Search

Interferometric synthetic aperture radar (InSAR) and tomographic SAR measurement techniques are commonly used for the three-dimensional (3D) reconstruction of complex areas, while the effectiveness of these methods relies on the interferometric coherence among SAR images with minimal angular disparities. Radargrammetry exploits stereo image matching to determine the spatial coordinates of corresponding points in two SAR images and acquire their 3D properties. The performance of the image matching process directly impacts the quality of the resulting digital surface model (DSM). However, the presence of speckle noise, along with dissimilar geometric and radiometric distortions, poses considerable challenges in achieving accurate stereo SAR image matching. To address these aforementioned challenges, this paper proposes a radargrammetric method based on the composite registration of multi-aspect SAR images. The proposed method combines coarse registration using scale invariant feature transform (SIFT) with precise registration using normalized cross-correlation (NCC) to achieve accurate registration between multi-aspect SAR images with large disparities. Furthermore, the multi-aspect 3D point clouds are merged using the proposed radargrammetric 3D imaging method, resulting in the 3D imaging of target scenes based on multi-aspect SAR images. For validation purposes, this paper presents a comprehensive 3D reconstruction of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) using Ka-band airborne SAR images. It does not necessitate prior knowledge of the target and is applicable to the detailed 3D imaging of large-scale areas with complex structures. In comparison to other SAR 3D imaging techniques, it reduces the requirements for orbit control and radar system parameters. To sum up, the proposed 3D imaging method with composite registration guarantees imaging efficiency, while enhancing the imaging accuracy of crucial areas with limited data. [ABSTRACT FROM AUTHOR]

Airborne VHR SAR image registration is a challenging task. The number of CPs is a key factor for complex CP-based image registration. This paper presents a two-step matching approach to obtain more CPs for VHR SAR image registration. In the past decade, SIFT and other modifications have been widely used for remote sensing image registration. By incorporating feature point location affine transformation, a two-step matching scheme, which includes global and local matching, is proposed to allow for the determination of a much larger number of CPs. The proposed approach was validated by 0.5 m resolution C-band airborne SAR data acquired in Sichuan after the 2008 Wenchuan earthquake via a SAR system designed by the IECAS. With the proposed matching scheme, even the original SIFT, which is widely known to be unsuitable for SAR images, can achieve a much larger number of high-quality CPs than the one-step SIFT–OCT, which is tailored for SAR images. Compared with the classic one-step matching approach using both the SIFT and SITF–OCT algorithms, the proposed approach can obtain a larger number of CPs with improved precision. [ABSTRACT FROM AUTHOR]

As polarimetric antennas can be isolated through excellent electronic frameworks in circular quad-polarization (CQP) synthetic aperture radar (SAR) systems, cross-polarization (x-pol) and co-polarization (co-pol) channel imbalances are more challenging and essential to calibrate than crosstalk in polarimetric calibration (PolCAL). In uncalibrated CQP SAR images without corner reflectors (CRs), the reciprocity and reflection symmetry assumptions of the distributed targets are commonly used to estimate the x-pol and co-pol channel imbalances, respectively. To suppress the influence of additive noise on determining channel imbalances through distributed targets, high signal-to-noise ratio (SNR) distributed targets should be obtained from the x-pol and co-pol channels of the CQP SAR images: namely, surface-dominated and volume-dominated targets. However, some reflection symmetry assumptions used in the existing calibration literature have poor applicability with volume-dominated targets, resulting in unsatisfactory estimation results for the co-pol channel imbalance phase. In this paper, we assess the priority of the reflection symmetry properties of volume-dominated targets used to calibrate the co-pol channel imbalance phase in CQP SAR data synthesized from linear quad-polarization data of ALOS, GF-3, and RADARSAT-2. In the theoretical part, high-priority reflection symmetry (termed semireflection symmetry) assumptions are confirmed as the most suitable for estimating the co-pol channel imbalance phase, and were selected to develop an algorithm for estimating the co-pol channel imbalance phase. Furthermore, based on the novel method for estimating the co-pol channel imbalance phase, a channel imbalance calibration scheme is proposed for CQP SAR systems with reciprocal crosstalk, including extracting surface-dominated and volume-dominated targets, and estimating and filtering channel imbalances. We demonstrate the effectiveness of our proposed scheme with CRs in simulated CQP SAR images. The experimental results show that the calibration scheme is an effective workflow for estimating channel imbalances in CQP SAR systems with reciprocal crosstalk. [ABSTRACT FROM AUTHOR]

Space-time waveform-encoding (STWE)-synthetic aperture radar (SAR) is an effective way to accomplish high-resolution and wide-swath (HRWS) imaging. By designing the specific signal transmit mode, the echoes from several subswaths are received within a single receiving window and overlap each other in STWE-SAR. In order to separate the overlapped echoes, the linear-constrained minimum variance (LCMV) beamformer, a single-null beamformer, is typically used. However, the LCMV beamformer has a very narrow and unstable notch depth, which is not sufficient to accurately separate the overlapped echoes with large signal energy differences between subswaths. The issue of signal energy differences in STWE-SAR is first raised in this paper. Moreover, a novel echo separation scheme based on a second-order cone programming (SOCP) beamformer is proposed. The beam pattern generated by the SOCP beamformer allows flexible adjustment of the notch width and depth, which effectively improves the quality of separation results compared to the LCMV beamformer. The simulation results illustrate that the scheme can greatly enhance the performance of echo separation. Furthermore, the experimental results based on the X-band STWE-SAR airborne system not only demonstrate the scheme's effectiveness but also indicate that it holds great promise for future STWE-SAR missions. [ABSTRACT FROM AUTHOR]

In this paper, a method of Synthetic Aperture Radar (SAR) image Automatic Target Recognition (ATR) based on Convolution Auto-encode (CAE) and Support Vector Machine (SVM) is proposed. Using SVM replaces the traditional softmax as the classifier of the CAE model to classify the feature vectors extracted by the CAE model, which solves the problem that the softmax classifier is less effective in the nonlinear case. Since the SVM can only solve the binary classification problem, and in order to realize the classification of the class objectives, the SVM were designed to achieve the classification of the input samples. After unsupervised training for CAE, the coding layer is connected with SVM to form a classification network. CAE can extract the features of the data by an unsupervised method, and the nonlinear classification advantage of SVM can classify the features extracted by CAE and improve the accuracy of the object recognition. At the same time, the high-accuracy identification of key targets is required in some special cases. A new initialization method is proposed, which initializes the network parameters by pretraining the key targets and changes the weights of different targets in the loss function to obtain better feature extraction, so it can ensure good multitarget recognition ability while realizing the high recognition accuracy of the key targets. [ABSTRACT FROM AUTHOR]

