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In scenarios with constrained physical aperture sizes, aiming to enhance the resolution and accuracy of Direction of Arrival (DOA) estimation, this paper proposes a novel approach that integrates a moving synthetic virtual array with Sparse Bayesian Learning (SBL) for DOA estimation. Initially, a virtual array is constructed based on the motion characteristics of the target. Subsequently, the SBL method is employed to estimate the DOA of the target. Simulation experiments validate the effectiveness of this approach, demonstrating comparable DOA estimation performance to synthetic aperture methods with larger aperture sizes, even in situations with limited aperture expansion. Furthermore, under constant virtual aperture expansion, this method surpasses non‐SBL methods regarding DOA resolution. We explore the construction of a virtual array through the relative displacement induced by target motion. It further investigates the performance improvement of Direction of Arrival (DOA) estimation resolution using sparse Bayesian learning within the context of a virtual array. [ABSTRACT FROM AUTHOR]

The authors present exploitation of Multiple Views in Single‐Path (MVSP) Synthetic Aperture Sonar (SAS). The authors demonstrate the interest of MVSP SAS for underwater Mine Counter‐Measures (MCM) with unmanned vehicles, to comply with requirements for performances of detection and classification and time constraints. The authors here lay the emphasis on exploitation in reduction of false alarms of classification by alleviating the ambiguity between mines and natural bottom objects. Finally, the authors show that MVSP SAS is offering a pre‐identification tool with high impact on MCM process duration. [ABSTRACT FROM AUTHOR]

Coherent change detection (CCD) takes advantage of the interferometric processing of synthetic aperture sonar (SAS) images and enables the detection of small scale changes to the scene between image pairs. This paper builds upon interferometric phase statistics developed for synthetic aperture radar and presents a method to differentiate between possible sources of decorrelation. A single‐pass pair of SAS images is categorized into four zones based on acoustic amplitude and coherence properties. Results suggest that regions of low coherence caused by a scene change can be differentiated from regions of low coherence due to other sources of decorrelation. Phase statistics could provide a technique to reduce the false alarm rate in CCD. Further studies are required to validate the approach for repeat‐pass SAS imagery and consider the effects of temporal decorrelation and misregistration errors on the phase distributions. [ABSTRACT FROM AUTHOR]

Synthetic aperture sonar image reconstruction relies on the coherence of overlapping phase centres to provide accurate micronavigation for a sensed scene. It is shown that phase centres lose coherence for near‐range scattering from large synthetic aperture sonar arrays due to the fundamentally bistatic nature of these sensors. This effect is modelled using the van Cittert‐Zernike theorem and a point‐based sonar scattering model. Reduction of the window length used in the delay estimation process can partially mitigate the loss of coherence at the expense of increased variance in the resulting delay estimates. [ABSTRACT FROM AUTHOR]

Synthetic aperture sonar (SAS) interferometry is a technique for very high resolution imaging and mapping of the seabed. In SAS interferometry, the seabed depth estimation performance is a function of the system, the geometry, the signal-to-noise ratio (SNR) and the filter size, equivalent to the achieved horizontal resolution. A strong driver for SNR is the imaging range and grazing angle. The variation of these parameters over a typical SAS swath gives rise to a large variation in the depth estimation performance. To mitigate the negative effect of this, we suggest to use an adaptive phase estimation filter size, such that the standard deviation of the depth estimate is proportional to the horizontal resolution. We demonstrate the suggested adaptive filter size method on long range data collected using a HUGIN Superior autonomous underwater vehicle (AUV) equipped with a HISAS 1032 Dual receiver interferometric SAS. Our technique increases the valid area coverage when the SNR is marginal, at the expense of reduced horizontal resolution [ABSTRACT FROM AUTHOR]

