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Speckle or multiplicative noise is a critical issue in coherence-based imaging systems, such as synthetic aperture radar and optical coherence tomography. Existence of speckle noise considerably limits the applicability of such systems by degrading their performance. On the other hand, the sophistications that arise in the study of multiplicative noise have so far impeded theoretical analysis of such imaging systems. As a result, the current acquisition technology relies on heuristic solutions, such as oversampling the signal and converting the problem into a denoising problem with multiplicative noise. This paper attempts to bridge the gap between theory and practice by providing the first theoretical analysis of such systems. To achieve this goal the log-likelihood function corresponding to measurement systems with speckle noise is characterized. Then employing compression codes to model the source structure, for the case of under-sampled measurements, a compression-based maximum likelihood recovery method is proposed. The mean squared error (MSE) performance of the proposed method is characterized and is shown to scale as $O\left({\sqrt {\frac{k \log n }{ m}}}\right)$ , where $k$ , $m$ and $n$ denote the intrinsic dimension of the signal class according to the compression code, the number of observations, and the ambient dimension of the signal, respectively. This result, while in contrast to imaging systems with additive noise in which MSE scales as $O\left({{\frac{k \log n }{ m}}}\right)$ , suggests that if the signal class is structured (i.e., $k \ll n$), accurate recovery of a signal from under-determined measurements is still feasible, even in the presence of speckle noise. Simulation results are presented that suggest image recovery under multiplicative noise is inherently more challenging than additive noise, and that the derived theoretical results are sharp. [ABSTRACT FROM AUTHOR]

Microwave photonic synthetic aperture radar (MWP-SAR) offers a larger signal bandwidth than conventional SAR, and its theoretical resolution can be improved to centimeter level. To achieve same order of magnitude resolution in the azimuth direction, long synthetic aperture is always required, which results in extremely high requirements for the accuracy of imaging procedure. Compared with the conventional SAR imaging algorithms, two major problems should be considered: 1) the scattering characteristics of target might vary from the frequency of signal and the angle of incidence, which seriously affects the coherence of received echo and 2) the imaging of the MWP-SAR system is more sensitive to motion errors and therefore requires higher accuracy of motion compensation processing. To solve the above issues, a high-precision imaging method for MWP-SAR is proposed. First, based on the attribute scattering center (ASC) model, this article analyzes the target scattering characteristics with different frequencies and incident angles. Then, according to the influence of scattering phase on MWP-SAR imaging, an optimal subaperture division algorithm is proposed to guarantee the coherence of each subaperture data and better imaging results. Furthermore, to compensate for the effects of high-order motion errors, this article proposes a motion error estimation algorithm based on subimage registration, where the full-aperture high-order motion errors can be divided into multiple linear components, and the flight trajectory of platform can be accurately reconstructed. Finally, a full-aperture time-domain high-precision imaging method is presented, and the effectiveness of the proposed formation is verified by both simulation and actual airborne MWP-SAR data processing. [ABSTRACT FROM AUTHOR]

In this study, we propose a generalized algorithm for far-field radar cross section determination by using 3-D synthetic aperture imaging with arbitrary antenna-scanning surfaces. This method belongs to a class of techniques called image-based near-field-to-far-field transformation. The previous image-based approaches have been formulated based on a specific antenna-scanning trajectory or surface, such as a line, plane, circle, cylinder, and sphere; the majority of these approaches consider 2-D radar images to determine the azimuth radar cross section. We generalize the conventional image-based technique to accommodate an arbitrary antenna-scanning surface and consider a 3-D radar image for radar cross section prediction in both the azimuth and zenith directions. We validate the proposed algorithm by performing numerical simulations and anechoic chamber measurements. [ABSTRACT FROM AUTHOR]

This article proposes a new synthetic aperture radar (SAR), named as panoramic SAR, based on a combination of linear and rotational SARs, by which a large 360° panoramic view of the observed scene can be reconstructed. First, the system geometry and its imaging process based on the back-projection algorithm (BPA) are presented. The combined movement constitutes a 2-D synthetic aperture, and thus higher imaging resolutions can be obtained. The corresponding resolution analysis and the sampling criteria are discussed accordingly. Then, a novel dynamic piecewise compensation (DPC) algorithm, a recursive imaging process, is proposed to reduce the processing complexity significantly. The imaging implementation and the complexity are also studied respectively. Finally, a prototype of panoramic SAR is built based on an frequency-modulated continuous wave (FMCW) radar and a moving platform, and the simulation and experimental results are provided to validate the proposed panoramic SAR principle and the DPC algorithm. [ABSTRACT FROM AUTHOR]

