstruction in Staggered Mode With Low Oversampling Factors

The next generation of spaceborne synthetic aperture radar (SAR) remote sensing systems will emphasize on high-resolution and wide-coverage imaging. For these design goals, variable pulse repetition interval (PRI), which is also called staggered SAR, is a promising candidate to deal with the inherent problem of blind range effect in conventional SAR with constant PRI. This letter presents an improved work of signal processing to cope with two unavoidable problems in staggered mode: the loss of echo signal and nonuniform sampling in azimuth. Since the existing signal processing methods are mostly based on a high oversampling ratio, which would increase the range ambiguity to signal ratio and the amount of data to be downlinked, this letter focuses on signal processing with low oversampling factors. A two-step processing scheme—recovery and reconstruction—is proposed to recover the missing sampled data using the spectral-estimation techniques first and then reconstruct the in-band energy and minimize the ambiguity energy, which is from band unlimited SAR raw data, to obtain uniform sampling in azimuth. Point target simulations and artificially gapped data generated from China’s S-band spaceborne SAR system HJ-1-C are shown to validate the proposed scheme.

Deep Neural Networks for Ultrasound Beamforming.

We investigate the use of deep neural networks (DNNs) for suppressing off-axis scattering in ultrasound channel data. Our implementation operates in the frequency domain via the short-time Fourier transform. The inputs to the DNN consisted of the separated real and imaginary components (i.e. in-phase and quadrature components) observed across the aperture of the array, at a single frequency and for a single depth. Different networks were trained for different frequencies. The output had the same structure as the input and the real and imaginary components were combined as complex data before an inverse short-time Fourier transform was used to reconstruct channel data. Using simulation, physical phantom experiment, and in vivo scans from a human liver, we compared this DNN approach to standard delay-and-sum (DAS) beamforming and an adaptive imaging technique that uses the coherence factor. For a simulated point target, the side lobes when using the DNN approach were about 60 dB below those of standard DAS. For a simulated anechoic cyst, the DNN approach improved contrast ratio (CR) and contrast-to-noise (CNR) ratio by 8.8 dB and 0.3 dB, respectively, compared with DAS. For an anechoic cyst in a physical phantom, the DNN approach improved CR and CNR by 17.1 dB and 0.7 dB, respectively. For two in vivo scans, the DNN approach improved CR and CNR by 13.8 dB and 9.7 dB, respectively. We also explored methods for examining how the networks in this paper function.

Three-Dimensional Imaging of Space Debris With Space-Based Terahertz Radar

The increasing natural or man-made space debris could pose a serious threat to orbital space-based systems and their operators. Consequently, their detection, reorganization, and tracking are of considerable significance. However, the traditional solutions, including ground-based radar and optical telescope, cannot exactly observe the debris with small diameter. Imaging with space-based terahertz (THz) radar in combination with inverse synthetic aperture radar (ISAR) technique enables us to obtain high-resolution 3-D image. In this paper, we have developed a high-resolution THz radar that operates at 340 GHz with a bandwidth of 28.8 GHz and the output peak power of 5 mW for proof-of-concept. In addition, using the characteristic that space debris rotates about its main axis, we have established a 3-D ISAR imaging geometry as well as its corresponding signal model. Then, a 3-D wavenumber-domain image formation algorithm is presented and has been validated by point target simulation. The experimental results have confirmed that the THz radar can effectively achieve high-resolution 3-D imaging of the spinning space debris.

Wide Nonlinear Chirp Scaling Algorithm for Spaceborne Stripmap Range Sweep SAR Imaging

The spaceborne stripmap range sweep synthetic aperture radar (SS-RSSAR) is a new concept spaceborne SAR system that images the region of interest (ROI) with ROI-orientated strips, which, unlike the traditional spaceborne SAR, are allowed to be not parallel with the satellite orbit. The SS-RSSAR imaging is a challenging problem because echoes of a wide region have strong spatial varieties, especially in high-squint geometries, and are hard to be focused by a single swath. The traditional imaging algorithms could solve this problem by cost-ineffectively dividing an ROI into many subswaths for separate processing. In this paper, a new wide nonlinear chirp scaling (W-NLCS) algorithm is proposed to efficiently image the SS-RSSAR data in a single swath. Comparing with the traditional nonlinear chirp scaling algorithm, the W-NLCS algorithm is superior in three major aspects: the nonlinear bulk range migration compensation (RMC), the interpolation-based residual RMC, and the modified azimuth frequency perturbation. Specifically, the interpolation for the residual RMC, the most significant step in achieving the wide-swath imaging performance, is made innovatively in the time domain. The derivation of the W-NLCS algorithm, as well as the performance analyses of the W-NLCS algorithm in aspects of the azimuth resolution, accuracy, and complexity, are all provided. The presented approach is evaluated by the point target simulations.