Nowadays, polarimetric interferometric synthetic aperture radar (PolInSAR) has attracted increasing attention for the simultaneous acquisition of scattering and terrain information. The scattering mechanism vectors corresponding to the optimal coherences have shown great effect in land cover classification and forest mapping. To extract scattering mechanism vectors, different optimization algorithms are proposed but always accompanied with spatial discontinuities. This letter proposes a method to optimize scattering mechanism vectors based on nonlocal estimations. A pixel‐by‐pixel optimization model is established by calculating patch‐based nonlocal similarity, which effectively reduces the uncertainty of scattering mechanism vector estimation while maintaining high resolution. The phase recovery experiment is conducted on simulated data and the root mean square errors (RMSEs) of three algorithms are compared. The proposed method performs better with a RMSE of 0.22 in the whole image, against 0.25 and 1.27 for other algorithms. The recovery results in the target region (RMSE 0.11 against 0.21 and 0.99) and linear edge region (RMSE 0.26 against 0.49 and 1.52) also indicate strong ability in detail preservation. Then the observed ESAR data is utilized for further assessment. It demonstrates that the proposed method has a significant improvement to reduce singularities and distinguish artificial buildings. [ABSTRACT FROM AUTHOR]

Due to the aircraft targets' uncooperative character, acquiring the complete scattering characteristics of enemy aircraft is challenging. An effective reconstruction method of target scattering centres based on characteristics analysis of inverse synthetic aperture radar (ISAR) images is proposed in this letter. First, a positive definite manifold characterizing ISAR images of different attitudes is constructed. Then, Kullback–Leibler divergence is used as a measure of the variability between ISAR images. Finally, an ISAR image interpolation method based on the characteristics analysis of ISAR images is proposed to obtain the scattering characteristics with more attitudes. Furthermore, simulation results confirm that the proposed method is effective. [ABSTRACT FROM AUTHOR]

This letter proposes an improved synthetic aperture imaging algorithm to enhance the imaging performance in the Azimuth Missing Data (AMD) case. The proposed algorithm designs an effective phase compensation function based on the Range Cell Migration Correction (RCMC) echo and first reconstructs the complete RCMC echo from the AMD echo. The accuracy of echo reconstruction is improved, leading to a better imaging result. Numerical simulations and a real measured experiment verify the effectiveness of the proposed algorithm. Furthermore, since the range positions of targets can be located after RCMC processing, only non‐zero RCMC signals are reconstructed. Thus, the computational complexity superiority of the proposed algorithm is obvious, especially when the targets are sufficiently sparse in the range direction. [ABSTRACT FROM AUTHOR]

The use of Multiple Input Multiple Output (MIMO) orthogonally coded waveforms sharing the same bandwidth, has the potential to increase area coverage rate in synthetic aperture sonar (SAS). The disadvantage is cross‐talk between the waveforms. In this letter, the benefits and limitations are listed for a best case use of MIMO in SAS. A scheme is developed to emulate a MIMO system with realistic cross‐talk that can be tested on non‐MIMO SAS data. The impact of cross‐talk is evaluated on simulated data and real data collected by a HISAS interfereometric SAS carried by a HUGIN autonomous underwater vehicle. The finding is that the negative impact of cross‐talk on SAS is significant. [ABSTRACT FROM AUTHOR]

The motion of targets is well known to result in their defocusing and displacement in SAR imagery, but detection of motion and re‐focusing of targets under generic conditions remains an ongoing interest. One class of methods involves forming images of sub‐apertures in which motion defocusing will be reduced. In this paper, dynamic tomographic image formation methods utilising an optical flow constraint is used to form a video of SAR sub‐aperture images. These retain fine resolution of the full aperture, focusing along‐track motion. [ABSTRACT FROM AUTHOR]

Radar forward‐looking imaging is gaining significance in various applications like battlefield reconnaissance, target surveillance, and precision guidance. Although synthetic aperture radar techniques provide high azimuth resolution but faced limitations in forward‐looking area due to the poor Doppler resolution and the "left‐right" ambiguity problem. Recently, generative adversarial networks have been extensively used for image motion blur removal. This letter proposes an end‐to‐end forward‐looking image enhancing network using generative adversarial network to produce high‐resolution images, improving the efficiency, and quality of imaging. Compared to conventional methods such as the deconvolution‐based methods, this algorithm eliminates the need for design and iterative processes of the observation matrix. Simulated and real radar data validate that this approach offers robust recovery and better performance. [ABSTRACT FROM AUTHOR]