A 360° video synthetic aperture radar (VideoSAR) appears as an interactive observation capability to understand the dynamic scenarios. VideoSAR system mounted on an unmanned aerial vehicle (UAV) delivers a highly flexible and cost-effective approach. In this letter, the UAV-borne repeat-pass circular stripmap (CSM) VideoSAR observation is formulated in the format of video area overflown to enhance the wide-area surveillance capability. A completely two-dimensional interpolation-free polar format algorithm is employed, especially in terms of repeat-pass CSM-VideoSAR configuration. We conduct the repeat-pass CSM-VideoSAR experiments on multirotor UAV-borne system in the interests of imaging demonstration and promoting the inspirations on the related open issues. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) can provide high-resolution electromagnetic backscattering images of the illuminated area, playing a significant role in various applications. However, achieving focused SAR images is challenging under sparse sampling and phase error conditions. By exploiting the sparsity or compressibility priors, the state-of-the-art sparsity-driven SAR imaging methods can reconstruct images under the condition of sparse sampling. However, the handcrafted priors used in these methods limit the imaging performance, and the iterative solution schemes reduce the computational efficiency. Besides, the measurement inaccuracy introduced by the phase error also degrades the reconstruction performance of the sparsity-driven imaging methods. To address these issues, a deep network for SAR autofocus imaging is proposed, which alternately performs image reconstruction and phase error estimation. When performing image reconstruction, the sparsity-cognizant total least-square (S-TLS) model is introduced to handle the problem of measurement inaccuracy, contributing to robust reconstruction performance under the condition of phase error. During the implementation of the deep network, a feature transform operator is used to realize data-driven prior knowledge learning and overcome the limitations of handcrafted priors. Moreover, the deep network approach can significantly improve computational efficiency. Experiments on simulated and real data verify the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Arc-synthetic aperture radar (ArcSAR) can observe the surrounding ground objects at 360°, with the advantages of a wide imaging range and constant azimuth angular resolution. In this article, based on the stepped frequency continuous wave (SFCW), fourth-order Taylor expansion, and the series-inversion method, the accurate phase expression of the 2-D spectrum is derived, and then, the 2-D frequency-domain imaging algorithm (2-D-FDA) for ArcSAR is realized. In the simulation part, the imaging results of 2-D-FDA are compared with the backprojection algorithm (BPA) and Liao’s method, which is the reference for 2-D-FDA. The simulation results show that the 2-D-FDA is more applicable to process the data obtained from the antenna with the beamwidth larger than 70°. The SFCW-ArcSAR system consists of a vector network analyzer (VNA), a rotating platform, two antennas, and a control computer. Then, the system is used for the outdoor experiment. The experimental results of the corner reflector show that the point target analysis of 2-D-FDA is consistent with those of the BPA and theory. Under the system parameters in this article, the measured azimuth angular resolution is 0.0177 radian, the peak sidelobe ratio (PSLR) in the range direction is −12.46 dB, and the range resolution is 0.48 m on the ground-range plane. The imaging results of the real scenario processed by BPA and 2-D-FDA are consistent, and the ArcSAR image agrees with the optical image of the experimental scene. The effectiveness and correctness of the 2-D-FDA are verified by simulation and experiment. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low resolution and poor noise suppression for maneuvering targets with traditional inverse synthetic aperture radar (ISAR) imaging algorithms, we propose a motion compensation-driven high-resolution imaging algorithm based on Fourier ptychographic microscopy (FPM) technology. FPM is a phase retrieval technology that uses the concept of synthetic aperture to obtain the high-resolution image of the target. The process of FPM imaging is composed of the enhancement of the known target information in the spatial domain and some fixed restricted alternating iteration in the frequency domain. This article analyzes the mathematical model of maneuvering target echo and then studies the rationality of applying the FPM phase retrieval algorithm to ISAR maneuvering target imaging. The proposed algorithm mainly includes two steps. First, a series of low-resolution ISAR images are generated by sampling echo data through an aperture function. Second, the FPM phase retrieval technology is applied to splice and reconstruct the spectrum of the low-resolution images to achieve the focused ISAR image. The effectiveness of the proposed algorithm is verified by using multiple groups of simulation data and real radar data. [ABSTRACT FROM AUTHOR]

