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The imaging of high-speed high-squint synthetic aperture radar (HSHS-SAR), which is mounted on maneuvering platforms with curved trajectory, is a challenging task due to the existence of 3-D acceleration and the azimuth spatial variability of range migration and Doppler parameters. Although existing imaging algorithms based on linear range walk correction (LRWC) and nonlinear chirp scaling (NCS) can reduce the range–azimuth coupling of the frequency spectrum (FS) and the spatial variability of the Doppler parameter to some extent, they become invalid as the squint angle, speed, and resolution increase. Additionally, most of them ignore the effect of acceleration phase calibration (APC) on NCS, which should not be neglected as resolution increases. For these issues, a modified frequency nonlinear chirp scaling (MFNCS) algorithm is proposed in this paper. The proposed MFNCS algorithm mainly includes the following aspects. First, a more accurate approximation of range model (MAARM) is established to improve the accuracy of the instantaneous slant range history. Second, a preprocessing of the proposed algorithm based on the first range compression, LRWC, and a spatial-invariant APC (SIVAPC) is implemented to eliminate most of the effects of high-squint angle and 3-D acceleration on the FS. Third, a spatial-variant APC (SVAPC) is performed to remove azimuth spatial variability introduced by 3-D acceleration, and the range focusing is accomplished by the bulk range cell migration correction (BRCMC) and extended secondary range compression (ESRC). Fourth, the azimuth-dependent characteristics evaluation based on LRWC, SIVAPC, and SVAPC is completed to derive the MFNCS algorithm with fifth-order chirp scaling function for azimuth compression. Consequently, the final image is focused on the range time and azimuth frequency domain. The experimental simulation results verify the effectiveness of the proposed algorithm. With a curved trajectory, HSHS-SAR imaging is carried out at a 50° geometric squint angle and 500 m × 500 m imaging width. The integrated sidelobe ratio and peak sidelobe ratio of the point targets at the scenario edges approach the theoretical values, and the range-azimuth resolution is 1.5 m × 3.0 m. [ABSTRACT FROM AUTHOR]

Single-phase center multiple azimuth beam (SPC MAB) mode is an effective method for high-resolution wide-swath (HRWS) SAR imaging. The traditional azimuth spectrum reconstruction method for SPC MAB mode is based on the combination scheme from which fake targets along the azimuth direction arise because the inter-beam interference is not considered. When the real antenna mode is inconsistent with the ideal one, the disadvantages of the combination scheme become more serious. In this paper, based on the basic theory of the low-pass, band-limited, multiple-channel under-sampling and reconstruction, a novel digital beam-forming method is proposed for the SPC MAB imaging mode with ideal antenna mode first. The method analyzes the system functions of the sub-beams, based on which digital beam-forming filters are designed for all the sub-beams. The designed filters can reconstruct the correct wide-bandwidth azimuth spectrum and suppress the inter-beam interference simultaneously. Furthermore, the proposed method is extended to SPC MAB mode with the non-ideal antenna mode. The simulation experiments prove the validities of the proposed method both for azimuth spectral reconstruction and the inter-beams interfering suppressing, no matter that the SPC MAB's antenna mode is ideal or non-ideal. [ABSTRACT FROM AUTHOR]

High-resolution wide-swath (HRWS) imaging is the research focus of the modern spaceborne synthetic-aperture radar (SAR) imaging field, with significant relevance and vast application potential. Staggered SAR, as an innovative imaging system, mitigates blind areas across the entire swath by periodically altering the radar pulse repetition interval (PRI), thereby extending the swath width to multiples of that achievable by conventional systems. However, the staggered mode introduces inherent challenges, such as nonuniform azimuth sampling and echo data loss, leading to azimuth ambiguities and substantially impacting image quality. This paper proposes a sparse SAR imaging method for the low-oversampled staggered mode via compound regularization. The proposed method not only effectively suppresses azimuth ambiguities arising from nonuniform sampling without necessitating the restoration of missing echo data, but also incorporates total variation (TV) regularization into the sparse reconstruction model. This enhances the accurate reconstruction of distributed targets within the scene. The efficacy of the proposed method is substantiated through simulations and real data experiments from spaceborne missions. [ABSTRACT FROM AUTHOR]