In this Letter, the authors present a novel imaging algorithm for multireceiver synthetic aperture sonar (SAS). The Loffeld's bistatic formula (LBF) including quasi‐monostatic (QM) and multireceiver deformation (MD) phases is first reformulated into range‐variant and range‐invariant phases. After compensating the range‐invariant phase, the subsequent steps are the extended Stolt mapping for each bistatic SAS. Based on simulations, the presented method can also provide high‐resolution result which is similar to that of back projection (BP) algorithm. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) renderings in 3D provide additional target information when compared to 2D by separating out features overlaid in height. However, the required 2D SAR aperture, when Nyquist sampled, necessitates large scanning times that would be impractical for most realistic collections. This research has developed a novel volumetric approach to sparse aperture 3D SAR imaging, which is applicable to bistatic SAR near‐field geometries, a generalization of far‐field cases. This approach is first demonstrated in simulation and then applied to a measured scene containing a model vehicle target, producing sub‐Nyquist sampled 3D SAR renderings. [ABSTRACT FROM AUTHOR]

A novel optimal time selection method for synthetic aperture radar (SAR) data processing via the expectation‐maximization (EM) algorithm is proposed, which can reduce the computational complexity and improve the image quality simultaneously. First, the Doppler frequency feature after the SAR processing is analyzed from the point of probability. Then, the Doppler frequency is modelled as the Gaussian mixture model (GMM), and the issue of optimal time selection can be implemented by the parameter estimation of GMM. The results of simulated and real measured data are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Sparse signal processing has been widely used in synthetic aperture radar imaging and feature enhancement of images in the recent decade. Sparse regularization ℓ1 can reduce the imaging noise level and suppress sidelobes. However, the suppression of sidelobes by sparse regularization often pays the price of losing information of weak targets. Therefore, the sparse regularization method combining spatially variant apodization is proposed in this paper, which can suppress noise, sidelobes and retain detail information. The performance of the proposed method is verified using simulated and real data. [ABSTRACT FROM AUTHOR]

Tomographic synthetic aperture radar (TomoSAR) plays a critical role in the 3D reconstruction of complex urban targets with the capability of 3D imaging. Nevertheless, multipath scattering interference is common in 3D point clouds, seriously affecting the structure of the 3D model. In this letter, the multipath scattering phenomenon of buildings is analysed and the building 3D reconstruction of TomoSAR using multiple bounce scattering model is proposed. The superiority of the proposed method is demonstrated for experiments on array TomoSAR data. It is found that the proposed method not only achieves interference suppression but also improves integrity and accuracy taking advantage of multiple scattering information. [ABSTRACT FROM AUTHOR]

Due to the azimuth shift and defocus of the moving targets in the synthetic aperture radar image domain, a new synthetic aperture radar ground moving target indication method is proposed in this letter based on the changes of moving targets' polarization characteristics before and after clutter suppression. This method can effectively suppress the false alarms caused by the man‐made objects compared with the displaced phase centre array method in the complex scenes. Finally, the effectiveness of the proposed method is verified by the real multi‐channel quadrature‐polarimetric synthetic aperture radar data. [ABSTRACT FROM AUTHOR]

Photonics-based radar enables a large operation bandwidth that is particularly favourable for high-resolution synthetic aperture imaging. However, how to implement fast and high-accuracy imaging with photonics-based broadband radar is still an open question. In this Letter, the performance of photonics-based inverse synthetic aperture radar imaging with frequency-domain and time-domain algorithms are experimentally investigated and compared. The results show that, frequency-domain range–Doppler algorithm has fast imaging capability, but the image suffers from defocusing and distortions. Although migration compensation techniques can be applied to improve the imaging accuracy, the imaging speed is significantly reduced. On the other hand, using time-domain back-projection (BP) algorithm can achieve well-focused images, and the imaging speed can be enhanced with fast BP methods. Therefore, the time-domain imaging method is found to be the best choice for fast and high-accuracy synthetic aperture imaging with photonics-based broadband radars. [ABSTRACT FROM AUTHOR]

The future L-band geosynchronous synthetic aperture radar (GEO SAR) system will be inevitably affected by ionospheric scintillation. Due to the lack of the real system, it is necessary to achieve the scintillation- affected GEO SAR raw data for the research of influential mechanism and correction strategies. A method for the generation of scintillation-affected GEO SAR raw data is proposed that utilises the reverse backprojection (ReBP) to efficiently and accurately modulate the scintillation transfer function on GEO SAR signals. A simulation experiment for a real SAR scene from one of the ALOS-PALSAR observation is operated in case of the current inclined L-band GEO SAR system configuration. The simulation takes less time by using the ReBP, compared with the existent method, and shows the speckle-like phase error similar to the injected scintillation phase error, which validates the nice efficiency and accuracy of the proposed methodology. [ABSTRACT FROM AUTHOR]