High-resolution wide-swath synthetic aperture radar (HRWS-SAR) imaging is highly desirable since it allows one to produce high-resolution SAR images of large areas during a short visit time. In this article, staggered coprime pulse repetition frequencies synthetic aperture radar (SCopSAR) is proposed. It divides the time during which a scatterer is illuminated by the antenna beam pattern into two halves where, in each half, pulses are transmitted at the rate of one of two sub-Nyquist pulse repetition frequencies (PRFs). Such PRFs are related to the Nyquist PRF using two coprime subsampling factors. This allows extending the maximum range swath width that can be imaged by a number of times that equals the smaller subsampling factor at the expense of a reduction in the azimuth resolution by half. It further allows for a reduction in the amount of data to be stored and communicated. SCopSAR is an imaging modality suitable for scenes that contain a small number of bright scatterers over a dark background which, for instance, is the case when imaging ships in a calm sea background. Compared with the techniques recently proposed in the literature, SCopSAR simplifies the radar requirements since it uses only one carrier frequency, one waveform, and one channel. Simulations and real ERS-2 satellite raw data are used to validate the theoretical findings presented in this article. [ABSTRACT FROM AUTHOR]

Arc synthetic aperture radar (ArcSAR) is a ground-based remote imaging technology with the ability to cover wide fields of view. However, because its azimuth is formed by scanning angle rotation, the focusing of ArcSAR images is different from classical SAR focusing. Since the existing imaging methods cannot give a good balance between computational efficiency and accuracy, the wavenumber domain algorithm (WMA) could become an interesting alternative. Due to the fact that in ArcSAR imaging, the slant range measurement depends on a sine term of the scanning angle, no dedicated WMA-based approach for ArcSAR imaging has been formulated yet. The main challenge in this context is that the solution of the stationary phase point cannot be resolved explicitly via Fourier transform (FT). This article proposes a new wavenumber domain imaging method, which exploits the sine law in the process of solving the stationary phase point during FT along the direction of the received echo using the triangular relationship formed by the target, the radar, and the rotation center of radar and then obtains the exact phase error expression in range and angular wavenumber domain without any approximation of the slant range or scanning angle. Using this formulation, we develop the corresponding phase error compensation method and complete image focusing. Through point target simulation and experiments on real ArcSAR data, the effectiveness of this method is verified in terms of imaging accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

This article presents an universal circular synthetic aperture radar (SAR) (UCSAR) by which the targets to be observed at any radial distance can be imaged, thus making SAR imaging possible in a more general scenario with a circular movement of the radar platform. The UCSAR point spread function (PSF) is firstly analyzed based on the time-domain correlation imaging approach, and thus a three-dimension (3-D) spatial variant PSF of the target can be formulated. The closed-form PSF expressions with single-frequency and frequency-modulated continuous wave (FMCW) transmitted signals are derived respectively to quantify the imaging resolutions, showing that the PSF is a product of a sinc function and a zeroth-order Bessel function when using a wideband FMCW signal. Secondly, a fast UCSAR imaging algorithm and its further simplified version are proposed to reduce the computational cost significantly based on the piecewise constant Doppler (PCD) principle. To quantify the imaging performance, we derive an error function of the slant range approximation for the proposed algorithm, serving as a practical guideline for the UCSAR parameter selection. Finally, the simulation and experimental results are provided to validate the PSF analysis, the fast imaging algorithm, and the implementation of the proposed UCSAR. [ABSTRACT FROM AUTHOR]

This article proposes an advanced THz multiple-input-multiple-output (MIMO) near-field sparse imaging scheme for target detection that uses single-pass synthetic aperture focusing and multipass interferometric synthetic aperture focusing techniques to improve imaging effectiveness and efficiency. It benefits from the MIMO of the linear sparse periodic array (SPA) and random undersampling sparse imaging to reduce sampling data and system cost. Both simulated and proof-of-concept experimental results have verified the scheme, revealing that the single-pass synthetic aperture imaging approach is sufficient to identify pure metallic targets with 3.87% of $\lambda /2$ sampling data. The multipass interferometric synthetic aperture imaging approach is capable of improving image quality on the image signal-to-noise ratio (SNR) and contrast, which is ideal for detecting more challenging targets. The random sparse imaging with help of the low-rank matrix completion (LRMC) technique has shown the promising potential of achieving equivalent image quality when further reducing 43.75% data in the experiment of five-pass imaging on a complex target; this corresponds to 82.51% data reduction compared to $\lambda /2$ sampling. [ABSTRACT FROM AUTHOR]

