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Gradient index (GRIN) lenses embody a powerful technology that enables control of electromagnetic wave propagation over wide frequency bands. However, GRIN lenses that achieve multifunctional (i.e., dual broadband) performance have not been realized mainly due to the limitations of conventional techniques such as Transformation Optics (TO). This paper proposes a multi‐objective inverse‐design approach for the optimization of multi‐band GRIN lenses with highly constrained aperture sizes. A candidate lens design is fabricated from a ceramic material using a new additive manufacturing approach allowing for spatially‐varying permittivities between 2–6.5 to be achieved at sub‐cm resolution. Measured results validate the candidate functionalized ceramic GRIN lens's simulated multi‐band performance and demonstrate the efficacy of the proposed inverse‐design procedure. [ABSTRACT FROM AUTHOR]

As a new imaging framework, the rotating synthetic aperture radar (ROSAR) derives a synthetic aperture through antenna rotation instead of traditional linear platform motion. The rotational synthetic aperture is sensitive to high-frequency vibrations aboard helicopters. The vibration causes severe phase error in signal echoes and imaging degradation. Unlike traditional synthetic aperture radar (SAR) imaging where range-Doppler algorithm (RDA) maybe applied for autofocus to improve the imaging performance, vibration phase errors cannot be estimated via conventional imaging algorithms due to severe range and azimuth couplings. A new ROSAR imaging procedure is proposed to compensate the phase error resulting from high-frequency vibrations of helicopters. A vibration model of ROSAR signal echo is established. The double Doppler keystone transform (DDKT) is adopted to correct the range cell migration (RCM) induced by slant range history and vibration errors. Analytical echo expression with range-independent vibration phase error is also derived in greater details. The focused image can then be obtained via classical autofocus algorithms. The effectiveness of the proposed technique is sufficiently demonstrated through simulation studies. [ABSTRACT FROM AUTHOR]

This letter deals with the issue of clutter suppression with the helicopter-borne single-channel rotating synthetic aperture radar (SCRoSAR). Commonly, obtaining an synthetic aperture radar (SAR) image and implementing the ground moving target indication (GMTI) simultaneously is a challenging task for the single-channel SAR (SCSAR), since, the clutter background covers most of the slow-moving targets in the SAR image. In this letter, we propose a novel clutter suppression method via the time-Doppler chirp varying (TDCV) approach for the SCRoSAR system. A traditional RoSAR imaging algorithm and a modified RoSAR-TDCV imaging algorithm are employed to generate an original image and a TDCV image from the same set of data, respectively. Benefits from the characteristics of the TDCV approach, the position of moving targets will be shifting along the range direction in the TDCV image. Meanwhile, the position displacement of stationary clutter scatterers is neglectable. Therefore, via image cancellation, the clutter background can be significantly suppressed. With the proposed approach, the RoSAR system is capable of imaging the stationary objects and revealing the moving targets, simultaneously. The experimental results with simulated data demonstrate the validation of our proposed method. [ABSTRACT FROM AUTHOR]

A range-ambiguous clutter suppression approach based on extended azimuth phase coding (EAPC) is proposed to handle the range ambiguity of the multiple-input multiple-output synthetic aperture radar (MIMO-SAR) system for ground moving target indication (GMTI) application. The echoes from different ambiguous range regions can be well separated in the transmit spatial frequency domain by properly designing the EAPC shift factor. In the sequel, a set of transmit filters are employed to extract the echoes of each ambiguous region independently. Then the azimuth deramp operation is applied to the extracted data to focus the target energy of the desired region while the residual target energy of other regions is still smeared due to the mismatched reference function. After this, the adaptive matched filtering algorithm is adopted to suppress the clutter and detect the moving target. Finally, numerical simulation experiments are presented to demonstrate that the developed framework can obtain good results for range-ambiguous clutter suppression and ground moving target detection. [ABSTRACT FROM AUTHOR]

There is a conflict between increasing the image swath and improving the azimuth resolution in a conventional single-channel synthetic aperture radar (SAR) system. This paper introduces a method of realizing high-resolution and wide-swath (HRWS) SAR imaging with a multiple-input multiple-output (MIMO) system based on a space-pulse phase coding (SPPC) technique, which makes it possible to discriminate and separate the echoes from multiple ambiguous range regions through coding the phases of the transmitted pulses in each spatial channel. Two coding schemes, referred to as the uniform-cyclic coding and the uniform-acyclic coding, respectively, are devised for discriminating the range-ambiguous echoes. By choosing a proper phase gradient factor, both coding schemes can be used to resolve the range ambiguities. The uniform-cyclic coding scheme presents a little better performance of the range ambiguity suppression, and the uniform-acyclic coding scheme can preserve the coherency of the range-ambiguous clutters. Simulation results have demonstrated the effectiveness of the proposed coding schemes. [ABSTRACT FROM AUTHOR]