The simple linear iterative clustering (SLIC) is the most popular superpixel segmentation method for its simplicity and effectiveness. In this Letter, we propose an edge attention-based geodesic distance, which can be applied to the SLIC framework for polarimetric synthetic aperture radar image superpixel segmentation. Image edges are especially considered to generate superpixels with better boundary adherence property, while the computing burden does not increase. Specifically, the authors first detect image edges, then fuse the edge map and polarimetric dissimilarity, and finally define the geodesic distance based on the fused results. Experiments performed on real scene images demonstrate the superiority of the proposed distance in both qualitative and quantitative ways. [ABSTRACT FROM AUTHOR]

Artefact phenomena resulting from synthetic aperture radar (SAR) image formation can pose a challenge for image interpretation. One such artefact is produced when a vibrating target is imaged. Suppression of these artefacts has previously been described, however little has been developed in the area of modelling the location and shape of such artefacts. The authors present an experimentally validated model that provides accurate location and shape of vibrating target paired echoes in both SAR near-field and SAR far-field imagery. [ABSTRACT FROM AUTHOR]

A new scheme for pixel-based polarimetric synthetic aperture radar (PolSAR) classification of the urban area was proposed. First, the characteristic of urban backscattering was analysed and it was found that the backscattering of buildings is very sensitive to the orientation of buildings. Second, by utilising Euler rotation to the polarimetric coherency matrix, a sequence of data with different rotation angles was simulated. Then a polarimetric statistical feature vector would be extracted from the simulated data. At last, the feature vector together with four components decomposition result would be put into a multiple layer perceptron neural network to get the classification result. The proposed scheme can improve the accuracy of urban area classification in a PolSAR image and be verified by using AIRSAR image data of San Francisco. [ABSTRACT FROM AUTHOR]

A new simulation and processing methodology based on open source tools to produce high fidelity synthetic aperture radar (SAR) simulations of ground vehicles of varying types, as well as analysis of an applied automatic target recognition (ATR) technique is presented in this Letter. This work is based around the RaySAR open-source model and the outputs have been configured for both monostatic and bistatic geometries. Input CAD models of various military and civilian vehicles are used to produce the SAR imagery. This output imagery was then used to train a tiny you only look once convolutional neural network (CNN) classifier. The classification success of the CNN applied was showed to produce significantly accurate results and the whole pipeline of processing enabled rapid evaluation of potential ATR methods against targets of choice. [ABSTRACT FROM AUTHOR]

Conventional time-series interferometric synthetic aperture radar techniques solve elevation correction and linear deformation rate by non-linear optimisation in 2D space, spatial baseline, and temporal baseline. This letter presents a new method called the time difference baseline set (TDBS). By utilising the discrete characteristic of temporal baseline, the conventional 2D optimisation can be transformed into two 1D optimisations to estimate elevation correction and linear deformation rate, respectively. The authors' TDBS-based two-steps method reduces the time complexity from O(n²) to O(n) without compromising on accuracy. The comparative experiments and analysis carried out on real data confirmed the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Synthetic aperture ladar (SAL) is analogous to the synthetic aperture radar (SAR) but works at wavelength 104-5 times shorter. SAL has the potential for much finer resolution than SAR. Due to the shorter wavelength used for SAL, the platform vibration would induce high-frequency and large-amplitude phase errors during the data collection. Direct using of the conventional imaging algorithms to SAL data suffers from performance degradation. To address this problem, an effective imaging method based on subaperture phase gradient auto-focus (PGA) and normalised cross correlation (NCC) is proposed for airborne SAL data. First, the length of subaperture is determined according to the criterion that the coherent processing interval (CPI) is shorter than half of the vibration period. Then the phase history data (PHD) is formatted into a few subapertures and the PGA is employed to estimate the phase errors in each subaperture. After the compensation of the phase errors, each subaperture image is focused with the conventional imaging algorithm. Finally, a recombination of the subapertures is performed based on the NCC. The proposed method is verified by processing the real SAL data collected by strip-mode with the demonstrator system built at Institute of Electronics, Chinese Academy of Science. [ABSTRACT FROM AUTHOR]