In the actual scene of interferometric inverse synthetic aperture radar (InISAR) imaging, the noncooperative targets may make a nonuniform 3-D rotational motion (3-D-RM), which contributes not only to the time-variant Doppler modulation but also to the spatial-variant wave path difference (SVWPD). This, in turn, seriously degrades the 3-D geometry reconstruction accuracy of the targets. Furthermore, it is an enormous challenge to realize InISAR imaging from sparse frequency band and sparse aperture (SFB-SA) signals. This article seeks to address the problems of fine image registration and 2-D joint sparse reconstruction (2-D-JSR) for InISAR imaging with SFB-SA signals. With regard to the maneuvering targets with 3-D-RM, a novel SVWPD signal model is established. Moreover, a new algorithm, named joint wave path difference compensation (JWPDC) algorithm, is developed to perform fine image registration. It can not only combine multiple channels to achieve image registration but also jointly compensate for the non-SVWPD (NSVWPD) and SVWPD. A joint multichannel 2-D-JSR (JMC-2-D-JSR) ISAR imaging algorithm is also proposed according to the SFB-SA signal model to produce high-resolution ISAR images. Underpinned by the Bayesian compressive sensing (BCS) theory, the JMC-2-D-JSR ISAR imaging can be realized by solving a sparsity-driven optimization problem via a modified quasi-Newton solver. Through iterative processing of JMC-2-D-JSR and JWPDC, the high-quality 3-D InISAR images of maneuvering targets with 3-D-RM can be obtained. Extensive experimental results based on both simulated and real data corroborate the effectiveness of the proposed algorithm that outperforms other available InISAR imaging frameworks in 2-D imaging, 3-D imaging, and motion compensation. [ABSTRACT FROM AUTHOR]

Radar imaging using the synthetic aperture radar (SAR) principle is a common method to obtain information about e.g., the surface of a target. However, most image formation algorithms for such systems assume (quasi-)static measurements. This may lead to errors in the processed images if the sensor is moving during the measurement process. This is especially the case for frequency-modulated continuous-wave (FMCW)-based sensors since the signal duration is longer than in a pulsed system and the achievable bandwidth is much larger and introduces additional challenges. Motion compensation in the context of radar imaging is usually related to the correction of deviations from an ideal trajectory. In contrast, this article presents a method to take the sensor movement during a single FMCW ramp into account and therefore addresses the effects caused by a continuous path during the transmit/receive process. Hence, faster movement can be achieved during the scanning of the synthetic aperture without being bound by stop-and-go approximations. In addition, it will be shown that the algorithm is suitable to reduce systematic errors due to aliasing caused by spatial sampling below the Nyquist rate. For this purpose, this article presents simulations and measurement results, obtained by an ultrawideband $D$ -band FMCW radar operating between 122 and 170 GHz. [ABSTRACT FROM AUTHOR]

Forward-looking multichannel synthetic aperture radar (FLMC-SAR) is an important tool for modern remote sensing applications, which has the capability to reconstruct the high-resolution image of the front area. However, due to the azimuth-variant characteristics of the motion errors over a long aperture, FLMC-SAR data processing is usually a challenging task, especially when involving the motion compensation (MOCO) coupled with Doppler ambiguity resolving. To accomplish an accurate MOCO for FLMC-SAR, a novel parametric azimuth-variant MOCO approach is proposed in this article. Aiming at the coupling problem of MOCO and Doppler ambiguity resolving over the full aperture, we can decouple them through the subaperture division. As a full synthetic aperture is decomposed into several subapertures, the high-order motion errors of the full aperture can be decomposed into the first-order motion errors of the subaperture. On this basis, the mismatch of the space–time spectrum caused by the motion errors can be solved by spectral estimation, yielding Doppler ambiguity resolving for each subaperture. Meanwhile, the azimuth-variant characteristic of motion errors in FLMC-SAR system is characterized by a parametric angle-dependent quadratic phase error (QPE) model. The motion parameters are estimated by a joint multichannel angle estimation-based signal quadratic decomposition method. Immediately, the MOCO for ambiguous targets with different motion errors can be processed separately to improve the imaging performance. Experimental results based on both simulated and real data demonstrate that the proposed method is suitable for FLMC-SAR system. [ABSTRACT FROM AUTHOR]