The Wishart mixture model is an effective tool for characterizing the statistical distribution of polarimetric synthetic aperture radar (PolSAR) data. However, due to the difficulty in determining the equivalent number of looks, the Wishart mixture model has some problems in terms of practicality. In addition, the flexibility of the Wishart mixture model needs to be improved for complicated scenes. To improve the practicality and flexibility, a new mixture model named the relaxed Wishart mixture model (RWMM) is proposed. In RWMM, the equivalent number of looks is no longer considered a constant for the whole PolSAR image but a variable that varies between different clusters. Next, an innovative algorithm named RWMM-Markov random field (RWMM-MRFt) for supervised classification is proposed. A new selection criterion for adaptive neighborhood systems is proposed in the algorithm to improve the classification performance. The new criterion makes effective use of PolSAR scattering information to select the most suitable neighborhood for each center pixel in PolSAR images. Three datasets, including one simulated image and two real PolSAR images, are utilized in the experiment. The maximum likelihood classification results demonstrate the flexibility of the proposed RWMM for modeling PolSAR data. The proposed selection criterion shows superior performance than the span-based selection criterion. Among the mixture model-based MRF classification algorithms, the proposed RWMM-MRFt algorithm has the highest classification accuracy, and the corresponding classification maps have better anti-noise performance. [ABSTRACT FROM AUTHOR]

Multiple-input and multiple-output synthetic aperture radar (MIMO SAR) is a very potential technique for high-resolution and wide-swath (HRWS) imaging due to the fact that it can provide more degrees of freedom. In this article, an innovative MIMO-HRWS SAR imaging system is introduced with segmented phase coding (SPC) waveforms. However, it is well-known that the echo separation issue is the most technical challenge for MIMO SAR. It has shown that the separation of orthogonal echoes from cross correlation interference can be achieved by scan-on-receive (SCORE). However, this method often requires large computing resources on board, especially for null-steering process. For this, we propose a two-stage spaceborne–ground echo separation scheme. This scheme is mainly divided into two steps: the first step is a real-time SCORE beamforming process on board to reduce the downlink data volume, and the second step is a bandpass–null-steering process to suppress the interfering echoes on the ground. Thus, this scheme allows for the low computing resources on board and sufficient suppression of the interference simultaneously. Following this scheme, the MIMO-HRWS SAR system enables its number of equivalent phase centers nearly double that of the azimuth multichannel SAR system, leading to higher resolution and wider swath imaging. Finally, detailed simulation experiments for the MIMO-HRWS SAR imaging system are performed to verify the practicability and feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

Dynamic deformation measurement is an important approach to monitor structure stability. Due to its rapid imaging capabilities, ground-based multi-input–multi-output (GB-MIMO) radar has shown great application potential in bridge structure monitoring. This article proposes a dynamic deformation estimation method based on radar image series. First, an improved clutter suppression method is used to overcome the estimation error in complex working status. Second, a two-step pixel extraction method is adopted to ensure both the quantity and quality of sample pixels. Finally, frequency- and time-domain environmental stimulating methods are jointly considered for stable mode shape estimation. This article systematically measured the dynamic deformations of bridge structures, including two suspension bridges and a cable-stayed bridge. The time-series deformation, deflection, vibration frequency, and amplitude on the bridge structure are obtained by image-domain measurement. For the first time, the mode shapes of bridges are obtained through GB-MIMO radar. The correctness of structure parameter measurement is verified with the finite element model (FEM). Experimental results prove that with the proposed method, stable results could be acquired against weak and complex stimulation conditions. [ABSTRACT FROM AUTHOR]

To achieve high-resolution and wide-swath (HRWS) imaging, a space-time waveform-encoding (STWE) spaceborne synthetic aperture radar (SAR) system is adopted. In rugged terrain, the beam-pointing mismatch problem will appear when the traditional digital beamforming (DBF) technique is used to separate the received echoes. This problem leads to decreasing the received echo's gain, deteriorating the quality of the image product and making the interpretation of SAR image difficult. To address this problem, an advanced echo separation scheme for STWE spaceborne SAR based on the DBF and blind source separation (BSS) is put forward in this paper. In the scheme, the echoes are transmitted within the adjacent pulse repetition intervals to simulate multiple beams, and the scattered echoes are received by the sixteen-channel antennas in elevation simultaneously. In post-processing, a detailed flow is adopted. In the method, the DBF is firstly performed on received echoes. Due to the error caused by terrain undulation, the degree of echo separation is not enough. Then, the BSS is performed on the multiple echoes obtained after the DBF processing. Finally, the highly separated echo signal can be obtained. In this scheme, there is no need to perform the direction of arrival (DOA) estimation before the DBF processing, which saves valuable computing resources. In addition, to verify the proposed scheme, point target and distributed target simulations based on the 16-channel data of an elevation X-band DBF-SAR system are carried out. The results of point targets indicate that the residual echo caused by rough terrain can be reduced by more than 14 dB using the proposed scheme. The proposed scheme can be directly implemented into existing SAR systems; thus, it does not increase the complexity of the system design. The scheme has the potential to be applied to future spaceborne SAR missions. [ABSTRACT FROM AUTHOR]

Due to the minimum antenna area constraints of synthetic aperture radar (SAR), high-resolution and wide-swath (HRWS) imaging is difficult to be achieved using classical modes, such as scan, spotlight, and so on. Range ambiguity is one of the main technical challenges limiting HRWS imaging in spaceborne SAR. Inspired by the cocktail party effect, an advanced scheme based on blind source separation (BSS) is put forward to suppress the range ambiguity of spaceborne SAR in this article. In the scheme, multiple subantennas are used to collect multiple echo datasets, which are given different patterns. In this way, the echo signal of the desired region and that of the ambiguous region are weighted using different coefficients. During postprocessing, a detailed flow with the BSS algorithm is proposed to separate the desired echoes from those datasets. To verify the scheme, point target and scene simulations based on GF-3 are carried out. The results indicate that the range ambiguity can be reduced by more than 15 dB using the proposed scheme, the processing flow is effective, and the scheme has a good performance without increasing the complexity of the system design under the current SAR system conditions. The scheme has the potential to be adopted in future spaceborne SAR missions. [ABSTRACT FROM AUTHOR]

Interference can degrade the detection performance of a radar system. To overcome the difficulty of target detection in unknown interference, in this paper we model the interference belonging to a subspace orthogonal to the signal subspace. We design three effective detectors for distributed target detection in unknown interference by adopting the criteria of the generalized likelihood ratio test (GLRT), the Rao test, and the Wald test. At the stage of performance evaluation, we illustrate the detection performance of the proposed detectors in the presence of completely unknown interference (not constrained to lie in the above subspace). Numerical examples indicate that the proposed GLRT and Wald test can provide better detection performance than the existing detectors. [ABSTRACT FROM AUTHOR]

One of the challenges of the low-frequency spaceborne synthetic aperture radar (SAR) is that propagation through the ionosphere will introduce nonnegligible errors in the final SAR product. In the low-frequency bistatic SAR (BiSAR) system, the ionosphere will degrade the imaging performance and cause nonnegligible phase errors in the single-pass SAR interferometry application, which results in undesired errors of digital elevation model (DEM). In this article, a method that embedded into the focusing procedure is proposed, which aims to estimate and remove ionospheric effects on L-band spaceborne BiSAR system. First, the impacts of ionospheric effects on the BiSAR system are demonstrated, including the deterioration of imaging performance and the geometric distortion. Then, a method is proposed to correct ionospheric effects. Afterward, the simulations, including point targets and distributed targets, are carried out to verify the effectiveness of the proposed method. The imaging results and the DEM reconstruction results show that the proposed method can effectively estimate and remove ionospheric effects on spaceborne BiSAR systems. [ABSTRACT FROM AUTHOR]