This study presents the first azimuth cutoff analysis in Synthetic Aperture Radar (SAR) altimetry, aiming to assess its applicability in characterizing sea-state dynamics. In SAR imaging, the azimuth cutoff serves as a proxy for the shortest waves, in terms of wavelength, that can be detected by the satellite under certain wind and wave conditions. The magnitude of this parameter is closely related to the wave orbital velocity variance, a key parameter for characterizing wind-wave systems. We exploit wave modulations exhibited in the tail of fully-focused SAR waveforms and extract the azimuth cutoff from the radar signal through the analysis of its along-track autocorrelation function. We showcase the capability of Sentinel-6A in deriving these two parameters based on analyses in the spatial and wavenumber domains, accompanied by a discussion of the limitations. We use Level-1A high-resolution Sentinel-6A data from one repeat cycle (10 days) globally to verify our findings against wave modeled data. In the spatial domain analysis, the estimation of azimuth cutoff involves fitting a Gaussian function to the along-track autocorrelation function. Results reveal pronounced dependencies on wind speed and significant wave height, factors primarily determining the magnitude of the velocity variance. In extreme sea states, the parameters are underestimated by the altimeter, while in relatively calm sea states and in the presence of swells, a substantial overestimation trend is observed. We introduce an alternative approach to extract the azimuth cutoff by identifying the fall-off wavenumber in the wavenumber domain. Results indicate effective mitigation of swell-induced errors, with some additional sensitivity to extreme sea states compared to the spatial domain approach. [ABSTRACT FROM AUTHOR]

A 3D surface deformation field for an earthquake can aid in understanding fault behaviors and earthquake mechanisms. However, SAR-based 3D surface deformation estimates are often limited by insufficient observations and hampered by various error sources. In this study, we demonstrate the derivation of a 3D coseismic displacement field from different InSAR processing algorithms. The azimuth displacements from Multiple Aperture Interferometry (MAI) and Pixel Offset Tracking (POT) were integrated to ensure reliable displacements at low coherent areas. The 3D displacement field was inverted pixel-by-pixel by Line-of-Sight (LOS) displacement and integrated azimuth displacement. The results showed that MAI and POT could compensate for the weaknesses of each algorithm. Also, pixels with less than three sets of observations showed higher noise levels. Such noisy pixels were removed by a denoising criterion proposed herein. For the vertical direction, the proportion of pixels inverted with two sets of azimuth and one set of LOS displacements was 26.1%. After denoising, the proportion dropped to 2.4% due to the insufficiency of LOS displacements. This shows that the viewing angle influences the overall performance of 3D surface displacement inversion. Implementing various displacement vectors should reduce such limitations. [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]

Polar format algorithm (PFA) is a widely used high-resolution SAR imaging algorithm that can be implemented in advanced widefield staring synthetic aperture radar (WFS-SAR). However, existing algorithms have limited analysis in wavefront curvature error (WCE) and are challenging to apply to WFS-SAR with high-resolution and large-swath scenes. This paper proposes an extended polar format algorithm for joint envelope and phase error correction in WFS-SAR imaging with maneuvering trajectory. The impact of the WCE and residual acceleration error (RAE) are analyzed in detail by deriving the specific wavenumber domain signal based on the mapping relationship between the geometry space and wavenumber space. Subsequently, this paper improves the traditional WCE compensation function and introduces a new range cell migration (RCM) recalibration function for joint envelope and phase error correction. The 2D precisely focused SAR image is acquired based on the spatially variant inverse filtering in the final. Simulation experiments validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Ladar (SAL) is a sensor that combines laser detection technology with synthetic aperture technology to achieve ultra-high-resolution imaging. Due to its extremely short wavelength, SAL is more sensitive to motion errors. The micrometer-level motion will affect the target's azimuth focus. This article proposes an SAL motion compensation method based on Symmetric Triangular Linear Frequency Modulation Continuous Wave (STLFMCW) segmented interference, utilizing the characteristics of a triangular wave, to solve the problem of target azimuth defocusing. This article first establishes an STLFMCW echo signal model based on the SAL system under the influence of motion errors. Secondly, the radial velocity gradient along the azimuth direction is extracted using the triangular-wave-positive and -negative frequency modulation signals segmented interference method. Then, for the initial phase wrapping problem, the frequency spectral cross-correlation method is used to accurately estimate the initial radial velocity error. The radial velocity gradient is integrated along the azimuth to obtain the platform motion trajectory. Finally, the compensation functions are constructed to complete the echo Range Cell Migration (RCM) correction and residual phase compensation, resulting in a focused SAL image. This article verifies the practical effect of this method in eliminating motion errors using only one-period STLFMCW signal through simulation and real experiments. The quantitative results show that compared with the traditional method, the proposed method reduces the azimuth Peak Sidelobe Ratio (PSLR) by 8dB and the Integrated Sidelobe Ratio (ISLR) by 9 dB. This method has significant improvements and is of great significance for high-resolution FMCW SAL imaging. [ABSTRACT FROM AUTHOR]