Inverse synthetic aperture radar (ISAR) imaging for the target with micro-motion parts is influenced by the micro-Doppler (m-D) effects. In this case, the radar echo is generally decomposed into the components from the main body and micro-motion parts of target, respectively, to remove the m-D effects and derive a focused ISAR image of the main body. For the sparse aperture data, however, the radar echo is intentionally or occasionally under-sampled, which defocuses the ISAR image by introducing considerable interference, and deteriorates the performance of signal decomposition for the removal of m-D effects. To address this issue, this paper proposes a novel m-D effects removed sparse aperture ISAR (SA-ISAR) imaging algorithm. Note that during a short interval of ISAR imaging, the range profiles of the main body of target from different pulses are similar, resulting in a low-rank matrix of range profile sequence of main body. For the range profiles of the micro-motion parts, they either spread in different range cells or glint in a single range cell, which results in a sparse matrix of range profile sequence. From this perspective, the low-rank and sparse properties are utilized to decompose the range profiles of the main body and micro-motion parts, respectively. Moreover, the sparsity of ISAR image is also utilized as a constraint to eliminate the interference caused by sparse aperture. Hence, SA-ISAR imaging with the removal of m-D effects is modeled as a triply constrained underdetermined optimization problem. The alternating direction method of multipliers (ADMM) and linearized ADMM (L-ADMM) are further utilized to solve the problem with high efficiency. Experimental results based on both simulated and measured data validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This communication presents a freehand imaging system, which takes full advantage of a compact multiple-input multiple-output (MIMO) radar to provide the real-time results by means of freehand movements. The system is based on a commercial radar-on-chip, equipped with four receivers and two transmitters, and an optical tracking system (i.e., motion capture system) for retrieving its position and attitude. The reduced size of the radar enables its handheld operation, making possible to create a synthetic aperture by moving the scanner over the area of interest. Due to the new degrees of freedom with respect to previous implementations based on quasi-monostatic topologies, a novel calibration strategy for the system is required in order to mitigate positioning errors. After calibration, the simulations and measurements are accomplished revealing that the novel freehand multistatic setup significantly outperforms the monostatic setup in terms of scanning speed and image quality. Multimedia material is provided to illustrate this performance. [ABSTRACT FROM AUTHOR]

This article investigates the pulse propagation in the near field of a transmitter and reflector from the perspective of radar sensing and imaging. The peaks of the radiated and reflected pulses were found to have traveled at superluminal speeds in the near field of radar. The conceptual explanation and experimental demonstration of the unique properties of the radiated and reflected pulses and their impact on near field radar imaging are presented in this article. To confirm the superluminal propagation, in this study, we considered several ultrawideband (UWB) sensors and scatterers. The physics behind the superluminal propagation and pulse shape change in the radar near field is demonstrated using the Huygens principle, and a method to improve the imaging of radar in the near field while using synthetic aperture techniques is also proposed. [ABSTRACT FROM AUTHOR]

The spatiotemporal coverage of a Moon-based synthetic aperture radar (SAR) is analyzed based on the imaging geometry, upon which the spatial coverage and image formulation rely. The distance from the Earth to the Moon-based SAR and bounds of the grazing and azimuthal angles jointly determine the coverage area on the Earth’s surface. Meanwhile, the ground coverage of the Moon-based SAR is determined by the bounds of the grazing and azimuthal angles and geographic coordinates of the nadir point at a specified time. Moreover, the temporal variation in the spatial coverage is pertinent to the temporally varying nadir point of the Moon-based SAR on the Earth’s surface. Furthermore, numerical simulations using the lunar ephemeris data are carried out to complement the analysis and to illustrate the spatiotemporal coverage. Finally, a guideline for the optimal site selection of a Moon-based SAR is proposed. In conclusion, a Moon-based SAR has the potential to perform long-term, continuous Earth observations on a global scale to enhance our capability to understand the planet. [ABSTRACT FROM AUTHOR]