Multichannel SAR system operating in the sliding spotlight mode has the capacity of imaging with very high resolution as requested by future spaceborne synthetic aperture radar (SAR) mission; hence, it has been attracted more and more attention in the SAR community. In a multichannel sliding spotlight SAR system with $N$ channels, the overall Doppler bandwidth of the data acquired by each channel is greater than $N \cdot \text {PRF}$ ; thus, the preprocessing algorithms (channel mismatch calibration and signal reconstruction) are no more available. To address this issue, a full-aperture imaging method for azimuth multichannel sliding spotlight mode is proposed in this article. First, the raw data of each channel need to be preprocessed based on a deramping operation, which can obtain an unambiguous Doppler spectrum. Afterward, the algorithm proposed for single-channel sliding spotlight mode can be performed. Finally, to avoid possible back-folded SAR images, postprocessing after focusing is demanded in some cases. The imaging results of the data acquired by GaoFen-3 (GF-3) are given for the first time in this article, which proves the effectiveness of the proposed imaging method and demonstrates the capacity of high-resolution wide-swath imaging of the multichannel sliding spotlight mode. [ABSTRACT FROM AUTHOR]

The echo separation issue associated with different transmit antennas is the most technical challenge in realizing the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) system. In this article, a novel MIMO-SAR imaging scheme based on an advanced radar waveform, namely, segmented-phase-code (SPC) waveform, is proposed. Compared with the state-of-the-art short-term shift-orthogonal (STSO) waveform beamforming schemes, this scheme relieves the short-term shift-orthogonality condition of transmitted waveforms without losing the imaging performance, which extends the optional waveform space. In this scheme, the separation of the echoes from close arrival angles is ensured by a simple time-shift weighting processing. Furthermore, a range bandpass filter bank and the digital beamforming (DBF) technique are employed to ensure that the echoes from far arrival angles are separable. Finally, detailed simulation experiments are performed to verify the feasibility of the proposed scheme, and in-depth discussions of different waveforms and MIMO-SAR imaging schemes are presented. [ABSTRACT FROM AUTHOR]

In this letter, the authors investigate the problem of subspace‐based distributed target detection when signal mismatch arises. To solve the problem, a simple and effective detector is introduced, which is parameterised by a non‐negative scalar. By adjusting the scalar, the proposed detector can flexibly change its detection properties for mismatched signals. In particular, the proposed detector with a small scalar is robust to signal mismatch, while the detector with a large scalar is selective. Moreover, the proposed detector with an appropriate scalar can provide higher probability of detection than the existing detectors in the absence of signal mismatch. Both simulated and real data confirm the effectiveness of the proposed detector. [ABSTRACT FROM AUTHOR]

Interface modification is an effective strategy to improve the performance of perovskite solar cells (PSCs). In this work, edible materials like glycerol and choline chloride were used to modify the surface of hole transport layer (HTL) NiOx. CH3NH3PbI3 (MAPbI3) film fabricated on the modified NiOx has a smoother surface and more uniform grains. It enables an improvement in short-circuit current density (JSC) of PSC from 17.77 ± 0.18 to 20.35 ± 0.36 mA cm−2, leading to an enhancement of power conversion efficiency from 13.37 to 15.25%. The work mechanism of glycerol and choline chloride modification was discussed. Our work provides an efficient and environmentally friendly choice for interface modification. [ABSTRACT FROM AUTHOR]

Based on the permanent scatterer (PS) technique, deformation measurements were taken in ground-based synthetic aperture radar (GB-SAR) applications. To realize long-term and real-time deformation monitoring, a PS processing framework is proposed. Firstly, a group selection framework is introduced. A certain number of GB-SAR images are selected as a group and different PS sets are selected. Secondly, a fluctuation factor is defined to detect abnormal images. Some images with abnormal amplitude information should not be used for deformation analysis. Thirdly, an adaptive threshold determination method to select the PSs is proposed. The PS numbers in different PS sets can be highly stable. Lastly, a real-time processing framework is introduced which can be applied for on-site monitoring. The proposed processing framework was also used to monitor an open-pit mine for about 11 days. Experimental results validated the effectiveness and reliability of the framework for long-term and real-time GB-SAR monitoring. [ABSTRACT FROM AUTHOR]

With the development of high-resolution radar satellite for global comprehensive environmental monitoring, day-and-night and all-weather surveillance has become an active and growing research field. However, in all cases, these applications require radar to have a high-efficiency radar module (e.g., T/R module), and high system transmitting power. These requirements may put an important limitation on the performance of a radar satellite with a high-power configuration. In this paper, we report a novel waveform optimization framework. Through this framework, an advanced nonlinear frequency modulation (NLFM) waveform with lower sidelobes and a smaller main lobe, which can significantly relieve the restriction of very limited satellite power, is constructed. In addition, we apply it in a real synthetic aperture radar (SAR) system with a bandwidth of 100 MHz at 9.6-GHz carrier frequency and the whole process of the NLFM waveform for radar imaging is discussed in detail, including the system architecture and configuration, a system error compensation method, and a modified chirp scaling algorithm (CSA). The imaging results demonstrate the excellent performance of the advanced NLFM waveform. Moreover, we observe that the SAR system with the advanced waveform has a higher signal-to-noise ratio (SNR) of 1.29 dB compared with the conventional linear frequency modulation (LFM) waveform. The improvement of 1.29-dB SNR means that the real radar system can reduce transmitting power with a ratio of 25%. This effect is likely to be a potential feature of NLFM waveform, which can reduce the transmitting power requirement, especially for radar satellite. [ABSTRACT FROM AUTHOR]

When multiple ground‐based differential interferometric radar (GB‐DInRad) systems are utilised together to resolve three‐dimensional (3D) deformation, the resolving accuracy is related with the measurement geometry of these radar systems. This Letter focuses on how to determine an optimal geometry. Based on the resolving equation of the 3D deformation, the Geometric Dilution of Precision (GDOP) is defined. Then the minimum value of the GDOP is calculated and a detailed geometrical analysis is made to determine the geometrical conditions of the minimum GDOP. The results prove that the optimal geometry could be obtained when the unit measurement vectors of these radar systems construct a regular pyramid with a specific structure. A numerical simulation is utilised to validate the analysis conclusion. [ABSTRACT FROM AUTHOR]