Beamforming plays a crucial role in synthetic aperture radar (SAR) for interference mitigation and ambiguity unaliasing. In this article, a series of novel beamforming methods for SAR systems is proposed based on nulling the transceive beampattern accurately in frequency diverse array (FDA)-multiple-input and multiple-output (MIMO) scheme. In general, these methods are implemented by assigning artificial interferences with prescribed powers within the given rectangular regions in the joint transmit–receive spatial frequency domain. In specific, according to the predefined null depths, closed-form expressions of artificial interference powers are first formulated. Then, iteration algorithms are developed to update the interference-plus-noise covariance matrix and the designed weight vector. In such a way, a trough-like transceive beampattern with arbitrarily distributed broadened nulls is formed in the joint transmit–receive spatial frequency domain. As a result, interferences mixed in signals received by SAR can be suppressed effectively. Numerical simulations and experimental results are provided to corroborate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

The clutter suppression and target radial velocity estimation are essential in the ground moving target indication processing with multichannel synthetic aperture radar (SAR) systems. In reality, the heterogeneous clutter, the image coregistration error, and channel mismatch will remarkably decline the estimation performance of the target radial velocity. To address these issues, a robust radial velocity estimation algorithm is proposed in this letter. Based on the joint-pixel signal model, the joint-pixel normalized sample covariance matrix (JPNSCM) is employed to mitigate the effect of heterogeneous clutter, and the shift vector determined by JPNSCM is used to obtain the actual target steering vector. Then, the adaptive matched filtering algorithm is adopted to estimate the target radial velocity. Compared with traditional estimation algorithms, the proposed method obtains better performance in both simulations and real SAR data experiments. [ABSTRACT FROM AUTHOR]

A rotating synthetic aperture radar (RoSAR) can image the environment in 360° on a stationary platform because it uses rotating antennas. The range-variant distortion in azimuth is evident in the RoSAR system, which degrades the imaging quality, particularly in high-resolution situations. In this letter, a new chirp $z$ transform (CZT) imaging algorithm is developed to remove the range-variant distortion in azimuth for helicopter-borne RoSAR systems. Based on a fourth-order approximation of the slant range model, a precise expression of the 2-D spectrum of the echo is derived via the series reversion method. The spatial-variant characteristics of the range cell migration term and the second range compression term are analyzed and compensated. Then, according to the analysis on the range-dependent output sample spacing variation in azimuth, which is caused by the RoSAR configuration, an efficient CZT is proposed to remove the range-variant distortion in azimuth. The experimental results with simulated data are provided to clearly demonstrate the proposed approach. [ABSTRACT FROM AUTHOR]

In the presence of range ambiguity, the synthetic aperture radar (SAR) systems suffer from image aliasing, which dramatically degrades the quality of SAR images. In this article, an easy-to-implement technique for range ambiguity suppression is investigated, which is based on phase coding in the transmit pulse dimension, referred to as pulse phase coding (PPC). By properly designing the PPC series, it is possible to discriminate the range ambiguous echoes from different range areas in the Doppler frequency domain. To further suppress the range ambiguous echo, a two-pulse cancellation (TPC)-based SAR imaging method is proposed, which improves the quality of SAR images in the presence of range ambiguity. The proposed two-pulse cancellation is performed followed by the azimuth compression. The simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR), as a wideband radar system, is easy to be interfered by radio frequency systems, such as the radio, television, and cellular works. Since the narrowband radio frequency interference (RFI) has a relatively fixed frequency during the synthetic aperture time, it is removed as a low-rank term of the received signal in recent research. In this paper, we employ a novel “low-rank + sparse” decomposition model to extract the low-rank RFI and protect the strong scatterers of a useful signal, which is explicit and more efficient than the previous augmented Lagrange function model. Because the radar signal is complex, we exploit soft thresholding instead of hard thresholding in the Go Decomposition algorithm, which is defined as the revised traditional decomposition (RTD) method. Soft thresholding can recover the phase term correctly for a further focused image. Both the previous augmented Lagrange method and the proposed RTD method need to search the values of user parameters with high computational complexity. In order to eliminate the bother of tuning user parameters, a parameter-free decomposition (PFD) method is proposed to adaptively estimate the user parameters. Also, by considering the property of the useful signal, the PFD method protects the useful signal with adaptive thresholds for each snapshot. It has a better performance for RFI suppression, but costs slightly more computational time compared with the RTD method. The real SAR data and the measured RFI are provided to demonstrate the correctness of the proposed methods. [ABSTRACT FROM AUTHOR]