Forward-looking imaging and target detection are highly desirable in many military and civilian fields, such as search and rescue, sea surface surveillance, airport surveillance, and guidance. However, there is a blind zone of forward-looking imaging for conventional Doppler beam sharpening and synthetic aperture radar. Scanning radar can be utilized to obtain a real beam image of a forward-looking area and implement target detection, while its azimuth resolution is poor due to the limitation of antenna size. Besides, during the processing procedure, imaging and target detection are usually regarded as two independent parts, which means that the imaging result will directly affect the detection performance. In this article, an integrated algorithm of super-resolution imaging and target detection for forward-looking scanning radar is proposed. In this algorithm, first of all, low-rank and sparse constraints as regularization norms are incorporated into the forward-looking scanning radar imaging and the objective function is established. Subsequently, the convex theory is utilized to solve the objective function and transform the problem of simultaneous super-resolution imaging and target detection into an optimization problem. Lastly, the super-resolution imaging and the target detection results are obtained simultaneously by solving the optimization problem using the alternating direction method of multipliers. In addition, simulation and experiment results are given to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The piecewise constant Doppler (PCD) algorithm is a novel radar imaging process recently proposed for the generalized continuous-wave synthetic aperture radar (GCW-SAR). This article presents a detailed theoretical analysis on the PCD algorithm's performance and proposes a further complexity-reduced PCD algorithm with motion compensation (MOCO) suitable for practical applications. First, the difference between conventional SAR imaging and PCD imaging, i.e., the zeroth-order versus the first-order slant range approximation, is revealed. Exact ambiguity function expressions of the PCD imaging in range and azimuth directions, respectively, are then derived. An error function of the PCD imaging as compared with the ideal matched filtering method is further defined and shown to be a function of an image quality factor, which can be used to quantify the PCD imaging performance. Finally, a faster and more flexible imaging process, called decimated PCD algorithm, is proposed, by which the image azimuth spacing can be easily extended, and hence, the computational complexity can be significantly reduced. The decimated PCD implementation incorporated with the MOCO is developed for practical GCW-SAR applications, and its imaging error lower-bounded by the PCD imaging error function is analyzed accordingly. Simulation and experimental results validate the theoretical analysis of the PCD imaging and show that the decimated PCD algorithm can achieve a high imaging quality at low cost. [ABSTRACT FROM AUTHOR]

A W-band multiple-input multiple-output (MIMO) radar imaging system has been proposed. The $4 \times 4$ radar system that forms a 2-D virtual array operates at a center frequency of 94 GHz and bandwidth of 1 GHz with frequency-modulated continuous wave. A hybrid scheme comprising time- and frequency-division multiplexing is introduced for establishing orthogonal waveforms, where the transmit channels perform alternate transmission in pairs. The proposed scheme can efficiently extend the number of MIMO channels utilizing the existing hardware with simultaneous transmission. The design, implementation, measurements, and imaging results of the proposed radar system have been presented. The imaging performance was tested through outdoor experiments. The high-resolution performance was shown with images generated using a synthetic aperture radar. The impulse responses of all channels were measured, and the resolution was confirmed to be 0.15 m in all the channels. In addition, a human and a car at 100-m range were imaged using the proposed radar system. The polarimetric and interferometric capabilities were tested for multimode imaging with the MIMO configuration. Overall, the measurements and experimental results verified the feasibility of the proposed MIMO radar with hybrid scheme as a high-resolution multimode imaging system. [ABSTRACT FROM AUTHOR]

Automatic vehicle detection from a video synthetic aperture radar (VideoSAR) system presents significant potential to enhance the surveillance performance in dynamic region of interest (DROI). In this paper, a novel VideoSAR low-rank plus sparse decomposition (LRSD) perspective for single-channel single-pass configuration is proposed to track the ground defocusing vehicles. Vehicle imaging features with 2-D motion parameters are derived theoretically by exploiting a priori knowledge of polar format algorithm (PFA). In accordance with the revealed characteristics, a vision-based VideoSAR-LRSD algorithm, called three-term decomposition (TTD) with proximal exchange-based alternating directions method of multipliers (PEADMM), is then proposed to improve the performance of vehicle detection. It can be used to break the limitation for the application of emergency response not permitting the acquisition of multi-channel or multi-pass data. We comprehensively demonstrate using extensive VideoSAR DROI experiments that in comparison with the state-of-the-art algorithms, TTD-PEADMM algorithm presents the improved accuracy and is able to offer competitive results. [ABSTRACT FROM AUTHOR]