In the processing of high-resolution wide-swath spaceborne synthetic aperture radar data, the slant range history is difficult to formulate with a high accuracy over a long data-acquisition interval, and the variation of the imaging parameters over the illuminated scene makes it necessary to implement 2-D space-variant processing. To deal with these issues, first, a slant range expression is derived based on a geometry model using a circular arc to approximate the curved trajectory in this paper, which is composed of a hyperbolic term, a cubic term, and a quartic term. Then, the imaging flow based on the slant range model is proposed: a cubic filtering in range is employed to normalize the range-variant secondary range compression; the nonuniform fast Fourier transform (NUFFT) is used to correct the additional range displacement introduced by the cubic filtering and the nonlinear range cell migration (RCM) caused by the range dependence of the velocity; necessary modifications are made on the matched filter for azimuth compression to accommodate the cubic filtering in range and to deal with the high-order terms of the slant range model. The simulation results show that the proposed slant range model has a relatively high accuracy; the range processing procedure that involves an NUFFT following a cubic filtering can apply to the case where the nonlinear chirp scaling algorithm is adopted, and it has the advantage of being capable of dealing with the nonlinear RCM; the azimuth processing procedure can provide satisfactory focusing qualities over a rather large azimuth extent. [ABSTRACT FROM AUTHOR]

This paper addresses some important aspects for the spaceborne/stationary bistatic synthetic aperture radar (SAR) (SS-BiSAR) imaging with the transmitter, TerraSAR-X, operated in staring spotlight (ST) mode. With the large integration time reaching 7.5 s and the azimuth steering span reaching \pm 2.2^0, several significant effects occur, including troposphere delay, precision phase and time synchronization, the curved orbit effect, azimuth spectrum aliasing problem, and efficient frequency domain focusing algorithm. To circumvent the main effects, corresponding solutions are proposed, including a precise synchronization strategy with troposphere delay correction based on the direct signal from the transmitter and a modified and integrative bistatic polar format algorithm (PFA). This paper covers the theoretical development, implementation, and analysis of the SS-BiSAR PFA based on 2-D fast Gaussian gridding nonuniform fast Fourier transform with wavefront curvature correction. Furthermore, the high-resolution ST-mode SS-BiSAR image processed by the proposed algorithm is acquired, and the differences of scattering behaviors between monostatic and bistatic SAR images are analyzed in detail. [ABSTRACT FROM AUTHOR]

Among many synthetic aperture radar (SAR) automatic target recognition (ATR) algorithms, convolutional neural network (CNN)-based algorithms are the commonly used methods. However, most previous SAR ATR studies assume that the precise location (and heading direction) of a target is (are) known and image is not suffering from translations, which are not always true in realistic applications. In this letter, a modern CNN model is trained by samples with no rotation and displacement, and is evaluated on the dataset with rotation and displacement. The results show that the classification accuracy is very low when the target’s displacement or rotation angle is different from the pre-assumed value in the training dataset. To overcome this problem, a displacement- and rotation-insensitive deep CNN is trained by augmented dataset. The proposed method is evaluated on moving and stationary target acquisition and recognition (MSTAR) dataset. It proves that our proposed method could achieve high accuracy in all three subsets which have different displacement and rotation settings. [ABSTRACT FROM AUTHOR]

Reconstructing the vegetation history of southwest China since the Last Glacial Maximum is crucial for understanding the evolution of the Indian summer monsoon. In this study, we present a high-resolution palynological investigation from a 5 m core from the Ganchi peatland (southwest margin of the Sichuan Basin, southwest China) in order to reconstruct regional vegetation and climate over the last 25 kyrs. The succession, from bottom to top, comprises lake, wetland, and peat deposits, and wetland/aquatic pollen types are found to be a sensitive indicator of palaeoenvironmental change. Deciduous broad leaf forests dominated by Betula were present between 25-18 cal kyrs BP, suggesting a cold and dry climate during the Last Glacial Maximum. After 18 cal kyrs BP, temperature and summer insolation increased gradually, marking the Lateglacial transition. Thermophilous and hygrophilous species expanded between 11-8 cal kyrs BP, indicating a progressively warmer and wetter climate. From 8-4 cal kyrs BP, evergreen forests developed, while Tsuga reached its maxim abundance, implying a warm and humid climate coincided with the mid-Holocene climatic optimum. Results indicate that residual ice sheets may have impeded the northward shift of the Intertropical Convergence Zone, resulting in peak Holocene warmth lagging behind peak summer insolation forcing. Vegetation change was primarily controlled by climate, with no obvious evidence of anthropogenic disturbance until the last 1 cal kyrs BP. Our study shows that vegetation and climate in the southwest margin of the Sichuan Basin were controlled by summer insolation and ice sheet dynamics, and also influenced by sea surface temperature in the Indian Ocean. • High-resolution pollen records revealed vegetation and climate history since 25 cal kyrs BP • Variations in proxies were highly correlated with depositional processes • Paleovegetation records suggest that the Holocene climate optimum occurred during 8-4 cal kyrs BP • The most conspicuous landscape transformation caused by human impact in the Sichuan Province began at ∼1 cal kyrs BP [ABSTRACT FROM AUTHOR]

Symmetrical windows are widely used as smoothing weighting for signals undergoing discrete Fourier transform (DFT) processing. Briefly speaking, the resolution of spectral analysis is governed by mainlobe width (MW) of a window, and the variance estimates are decreased by the sidelobes leakage with the window. It is generally believed that there has an optimal trade-off between MW and sidelobes ripple levels. The rectangular window (RW) has the smallest MW, but with the highest peak-sidelobe ratio (PSLR). The lower sidelobes of nonrectangular windows, however, have been achieved at the cost of the MW broadening. This paper poses a challenging question of whether the PSLR of a window can be reduced while, preserving the same MW as RW. To demystify this question, we present a global optimization procedure, firefly algorithm (FA), borrowed from nature-inspired methodology, to compute the proposed optimization formulation and perform an extensive number of experimental tests. The experimental results show that the PSLRs of optimized windows can be reduced by 0.98–4.04 dB, while preserving the same MW as RW. Furthermore, adjusting the parameters of optimization algorithm, we find that the lower PSLR of optimized window generally leads to higher envelope level of the sidelobes ripple. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) frequently suffers from radio frequency interference (RFI) due to the simultaneous presence of numerous wireless communication signals. Recently, the narrowband RFI is found to possess the low-rank property benefiting from stable frequency occupancy, hence the reconsideration of RFI suppression as a joint sparse and low-rank optimization problem. The existing methods either use the non-sparse useful signal itself as the sparse regularizer, or employ the nuclear norm to approximate the rank function, which punishes all singular values with the same penalty via singular value thresholding (SVT), resulting in the improper punishment problem. Hence, both are consequentially subject to performance limitation. In this paper, a novel dictionary-based nonconvex low-rank minimization (DNLRM) optimization framework is proposed for RFI suppression, which concurrently considers the improvements for both the sparse regularizer and the low-rank regularizer. For the former, an over-completed dictionary is constructed, for which the sparse coefficient acts as the sparse regularizer. For the latter, the rank function is more accurately approximated by innovatively introducing the nonconvex function, for which the supergradient is synchronously used to generate the weighted penalty, thus solving the improper punishment problem. The derivation of the closed-form solution and the convergence analysis are described in detail. Additionally, the adaptive selection scheme for the model parameter is uniquely proposed for further ensuring the practicality of the DNLRM framework. The superiority of the proposed method is demonstrated via not only the RFI-free real SAR data combined with the measured RFI, but the RFI-contaminated real SAR data. [ABSTRACT FROM AUTHOR]