A New Nonlinear Chirp Scaling Algorithm for High-Squint High-Resolution SAR Imaging

Among high-squint high-resolution (HSHR) synthetic aperture radar imaging algorithms, nonlinear chirp scaling algorithm (NLCSA) and its extensions, such as extended NLCSA (ENLCSA), have a common drawback in that they all neglect the spatial variations of linear range migration (LRM) and Doppler centroid, and thus, only targets in a specific central slant range plane can be strictly focused. In this letter, we show that by using a new NLCSA, targets can be focused in the ground plane under HSHR conditions. Based on a more accurate 2-D spectrum, the new NLCSA outperforms the ENLCSA by introducing a new range–Doppler domain interpolation to correct residual range migration and a new perturbation function to remove the dependence of Doppler phase on azimuth. The coefficients of the new perturbation function are numerically calculated and then smoothed by polynomial fitting. Though the outputs of the numerical calculation are somewhat unstable at the current stage, it has been demonstrated to perform better than the algorithms neglecting the spatial variations of LRM and Doppler centroid, such as the ENLCSA, by point target simulations.

A Novel Spaceborne Sliding Spotlight Range Sweep Synthetic Aperture Radar: System and Imaging

In this paper, a new Spaceborne Sliding Spotlight Range Sweep Synthetic Aperture Radar (SSS-RSSAR) is proposed to generate a high-resolution image of a Region of Interest (ROI) tilted with respect to the satellite track. Comparing to the traditional Spaceborne Sliding Spotlight Synthetic Aperture Radar (SSS-SAR), the SSS-RSSAR is superior in contributing to less data amount, lighter computational load and hence higher observation efficiency. Unlike the Spaceborne Stripmap Range Sweep Synthetic Aperture Radar (SS-RSSAR) proposed in a previous paper, the SSS-RSSAR not only continuously sweeps the beam in range for the ROI tracking, but also in azimuth to enlarge the synthetic aperture for an improved azimuth resolution. Two aspects of the SSS-RSSAR are focused: system and imaging. For the system part, a Continuous Varying Pulse Interval (CVPI) technique is proposed to avoid the transmission blockage problem by non-uniformly adjusting the pulse intervals based on the geometry. For the imaging part, a Modified Polar Format Algorithm (MPFA) is proposed to accommodate the original polar format algorithm to the echo received with the CVPI technique. Moreover, an integrate system parameter design flow for the SSS-RSSAR is also suggested. The presented approach is evaluated by exploiting the point target simulations.

A Sparse Bayesian Approach for Forward-Looking Superresolution Radar Imaging.

This paper presents a sparse superresolution approach for high cross-range resolution imaging of forward-looking scanning radar based on the Bayesian criterion. First, a novel forward-looking signal model is established as the product of the measurement matrix and the cross-range target distribution, which is more accurate than the conventional convolution model. Then, based on the Bayesian criterion, the widely-used sparse regularization is considered as the penalty term to recover the target distribution. The derivation of the cost function is described, and finally, an iterative expression for minimizing this function is presented. Alternatively, this paper discusses how to estimate the single parameter of Gaussian noise. With the advantage of a more accurate model, the proposed sparse Bayesian approach enjoys a lower model error. Meanwhile, when compared with the conventional superresolution methods, the proposed approach shows high cross-range resolution and small location error. The superresolution results for the simulated point target, scene data, and real measured data are presented to demonstrate the superior performance of the proposed approach.

Rapid raw data simulation for fixed-receiver bistatic interferometric synthetic aperture radar

Raw data simulation of synthetic aperture radar (SAR) is useful for system designing, mission planning, and testing of imaging algorithms. According to the two-dimensional (2-D) frequency spectrum of the fixed-receiver bistatic SAR system, a rapid raw data simulation approach is proposed. With the combination of 2-D inverse Stolt transform in the 2-D frequency domain and phase compensation in the range-Doppler frequency domain, our approach can significantly reduce the simulation time. Therefore, simulations of extended scenes can be performed much more easily. Moreover, the proposed algorithm offers high accuracy of phase distribution, therefore, it can be used for single-pass fixed-receiver bistatic interferometric usage. The proposal is verified by extensive simulations of point targets and extended scene, in which the results indicate the feasibility as well as the effectiveness of our approach. In the end, the accuracy of phase distribution of the proposed algorithm is further examined with simulations of synthetic aperture radar interferometry.