In this paper, we extend the forward-scanning synthetic aperture radar (SAR) methodology to reconstruct images of the moving targets, for a forward-looking automotive radar. We adapt a matrix decomposition approach to forward-scanning SAR in order to separate moving targets from clutter/stationary objects. To solve our optimization problem, we propose an iterative solution based on augmented Lagrangian method. Image focusing, over the synthetic aperture, is achieved through spatial segmentation and cross-correlation maximization. Our proposed method results in well-focused imaging of the moving targets with enhanced angular resolution. Experimental results from simulation as well as real-data corroborate our proposed methodology. [ABSTRACT FROM AUTHOR]

A novel generalized continuous-wave synthetic aperture radar (GCW-SAR) based on deramp-on-receive operating in millimeter-wave frequency is proposed in this article. With deramp-on-receive, the receiver sampling rate is drastically reduced, and the downsampled 1-D raw data can be obtained from the received beat signal. Further adopting piecewise constant Doppler (PCD) imaging in the digital domain, a GCW-SAR image can be easily reconstructed by using the existing frequency-modulated continuous-wave (FMCW) radar system. The effects of deramp-on-receive in PCD imaging are analyzed accordingly. The short wavelength of the millimeter-wave carrier used in the proposed GCW-SAR enables high azimuth resolution as well as a short synthetic aperture, which, in turn, significantly reduces the imaging computational complexity. Simulation and experimental results confirm the advantages of the proposed GCW-SAR. [ABSTRACT FROM AUTHOR]

Generally, high-resolution imaging for highly squinted synthetic aperture radar (SAR) data is a difficult problem due to large range migration. Thus, when trying to solve this nontrivial problem, an azimuth-variant Doppler will arise, thereby leading to phase errors containing the azimuth spatial-variant (ASV) component. In this article, we analyze the characteristics of highly squinted SAR data and propose a new full-aperture ASV phase error autofocus algorithm. In this new algorithm, the accurate and suitable phase error signal model for highly squinted SAR data is derived. Moreover, the closed-form solution of the relationship between a distorted image and a focused image is also explicitly revealed. Furthermore, in this newly proposed algorithm, an accurate estimation of nonlinear ASV phase error is established based on the maximum contrast of the SAR imagery. In addition, an iterative gradient-based solver is introduced. The advantage of this new method provides a simple yet effective approach while being able to eliminate the ASV phase errors. More importantly, the accuracy of this new method using the full-aperture data is independent of SAR imaging algorithms. As a result, the proposed new method can be easily embedded in many existing imaging algorithms to produce focused imagery. Finally, two real highly squinted SAR data sets are provided to validate the advantages of our algorithm. [ABSTRACT FROM AUTHOR]

The inverse synthetic aperture radar (ISAR) imaging technique of a moving target with sparse sampling data has attracted wide attention due to its ability to reduce the data collection burden. However, traditional low-rank or 2D compressive sensing (CS)-based ISAR imaging methods can handle the random sampling or the separable sampling data only. When the specific data collection condition cannot be satisfied, low-rank or 2D CS-based methods cannot provide satisfactory imaging results any more. To remedy this problem, in this paper, we proposed a joint low-rank and sparsity priors’ constrained model for ISAR imaging with various sparse data patterns. This model is inspired by the facts that the received radar data have a low-rank property and the ISAR image is sparse on the specific dictionary. Two reconstruction algorithms to solve the double priors’ constrained optimization problem are developed under the alternative direction method of multipliers (ADMM) framework with the help of augmented Lagrange multipliers (ALM). Results on simulation data and real data show that the proposed methods are quite effective in recovering missing samples and focused image and perform better than the matrix completion-based method and the sparse representation-based method when dealing with the various kinds of sparse sampling data. [ABSTRACT FROM AUTHOR]

In this paper, we propose a forward scanning synthetic aperture radar methodology for a forward-looking automotive (low-terahertz) radar, which combines scene scanning with synthetic aperture processing, resulting in enhanced angular resolution and improved imaging. We propose two algorithms, first, a modified back-projection (BP) algorithm and, second, a compressed sensing-based BP algorithm. We suggest techniques to reduce computational complexity of the proposed algorithms. Results of simulation and real-data experiments corroborate the validity of our proposed methodology and algorithms. [ABSTRACT FROM AUTHOR]