LuTan-1 (LT-1) is an innovative spaceborne radar Earth observation mission including two satellites equipped with synthetic aperture radar (SAR) which will be launched in 2022. Active phased array antennas that can be divided into two physical channels are equipped on each satellite. The signal can be transmitted through the full antenna without broadening and recorded by each channel. Therefore, two methods can be used to preprocess the dual-channel receiving signals, referred to as dual-channel echo reconstruction and dual-channel echo synthesis. The former is inherited from the traditional high-resolution wide-swath mode and the latter is a method that takes coherent superposition as the reference. This paper researches the impacts of the two methods in system performance and imaging quality. Principles and theoretical models are firstly given. Furthermore, the system performance under the "L1A_SM_S" working mode of the LT-1 is simulated to compare the differences between the two methods, which mainly focuses on azimuth ambiguity-to-signal ratio, noise equivalent sigma zero, and the performance of block adaptive quantization. Afterwards, the test data acquired by the ground validation system of the LT-1 are used for the hardware-in-the-loop simulation to demonstrate the imaging quality between the two methods. Finally, a quantitative comparison is given. [ABSTRACT FROM AUTHOR]

This paper presents a double-channel hybrid bistatic synthetic aperture radar (SAR) system. It can be implemented with the available illuminator (e.g., spaceborne and airborne SAR systems) to acquire the 2-D and 3-D microwave images for remote-sensing applications. This system can be used as a test system for the validation of complex bistatic acquisitions, novel synchronization algorithms, and advanced imaging techniques. In this paper, we will demonstrate the time and phase synchronization strategies, fast time-domain imaging algorithm, 2-D bistatic SAR, and 3-D bistatic stereo radargrammetry in SAR images. Based on the proposed bistatic system, the acquired bistatic image has a much better sensitivity than its monostatic counterpart, which will facilitate the detection and recognition of targets based on their characteristic and bistatic scattering behaviors. Finally, the experiment results highlight the differences between monotatic and bistatic SAR images. [ABSTRACT FROM AUTHOR]

Burst imaging schemes such as ScanSAR and Terrain Observation by Progressive Scans (TOPS) are often adopted to obtain wide swath coverage by synthetic aperture radar (SAR) systems with electronic beam steering in elevation. Long burst trains with zero padding in the inter-burst intervals can be focused by standard stripmap processors for the phase preserving product. However, this approach is less efficient due to the larger azimuth data extension. We discuss an efficient imaging approach for burst mode SAR. The key point of the proposed procedure is a postfiltering step after standard stripmap processors, which employs an azimuth convolution between the focused SAR data and the selected chirp signal. The postfiltering step is generalized by a two-step focusing technique formerly proposed for spotlight/sliding spotlight SAR. This approach extends the focusing capacity of standard stripmap processors to process burst mode raw data. Moreover, it is highly efficient, as it requires a very limited azimuth data extension. [ABSTRACT FROM AUTHOR]

Video Synthetic Aperture Radar (ViSAR) operating in spotlight mode has received widespread attention in recent years because of its ability to form a sequence of SAR images for a region of interest (ROI). However, due to the heavy computational burden of data processing, the application of ViSAR is limited in practice. Although back projection (BP) can avoid unnecessary repetitive processing of overlapping parts between consecutive video frames, it is still time-consuming for high-resolution video-SAR data processing. In this article, in order to achieve the same or a similar effect to BP and reduce the computational burden as much as possible, a novel time-frequency sub-aperture technology (TFST) is proposed. Firstly, based on azimuth resampling and full aperture azimuth scaling, a time domain sub-aperture (TDS) processing algorithm is proposed to process ViSAR data with large coherent integration angles to ensure the continuity of ViSAR monitoring. Furthermore, through frequency domain sub-aperture (FDS) processing, multiple high-resolution video frames can be generated efficiently without sub-aperture reconstruction. In addition, TFST is based on the range migration algorithm (RMA), which can take into account the accuracy while ensuring efficiency. The results of simulation and X-band airborne SAR experimental data verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Hybrid and ± π / 4 quadrature-polarimetric (quad-pol) synthetic aperture radar (SAR) systems operating from space can obtain all polarimetric components simultaneously but suffer from severe azimuth ambiguities in the cross-polarized (cross-pol) measurement channels. In this paper, the hybrid and ± π / 4 quad-pol SAR systems with multiple receive channels in azimuth are widely investigated to suppress the azimuth ambiguities of the cross-pol components. We first provide a more thorough analysis of the multichannel hybrid and ± π / 4 quad-pol SAR systems. Then, the multichannel signal processing is briefly discussed for the reconstruction of the quad-pol SAR signal from the aliased signals, in which the conventional reconstruction algorithm causes extremely severe azimuth ambiguities. To this end, an improved reconstruction method is proposed based on a joint optimization, which allows for the minimization of ambiguities from the desired polarization and the simultaneous power of undesired polarized signal. This method can largely suppress azimuth ambiguities compared with the conventional reconstruction algorithm. Finally, to verify the advantages and effectiveness of the proposed approach, the azimuth ambiguity-to-signal ratio (AASR), the range ambiguity-to-signal ratio (RASR) and signal-to-noise ratio (SNR) of all polarizations, as well as a set of imaging simulation results, are given to describe the effects of reconstruction on the multichannel hybrid and ± π / 4 quad-pol SAR systems. [ABSTRACT FROM AUTHOR]

Phase analysis based on high-quality pixel (HQP) is crucial to ensure the measurement accuracy of ground-based SAR (GB-SAR). The amplitude dispersion (ADI) criterion has been widely applied to identify pixels with high amplitude stability, i.e., permanent scatterers (PSs), which typically are point-wise scatterers such as stones or man-made structures. However, the PS number in natural scenes is few and limits the GB-SAR applications. This paper proposes an improved method to take HQP selection applied for natural scenes in GB-SAR interferometry. In order to increase the spatial density of HQP for phase measurement, three types of HQPs including PS, quasi-permanent scatter (QPS), and distributed scatter (DS), are selected with different criteria. The ADI method is firstly utilized to take PS selection. To select those pixels with high phase stability but moderate amplitude stability, the temporal phase coherence (TPC) is defined. Those pixels with moderate ADI values and high TPC are selected as QPSs. Then the feasibility of the DS technique is explored. To validate the feasibility of the proposed method, 2370 GB-SAR images of a natural slope are processed. Experimental results prove that the HQP number could be significantly increased while slightly sacrificing phase quality. [ABSTRACT FROM AUTHOR]