The synthetic aperture radar (SAR), as a wideband radar system, operates over a large frequency band ranging from the low very high frequency to millimeter waves. It often overlaps in frequency with other radio-frequency systems including radio, television, and cellular networks. Therefore, radio-frequency interference (RFI) suppression is the severe test for SAR systems. Recently, some methods are proposed to suppress the RFI based on the sparse recovery in range-frequency domain and low-rank extraction in the azimuth dimension. However, all the previous methods exploit one property of the RFI, which may leave the room for performance improvement. Hence, in this paper, we propose three methods to jointly exploit the sparsity and low-rank property of RFI. We first include the sparse term and low-rank term of the RFI in the objective function to separate the RFI and the useful signal, which is defined as the joint sparsity and low-rank property method. It has better performance but heavier computational burden than the algorithm employing only the low-rank property. Then, we use row-sparse (RS) concept in lieu of the two properties, since the narrowband RFI has relatively stable frequencies during the synthetic aperture time. The RS method avoids the low-rank optimization and dramatically decrease the computational burden. Also for the real radar system, the sampling frequency is commonly larger than the frequency bandwidth. Therefore, there are some redundant data in the received signal. We exploit both the downsampling operation and the RS concept to speed up the convergence, which is called the fast row-sparse (FRS) method. The FRS method can further eliminate the out-of-mainband RFI. The real SAR data are provided to demonstrate the effectiveness of the three proposed methods. [ABSTRACT FROM AUTHOR]

Helicopter‐borne rotating synthetic aperture radar (ROSAR) enjoys fast imaging property as the synthetic aperture obtained by rotor rotation. However, ROSAR data processing is usually a challenging task due to severe range cell migration (RCM) and motion error. To solve this problem, an enhanced phase gradient autofocus (PGA) algorithm based on helicopter‐borne ROSAR wavenumber‐domain imaging approach is proposed in this study, which alleviates the imaging performance degradation due to the RCM and motion error. With even small motion error induced in the wavenumber domain, the influence of motion error will become evident after performing Stolt interpolation, which induces serious image defocusing and degradation. Hence, the authors further propose the PGA‐based ROSAR motion compensation scheme, which combines quadratic term correction with phase gradient estimation, and well‐focused ROSAR images can be obtained via iterative processing. Several results of simulated experiments are presented to validate the proposed method for helicopter‐borne ROSAR imaging. [ABSTRACT FROM AUTHOR]

The conflict between range and azimuth ambiguities is a challenging problem for spaceborne high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) imaging. In this letter, a novel ambiguity resolution approach based on frequency diverse array (FDA) is proposed to retrieve unambiguous signal from that with ambiguities in both range and azimuth domains. By exploiting the range-angle-dependent property of transmit steering vector in FDA and applying the second range dependence compensation approach, echoes from different ambiguous regions are separable in transmit spatial-Doppler frequency domains. Then a corresponding transmit beamformer is designed to extract spectrum component of each ambiguous region, which can be rearranged to comprise the desired unambiguous signal. Compatible with most existing azimuth ambiguity suppression algorithms which employ the receive degrees of freedom, the proposed approach can further enhance the capability of resolving ambiguity for HRWS SAR systems, and its effectiveness is verified by simulation experiments. [ABSTRACT FROM PUBLISHER]

Conventionally, a single-channel synthetic aperture radar (SC-SAR) system can hardly detect weak moving targets simply. In this paper, a time-Doppler chirp-varying (TDCV) filter is proposed for ground moving target indication and parameter estimation with the airborne SC-SAR system. The proposed method is easy to implement and mainly includes three steps. First, a traditional 2-D frequency range-Doppler algorithm is used to generate an original image. Second, the second-order range cell migration (RCM) phase term is partly compensated in the range frequency and azimuth time domain, and the rest of second-order RCM phase term is compensated in 2-D frequency domain. The whole processing, which is referred to as the TDCV approach, is employed to acquire a new TDCV image. Third, compared the original image with the new image, the clutter scatterers are nearly motionless while the moving targets are translated along the range direction due to their nonzero radial velocities. After the cancellation between two normalized images, the clutter background would be significantly suppressed since the two images generated by the same data. As a result, the moving targets can be indicated and the range difference of the moving target between two images can be exploited to estimate their radial velocities. The results obtained by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this paper. [ABSTRACT FROM PUBLISHER]