The radar echoes of space debris sometimes have drawbacks of inadequate pulse samples, self-occlusion, and data missing, while the state-of-art radar imaging algorithms become unproductive. To tackle this problem, this paper proposes a novel method for three-dimensional (3-D) imaging of space debris. This iterative algorithm terminates automatically and can recover the intensity of space debris radar cross section, making it practical in real-world applications. Unlike the 3-D imaging methods based on multistatic inverse synthetic aperture radar, the proposed method is applicable to monostatic ISAR. [ABSTRACT FROM AUTHOR]

In the Part 1 of this two-part study, we present a method of imaging and velocity estimation of ground moving targets using passive synthetic aperture radar. Such a system uses a network of small, mobile receivers that collect scattered waves due to transmitters of opportunity, such as commercial television, radio, and cell phone towers. Therefore, passive imaging systems have significant cost, manufacturing, and stealth advantages over active systems. We describe a novel generalized Radon transform-type forward model and a corresponding filtered-backprojection-type image formation and velocity estimation method. We form a stack of position images over a range of hypothesized velocities, and show that the targets can be reconstructed at the correct position whenever the hypothesized velocity is equal to the true velocity of targets. We then use entropy to determine the most accurate velocity and image pair for each moving target. We present extensive numerical simulations to verify the reconstruction method. Our method does not require a priori knowledge of transmitter locations and transmitted waveforms. It can determine the location and velocity of multiple targets moving at different velocities. Furthermore, it can accommodate arbitrary imaging geometries. In Part 2, we present the resolution analysis and analysis of positioning errors in passive SAR images due to erroneous velocity estimation. [ABSTRACT FROM PUBLISHER]

Synthetic transmit aperture (STA) imaging is susceptible to tissue motion because it uses summation of low-resolution images to create the displayed high-resolution image. A method for 2-D tissue motion correction in STA imaging is presented. It utilizes the correlation between highresolution images recorded using the same emission sequence. The velocity and direction of the motion are found by cross correlating short high-resolution lines beamformed along selected angles. The motion acquisition is interleaved with the regular B-mode emissions in STA imaging, and the motion compensation is performed by tracking each pixel in the reconstructed image using the estimated velocity and direction. The method is evaluated using simulations, and phantom and in vivo experiments. In phantoms, a tissue velocity of 15 cm/s at a 45° angle was estimated with relative bias and standard deviation of -6.9% and 5.4%; the direction was estimated with relative bias and standard deviation of -8.4% and 6.6%. The contrast resolution in the corrected image was -0.65% lower than the reference image. Abdominal in vivo experiments with induced transducer motion demonstrate that severe tissue motion can be compensated for, and that doing so yields a significant increase in image quality. [ABSTRACT FROM PUBLISHER]

Most of existing through-the-wall radar imaging (TWRI) algorithms deal with a single layer homogeneous wall in two-dimensional scenario. In this communication we present a generalized three-dimensional (3-D) beamforming algorithm for the focused imaging of targets behind multilayered building walls. The far field layered medium Green's function is incorporated in the 3-D beamformer for the compensation of the wall effect. 3-D polarimetric imaging is exploited in TWRI for enhanced target identification and feature extraction as well as wall effect mitigation. Numerical results show that the proposed 3-D beamformer provides high quality focused images in various wall-target scenarios. [ABSTRACT FROM AUTHOR]

We present a method to generate three-dimensional (3D) inverse synthetic aperture radar (ISAR) images of a target at arbitrary aspect angles using the shooting and bouncing ray (SBR) method. We have derived a 3D-image-domain ray-tube integration formula based on the SBR technique. The imaging formula is in a form of convolution, then a nonuniform fast Fourier transform (NUFFT) is induced to achieve the convolution, which can be used to generate 3D ISAR images rapidly. Compared to the conventional algorithm where the ISAR images are obtained by inverse Fourier transforming the computed scattered fields over a range of frequencies and a range of aspect angles, the new formula needs only one-time ray tracing and physical optics (PO) integration over a small angle span. Hence the computational time is decreased tremendously. The ISAR images of a missile target and an armored car for several aspect angles are presented to demonstrate the efficiency and accuracy of the proposed method. [ABSTRACT FROM PUBLISHER]