In recent years, jamming strategies for Synthetic Aperture Radar (SAR) pertaining to target detection and identification, such as the creation of false targets, electromagnetic (EM) deception, and signal spoofing, have been increasingly emphasized. Distinct from traditional SAR jamming approaches, the introduction of an innovative artificial material cloak in SAR target jamming presents augmented capabilities. These methods demonstrate a proficient redirection of incident EM waves in specific or arbitrary directions, effectively masking the vital information linked to critical targets. This study introduces a broadband SAR target jamming system employing an information metasurface that incorporates intelligent information processing algorithms in conjunction with a space-time-coding digital metasurface, endowing it with the capacity to adeptly modulate incident EM waves. This integration facilitates a versatile approach to jamming, enabling the deployment of multi-mode protective measures against critical targets. The conducted simulation and experiment results validate the system's ability to adjustably produce EM deception and generate multiple false targets independently of the SAR system. The outcomes of this research significantly advance the practicality of SAR protection strategies, pushing the boundaries toward more dynamic, broadband, and controllable scenarios, thereby substantially improving the concealment of critical targets in highly sensitive conflict areas. [ABSTRACT FROM AUTHOR]

Ground-based interferometric synthetic aperture radar (GB-InSAR) technology can be applied to generate a digital elevation model (DEM) with high spatial resolution and high accuracy. Phase unwrapping is a critical procedure, and unwrapping errors cannot be effectively avoided in the interferometric measurements of terrains with discontinuous heights. In this paper, an improved multi-baseline phase unwrapping (MB PU) method for GB-InSAR is proposed. This method combines the advantages of the cluster-analysis-based MB PU algorithm and the minimum cost flow (MCF) method. A cluster-analysis-based MB PU algorithm (CA-based MB PU) is firstly utilized to unwrap the clustered pixels with high phase quality. Under the topological constraints of a triangulation network, the connectivity graph of any non-clustered pixel is established with its adjacent unwrapped cluster pixels. Then, the absolute phase of these non-clustered pixels can be identified using the MCF method. Additionally, a spatial-distribution-based denoising algorithm is utilized to denoise the data in order to further improve the accuracy of the phase unwrapping. The DEM generated by one GB-InSAR is compared with that generated by light detection and ranging (LiDAR). Both simulated and experimental datasets are utilized to verify the effectiveness and robustness of this improved method. [ABSTRACT FROM AUTHOR]

Up to now, multiple innovative spaceborne synthetic aperture radar (SAR) imaging schemes have been demonstrated for high resolution or/and wide swath coverage. Different imaging modes usually require different imaging processors to focus their raw data. However, presented is a novel full-aperture imaging processor for different imaging modes. According to echo properties of different SAR imaging modes, a preprocessing step and a post-processing step are added to a modified accurate range migration algorithm processor. In addition to the advantage of being suitable for different imaging modes, this imaging processor is very efficient, since it avoids the large azimuth data extension to resolve the aliasing problem. Imaging results on simulated raw date validate the proposed imaging processor. [ABSTRACT FROM AUTHOR]

Hybrid quadrature polarimetric (hybrid quad-pol) synthetic aperture radar (SAR) is proposed as a potential candidate for the full-polarimetric SAR mode. It allows balanced range ambiguity performance and simplified system structure. System based on hybrid-pol SAR mode can also implement the conventional quad-pol mode and the compact-pol mode via few adjustments. However, the azimuth ambiguity performance in cross-pol channels is proved deteriorated in hybrid quad-pol mode due to the lopsided energy distribution of ambiguities. As are generally called "ghost" targets, azimuth ambiguities usually influence the recognition of the targets in SAR imaging. This letter describes how to remove the false targets that arise from azimuth ambiguities by means of waveform diversity and dual-focus post-processing (DFPP) technique. The proposed method exploits the feature of azimuth ambiguity and yields improved image quality in cross-pol channels with strong co-pol azimuth ambiguities removed in hybrid quad-pol SAR at a low system cost. Furthermore, it offers remarkable benefits for target detecting and recognition with strong false targets removed. [ABSTRACT FROM AUTHOR]

An atmospheric effect is a main error source that affects interferometric measurements. When a ground-based multiple-input multiple-output (GB-MIMO) radar, i.e., a specific type of GB-synthetic aperture radar (GB-SAR), was utilized to continuously monitor an open-pit mine, the interferometric phases of some interferograms were complexly space-variant due to time-variant weather conditions. The conventional method of atmospheric phase (AP) compensation was no longer applicable. This paper proposes an improved compensation method of a time-space variant AP applied to time-series GB-SAR images. The permanent scatterers (PSs) were classified into three types based on their different spatial properties: The noise-dominant PS (NPS), the deformation-dominant PS (DPS), and the atmospheric effect-dominant PS (APS). The NPSs were firstly rejected based on the differential phase analysis of neighboring PSs. The DPSs were then rejected based on the cluster partition and selection. With the APSs, the space-variant AP was estimated with a spatial interpolation. To validate the feasibility of the proposed method, short-term and long-term experimental datasets were processed. Comparisons with a conventional method proved that the proposed method can well reduce AP errors and avoid the misunderstanding of motional areas. [ABSTRACT FROM AUTHOR]

High-resolution and high-squint spaceborne spotlight synthetic aperture radar (SAR) has significant potential for extensive application in remote sensing, but its swath width effectiveness is constrained by a critical factor: severe range cell migration (RCM). To address this, pulse repetition interval (PRI) variation offers a practical scheme for raw data reception. However, the current designs for continuously varying PRI (CV-PRI) exhibit high complexity in engineering. In response to the issue, this paper proposes a novel strategy of stepwise varying PRI (SV-PRI), which demonstrates higher reconstruction accuracy compared with CV-PRI. Furthermore, confronting the azimuth non-uniform sampling characteristics induced by the PRI variation, this paper introduces a complete uniform reconstruction processing based on the azimuth partitioning methodology, which effectively alleviates the inherent contradiction between resolution and swath width. The processing flow, utilizing the temporal point remapping (TPR) concept, ensures the uniformity and coherence of dataset partitioning and reassembly in the context of the interpolation on non-uniform grids. Finally, according to the simulation results, the point target data, processed through the processing flow proposed in this study, have demonstrated effective focusing results. [ABSTRACT FROM AUTHOR]