A new method for estimating the longevity and degradation of photovoltaic systems considering weather states

The power output of solar photovoltaic (PV) systems is affected by solar radiation and ambient temperature. The commonly used evaluation techniques usually overlook the four weather states which are clear, cloudy, foggy, and rainy. In this paper, an ovel analytical model of the four weather conditions based on the Markov chain is proposed. The Markov method is well suited to estimate the reliability and availability of systems based on a continuous stochastic process. The proposed method is generic enough to be applied to reliability evaluation of PV systems and even other applications. Further aspects investigated include the new degradation model for reliability predication of PV modules. The results indicate that the PV module degradation over years, failures, and solar radiation must be considered in choosing an efficient PV system with an optimal design to achieve the maximum benefit of the PV system. For each aspect, a method is proposed, and the complete focusing methodology is expounded and validated using simulated point targets. The results also demonstrate the feasibility and applicability of the proposed method for effective modeling of the chronological aspects and stochastic characteristics of solar cells as well as the optimal configuration and sizing of large PV plants in terms of cost and reliability.

Focusing Bistatic FMCW SAR Signal by Range Migration Algorithm Based on Fresnel Approximation.

Frequency modulated continuous wave (FMCW) technique has recently been employed by synthetic aperture radar (SAR) to decrease the radar cost and volume. However, the operation range is limited by the direct energy leakage from the transmitting channel to receiving channel due to the operation principle of FMCW technique. Bistatic configuration is an efficient way to increase the isolation between the transmitter and receiver, which could significantly increase the radar standoff range. A bistatic FMCW SAR spectrum model is proposed by using the Fresnel approximation in this paper. This model is similar to that of a monostatic FMCW SAR spectrum, which allows the existing imaging algorithms to be used on bistatic image processing. Based on the new model and the characteristics of FMCW signal, a modified range migration algorithm (RMA) for FMCW SAR is proposed to focus the image, which requires less memory and computational load than the traditional RMA. Point-target simulation is used to verify the proposed spectral model and real data processing verified the effectiveness of the proposed RMA.

Simulation of the SuperSAR Multi-Azimuth Synthetic Aperture Radar Imaging System for Precise Measurement of Three-Dimensional Earth Surface Displacement

The SuperSAR imaging system, a novel multi-azimuth synthetic aperture radar (SAR) system capable of detecting Earth surface deformation in three dimensions from a single satellite platform, has recently been proposed. In this paper, we investigate the feasibility of detecting precise 3-D surface displacement measurements with the SuperSAR imaging system using a point target simulation. From this simulation, we establish both a relationship between the interferometric SAR phase and the across-track displacement and a relationship between the multiple-aperture interferometry phase and the along-track displacement based on the SuperSAR imaging geometry. The theoretical uncertainties of the SuperSAR measurement are analyzed in the across- and along-track directions, and the theoretical accuracy of the 3-D displacement measurement from the SuperSAR system is also investigated according to both the decorrelation and the squint and look angles. In the case that the interferometric coherence is about 0.8 and that five effective looks are employed, the theoretical 2-D measurement precision values are about 3.67 and 6.35 mm in the across- and along-track directions, respectively, and the theoretical 3-D measurement precision values for 3-D displacement are about 4.05, 4.56, and 3.45 mm in the east, north, and up directions, respectively. The result of this study demonstrates that the SuperSAR imaging system is capable of measuring the 3-D surface displacement in all directions with subcentimeter precision.

“Stop-and-go” error analysis of geosynchronous SAR

In this paper, the slant range error introduced by the “stop-and-go” assumption is analyzed in detail. Owing to the high orbit and long synthetic aperture time of geosynchronous SAR (Geo-SAR), the slant range error introduced by the “stop-and-go” assumption should be considered. In addition, an accurate signal propagation delay time equation of Geo-SAR based on circle orbit is presented, and the error of the “stop-andgo” assumption is demonstrated by simulation. An “equivalent position” model is proposed and validated by simulation. The error of various powers of “stop-and-go” slant range is analyzed using Legendre orthogonal series expansion. The limitation of the stop-and-so assumption is proved by point target simulation.