In spaceborne synthetic aperture radar (SAR), it is a challenging problem to realize high resolution and wide swath imaging (HRWS) due to the conflict between Doppler and range ambiguities. To mitigate this conflict, a range ambiguity resolution approach for HRWS SAR imaging using frequency diverse array (FDA) is proposed in this paper. The FDA employs a set of slightly different carrier frequencies, each of which is emitted by an individual array element. Frequency diversity introduces wave-path difference among the array elements, thus resulting in the range-angle-dependent property of transmit steering vector. Utilizing the extra degrees-of-freedom in range domain, FDA is capable of distinguishing the range ambiguous echoes in the spatial frequency domain. In our approach, the range ambiguous echoes are compensated by range dependence compensation (RDC) technique in the transmit spatial frequency domain. In the sequel, the range ambiguous echoes are separated by using a series of transmit beamformers as the echoes from different range regions are discriminable. Finally, traditional imaging processing is performed on the reconstructed unambiguous data to achieve HRWS imaging. Simulation results have verified the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]

Clutter suppression and ground moving target indication (GMTI) are challenging tasks for multichannel synthetic aperture radar (MC-SAR) systems. In recent years, robust principal component analysis (RPCA), such as the augmented Lagrange multiplier method (ALM) and go decomposition (GoDec) algorithm, has drawn considerable attention for its excellent performance in distinguishing the different parts from a set of correlative database. In this letter, an efficient along-track interferometry GoDec (ATI-GoDec) approach is proposed for GMTI in MC-SAR systems under a strong clutter background. The proposed method can be separated into two sections: the predetection and the postdetection. The predetection by an efficient ATI RPCA method can decrease missing targets, and postdetection with a novel magnitude and phase (M&P) detection has the ability to reduce the false targets. As a result, the proposed method can provide a more robust performance by a comparison to the traditional ATI detection. It can also widen the tolerant values of the preset cardinality and decrease the probability of false alarm compared with the conventional GoDec algorithm. Moreover, the proposed method only takes several iterations to reach the convergence by solving the optimization problem of the RPCA model, which makes it more efficient than the previous RPCA methods. The results by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this letter. [ABSTRACT FROM PUBLISHER]

Efficient motion parameter estimation is a key challenge for moving-target imaging and localization in the synthetic aperture radar ground moving-target indication system. However, the existing methods suffer from ambiguities, complex realization, or heavy computation load of $O(MN)$. To solve these problems, we propose an efficient Radon transform (RT) and an efficient fractional Fourier transform (FRFT) to estimate the radial velocity and azimuth velocity. By exploiting the geometry information, we model a geometry relationship between the motion parameters and two transform angles of RT or FRFT. The matched motion parameters can be estimated by the geometry relationship of the mismatched results, and the computation complexity is reduced from $O(MN)$ to $O(2N)$ effectively. Additionally, the symmetry property can be used for clutter canceling. Simulated and experimental results demonstrate the validity of the proposed methods. Compared with conventional motion parameter estimation methods, the proposed methods are much more efficient in acquiring accurate estimation results. [ABSTRACT FROM PUBLISHER]

High-resolution and wide-swath (HRWS) imaging is highly desired in future synthetic aperture radar (SAR) systems. However, it is a contradictory requirement between high azimuth resolution and wide unambiguous swath coverage in a traditional SAR system. This paper proposes a novel solution to realize HRWS imaging by resolving the range ambiguity through a phase coding technique. The phase coding is employed in both spatial channels and slow time pulses. By properly designing the coding scheme, it is possible to separate the echoes from multiple ambiguous range regions from each other in the spatial domain. For each particular range region, the corresponding optimized receive beampattern can be used to extract the desired echoes from the presumed range region and suppress the undesired echoes from other range-ambiguous regions. The residual range-ambiguous echoes are also addressed. Specifically, it is capable of further mitigating the residual range-ambiguous echoes by optimally designing the coding scheme and the transmit beampattern. In the final, a bank of imaging processors can be implemented to obtain the high-resolution images of these range regions, which can be synthesized into a whole HRWS SAR image of the scene of interest. Simulation results have demonstrated the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]