The azimuth phase coding (APC) technique is known for its very low implementation complexity and its effectiveness for point and distributed ambiguities in conventional synthetic aperture radar (SAR) systems. In recent years, as an extension, the APC technique has been briefly discussed for multichannel SAR systems. However, the properties of the APC technique are no longer guaranteed in the multichannel SAR systems based on the digital beamforming (DBF) on-receive, and only a slight APC gain in the suppression of the range ambiguity can be obtained. In this article, we first provide a more thorough analysis for an APC-multichannel SAR system with respect to a uniform pulse-repetition frequency (PRF). Then, the APC/multichannel SAR system with nonuniform spatial sampling is briefly discussed, and an improved reconstruction approach based on a quadratically constrained optimization model is proposed to increase greatly the APC gain with respect to existing multichannel reconstruction algorithms. This proposed approach allows the minimization of the range ambiguity with a given azimuth-ambiguity constraint. In particular, for some specific PRFs, the proposed method permits a cancellation of the odd-order range ambiguity. Finally, simulation experiments are performed to verify the advantages and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This article establishes a multiobjective optimization model to suppress the azimuth ambiguity power and noise simultaneously in signal reconstruction for a multichannel synthetic aperture radar (SAR) system. This multiobjective optimization model extends the theory of multichannel signal processing for reconstructing the SAR signal from the aliased signals. Linear scalarization and a quadratically constrained method for the multiobjective optimization model are applied to obtain $l_{1}$ norm optimization, $l_{2}$ norm optimization, and quadratically constrained optimization, respectively, in signal reconstruction. Azimuth ghosts can intuitively reflect the effects of azimuth ambiguity on SAR images. The $l_{1}$ norm optimization solution leads to a minimum upper bound of azimuth ghosts. A lowest azimuth ambiguity-to-signal ratio (AASR) can be derived by $l_{2}$ norm optimization. By relaxing the constraint of total ambiguity power suppression, one can obtain a minimum noise level in the case of quadratically constrained optimization. The reconstruction performances of the multiobjective optimization model in terms of AASR, signal-to-noise ratio (SNR), and signal-to-ambiguity-plus-noise ratio (SANR) are investigated with respect to the pulse repetition frequency (PRF) and compared with other methods for a multichannel SAR system. [ABSTRACT FROM AUTHOR]

LuTan-1 [(LT-1), i.e., TwinSAR-L] mission is an innovative spaceborne bistatic synthetic-aperture radar (BiSAR) mission focusing mainly on differential interferometry, which will be launched in 2020. This article introduces some important aspects of the LT-1 mission for the first time, including the formation configuration, imaging mode, application scenarios, and the efficient baselines between the master satellite and the slave satellite. To realize the high accurate topography and deformation measurements, a wide swath BiSAR focusing algorithm with phase reserving ability should be developed. This article proposes a modified bistatic range-Doppler algorithm based on 2-D principle of stationary phase spectrum, which reduces the phase error introduced by the root term expansion and has an excellent focus performance and a good phase reserving ability. Finally, the spaceborne bistatic simulation experiments using orbital parameters and imaging mode of the LT-1 mission, including point targets and scene targets, are utilized to illustrate the validity and accuracy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Multi-channel synthetic aperture radar (SAR) in azimuth can overcome the minimum-antenna-area constraint of the conventional SAR in high-resolution and wide-swath (HRWS) imaging. However, the SAR system suffers from amplitude and phase mismatch among channels and nonideal antenna pattern, which will result in azimuth ambiguity and ghost targets in the final image. Therefore, taking the nonbandlimited signal and channel errors into account, a practical azimuth ambiguity-to-signal ratio (AASR) model of multi-channel SAR system is established. Meanwhile, the baseband Doppler centroid (DC) frequency related to channel errors also has an influence on image quality. Then, an effective method is proposed to calculate the baseband DC frequency according to the jumping points of the channel phase errors estimate. Subsequently, considering the effect of azimuth antenna pattern (AAP), a corresponding relationship between the ideal steering vectors and the signal subspace from the decomposing covariance matrix is established. After that, based on the uniqueness of the signal subspace and the correct corresponding relationship, an accurate method is proposed to estimate the channel phase errors by minimizing the minimum mean square error (MMSE) of the signal subspace. Finally, an accurate multi-channel SAR imaging diagram is shown to effectively mitigate the azimuth ambiguous energy caused by channel errors. Simulation and real data experiments, including four channel airborne SAR data with a bandwidth of 210 MHz and the Chinese Gaofen-3 dual receiving channel (DRC) spaceborne SAR data, validate the effectiveness of the proposed calibration method, particularly in low signal-to-noise ratio (SNR). [ABSTRACT FROM AUTHOR]

Abstract Due to highly compressible soil and a large amount of human activity, the costal deltas are more prone to ground subsidence. Many major costal deltas in the world are facing subsidence and are consequently more susceptible to flooding, salinization and seawater infusion or even permanent submergence. Therefore, ground subsidence has been a significant problem in coastal delta areas worldwide. The Yellow River Delta (YRD) is the second largest river delta in China. On the one hand, the YRD contains a large area of wetlands rich in biodiversity, and on the other hand, industrial activities and urbanization are extensive due to abundant underground resources such as oil, gas and brine. Excessive land use has caused different degrees of ground subsidence in this area. However, a detailed and comprehensive description of the ground subsidence pattern over the YRD has not been provided. Also, widespread non-urban area in Yellow River Delta region, such as wetlands, farmland and coastal tidal areas, hinders the application of persistent scatterer interferometry method (PSI) for comprehensive subsidence measurement over the whole area. In this paper, we developed a multitemporal InSAR method to map ground subsidence over the YRD area by exploiting both persistent scatterers (PS) and distributed scatterers (DS). This method is characterized by employing the coherence-weighted phase-linking algorithm for fast and reliable optimal phase reconstruction of each DS point and a two-tier network of PS and DS for the robust analysis of land subsidence. To extract the detailed and comprehensive ground subsidence over the whole YRD, we apply our method to 30 ENVISAT ASAR images (2007–2010) and 49 Sentinel-1A (S-1A) images (2015–2018) and obtain measurements of the ground subsidence during these two periods. Forty-one Sentinel-1B (S-1B) images (2016–2018) are also exploited for cross-sensor consistency validation with the result derived from the S-1A dataset. Our method shows a great advantage over the PSI method, providing much higher measuring point (MP) density in mapping land subsidence over the YRD, including 15-fold higher density for the ASAR dataset, 5.1-fold for the S-1A dataset and 5.3-fold for the S-1B dataset, which enables a very detailed description of local ground deformation patterns. Cross-track consistency in the derived measurements from the S-1A and S-1B datasets shows a standard deviation of 9.6 mm/yr for the vertical subsidence rate. A quantitative validation of the derived subsidence results compared with leveling measurements suggests an accuracy of 4.58 mm/yr for the standard deviation term. By comparing the ground deformation over the YRD during the periods of 2015–2018 and 2007–2010, we find that the subsidence in this region shows an overall intensification trend and many new and severe subsidence depressions appear along the coastline, with a maximum vertical subsidence rate of 432 mm/yr. Subsequently, the overextraction of underground brine for salt production is identified as the primary factor causing the ground subsidence near the YRD coastal area. [ABSTRACT FROM AUTHOR]

In this work, a facile method to prepare graphene oxide films with controllable interlayer distances similar to that of wet-spinning is proposed. Wet graphene oxide gel films were dipped into coagulation bath for crosslinking. Calcium chloride, two ionic liquids, 1-butyl-3-methylimidazole L lactate and 1-aminopropyl-3-methylimidazolium chloride and 1,8-octanediamine were chosen as the coagulants. The obtained graphene oxide films were characterized by Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, X-ray diffraction and tensile tests. The adsorption of Rhodamine B solutions tests proved that GO films with different interlayer distances exhibited varied sieving performance. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) images require a high-resolution system for accurate interpretations. This high range resolution can be achieved by stepped frequency chirp signals. To reconstruct a wideband waveform from each subband signal, amplitude/phase/delay imbalance between the channels should be precisely compensated. In this paper, the system configuration is first presented. Further, a calibration strategy was proposed based on three calibration loops: the reference calibration, transmitting calibration, and receiving calibration loops for coarsely compensating the channel imbalance. Then, two different methods based on the cost functions were proposed to remove the residual channel imbalance. The proposed methods were validated using stepped frequency SAR data acquired by an X-band airborne SAR system with a total bandwidth of 3.6 GHz, yielding (unweighted) a 3-dB range resolution of 4 cm. [ABSTRACT FROM PUBLISHER]

The ambiguity suppression is a technical challenge for the present generation of spaceborne synthetic aperture radar (SAR) systems since this kind of suppression does not take the high spatial resolution and wide coverage into account simultaneously. The transmitting scheme based on the waveform diversity technique is a promising candidate for the conventional (one transmit, one receive channel) SAR systems and has been widely discussed, because it has almost no extra system costs and the ambiguity suppression performance is not closely related to pulse repetition frequency (PRF). However, the accurate method to evaluate the ratio of the intensities of the ambiguities to that of the signal is still a gap. To this end, starting from the precise signal model formulated in this paper, the ambiguity evaluation for spaceborne SAR with waveform diversity has been analyzed in detail. Particularly, the modified azimuth ambiguity-to-signal ratio (AASR) and range ambiguity-to-signal ratio (RASR) formulas are given for the single polarization SARs and quadrature-polarimetric (quad-pol) SARs, which contributes a lot, for the system designer, to precisely evaluating the ambiguity performance. Finally, detailed simulation experiments exploiting the system parameters of the LuTan (LT-1) system are carried out to corroborate the theoretical developments. [ABSTRACT FROM AUTHOR]

Due to the light weight and small size, synthetic aperture radar (SAR) sensors with light-small aircraft are very sensitive to atmospheric turbulences, which cause serious trajectory deviations. Limited by the cost or payloads, light-small aircraft sometimes cannot carry high-accuracy inertial navigation systems (INS)/global positioning systems (GPS). For the very high resolution (VHR) case, residual range cell migration (RCM) often exceeds several range resolution cells during the course of the synthetic aperture, thus degrading the image quality substantially. In this paper, a robust scheme for the correction of residual RCM is presented. The scheme consists of three principle steps. First, the range-compressed data in the signal domain are divided into subapertures in azimuth. For each subaperture, a sliding window is used to select the subblock data with the highest signal-to-clutter ratio. Second, for each subaperture, residual RCM is estimated by using the selected subblock data based on a nonparametric entropy minimization technique. Third, the estimated residual RCM of all subapertures are filtered and coherently combined to perform the correction for the full-aperture data. Processing the results of VHR SAR raw data shows that the proposed scheme is effective for highly precise imaging with light-small aircraft equipped with only low-accuracy INS/GPS. [ABSTRACT FROM PUBLISHER]

This paper proposes a synchronization algorithm for bistatic synthetic aperture radar (BiSAR) imaging in a spaceborne/stationary configuration. In real bistatic systems, synchronization errors are generally introduced into the received data. Additionally, the lack of precise imaging parameters, such as the position of the transmitter and the accurate sampling time, could affect the imaging quality greatly. Fortunately, the image could be well focused by the proposed algorithm in the case of lack of the accurate position of a transmitter and the sampling time. First, a preprocessing step is employed to remove synchronization errors through matching an echo signal with a direct signal. Then, a modified chirp scaling factor containing an error phase term is constructed, and the accurate position of the transmitter and the sampling time can be acquired by the phase extraction of the direct signal and the searching method based on contrast optimization. After that, the corresponding imaging process can be implemented. Finally, the proposed algorithm is validated by the simulation and experimental results, where TerraSAR-X is used as the illuminator. [ABSTRACT FROM PUBLISHER]

Multiple-input multiple-output synthetic aperture radar (MIMO-SAR) is of great potential for future high-resolution and wide swath imaging. However, its development is limited as the condition of orthogonality among the multiple waveforms received simultaneously is hard to satisfy. In this paper, a class of linear frequency modulation-based MIMO waveforms is introduced to settle this problem and correspondingly an effective processing scheme is proposed based on digital beam forming in elevation. In this scheme, for separating the mixed signals, null steering technique is employed to extract one waveform from the others. The main advantages of the proposed scheme include transmitting simultaneously, good inter-orthogonality between different waveforms with identical frequency range, separating them with mutual interference cancellation and good imaging quality. The main procedure of this scheme is derived and described in detail in the paper. Furthermore, an example MIMO-SAR system is provided for numerical simulation and the simulation results are obtained to validate the proposed scheme. [ABSTRACT FROM PUBLISHER]

The technique of multiple apertures in azimuth enables a wide swath synthetic aperture radar (SAR) with a high azimuth resolution. In a traditional multi-channel SAR system, if the pulse repetition frequency (PRF) is not an optimum value it will result in a non-uniform sampling. To overcome this limitation, a reconstruction algorithm has been designed to recover the non-uniform signal. In this letter, we claim that while the system PRF is around some specific values, singular points exist in the reconstruction algorithm and therefore the reconstruction cannot get correct result. To avoid the influence of these singular points, a novel method is presented in this letter which can also improve the system signal-to-noise ratio. Furthermore, simulation results are presented to evaluate the performance of this method. At the end of this letter, the real multi-channel SAR data are processed to demonstrate the effectiveness of the proposed method experimentally. [ABSTRACT FROM PUBLISHER]

A promising candidate for ultra–wide-swath spaceborne synthetic aperture radar (SAR) imaging with a fine resolution is the multiple-elevation-beam (MEB) SAR. Conventional MEB SAR suffers from deterioration of noise-equivalent sigma zero (NESZ) and range ambiguity–to–signal ratio (RASR) performances in the far end of the imaging swath and disturbances between different subbeam elevations. Another inherent problem of previously proposed MEB SAR systems is the blind range effect, which blocks continuous mapping. In this paper, we introduce a potential modified MEB SAR system based on space-time-frequency waveform encoding on transmit and on digital beamforming (DBF) on receive that provides a much improved performance of NESZ and RASR, a lower requirement for the transmit peak power, and a more flexible signal energy distribution. Furthermore, to overcome the blind range problem, a periodic sweep of pulse repetition interval (PRI) design strategy is employed. In this paper we are developing the idea of sweep-PRI mode into a complete detailed processing scheme. The explicit signal model, the instructive system design guideline, and the corresponding signal processing scheme for this operational mode are described in detail. A recurrent nonuniform reconstruction algorithm is adopted first to cope with the problems of nonuniform sampling and periodic gaps in the azimuth preprocessing. Additionally, an in-depth analysis of system performance for the presented MEB SAR system is carried out. Finally, an example system with a 400-km-wide swath and 3-m resolution is designed based on the proposed strategies. The simulation results demonstrate that the presented SAR system shows satisfactory performance. [ABSTRACT FROM AUTHOR]