In this study, we obtained the intensity and orbital angular momentum (OAM) spectral distribution of the scattering fields of vortex electromagnetic beams illuminating electrically large targets composed of different materials. We used the angular spectral decomposition method to decompose a vortex beam into plane waves in the spectral domain at different elevations and azimuths. We combined this method with the physical optics algorithm to calculate the scattering field distribution. The OAM spectra of the scattering field along different observation radii were analyzed using the spiral spectrum expansion method. The numerical results indicate that for beams with different parameters (such as polarization, topological charge, half-cone angle, and frequency) and targets with different characteristics (such as composition), the scattering field intensity distribution and OAM spectral characteristics varied considerably. When the beam parameters change, the results of scattering from different materials show similar changing trends. Compared with beams scattered by uncoated metal and dielectric targets, the scattering field of the coating target can better maintain the shape and OAM mode of beams from the incident field. The scattering characteristics of metal targets were the most sensitive to beam-parameter changes. The relationship between the beam parameters, target parameters, the scattering field intensity, and the OAM spectra of the scattering field was constructed, confirming that the spiral spectrum of the scattering field carries the target information. These findings can be used in remote sensing engineering to supplement existing radar imaging, laying the foundation for further identification of beam or target parameters. [ABSTRACT FROM AUTHOR]

The increasing amount of space debris poses a significant threat to operational satellites and space-based services. This article updates the community on the current status of the development of ATLAS, a tracking radar that is part of the EUSST network and aims to detect space objects in low Earth orbits. This article focuses on the latest activities performed: calibration of the pointing system and initial observations of space objects. The calibration procedure consisted of cross-scanning the Solar disk and yielded great results, obtaining an offset of 5.3° in azimuth and 0.10° in elevation. The first observation campaign resulted in 33 range detections of the International Space Station (ISS) with a probability of false alarm of  10 − 9 . The observations were then used to readjust the radar equation to assess the real-world performance of the system. [ABSTRACT FROM AUTHOR]

The frequency–azimuth (FRAZ) spectrum is a critical characteristic in passive target detection and tracking, as it encapsulates information regarding the signal's frequency and azimuth. However, due to the inherent limitations in the sonar array's physical aperture and the analysis time of the system, the signal often suffers from undersampling in both spatial and temporal dimensions. This undersampling leads to energy leakage across the azimuth and frequency domains, adversely affecting the resolution of the FRAZ spectrum. Such a reduction in resolution hampers multitarget resolution and feature extraction. To address these challenges, this study introduces a deconvolution-based FRAZ spectrum estimation method tailored for uniform linear arrays. The proposed method initiates by decoupling the azimuth and frequency in the FRAZ spectrum, forming a two-dimensional point scattering function that possesses shift-invariance. Subsequent to this, the power spectrum and the two-dimensional point scattering function undergo deconvolution using the Richardson–Lucy (R–L) iterative algorithm. The final stage involves calculating the signal azimuths and frequencies based on the deconvolution results from the preceding step. Comparative analyses involving simulations and sea test results reveal that the proposed method achieves a narrower main lobe width and diminished background noise in contrast to traditional FRAZ spectrum estimation techniques. This improvement is instrumental in minimizing the target's energy leakage in both the azimuth and frequency domains. [ABSTRACT FROM AUTHOR]

Amid the conflict between the current huge data volumes and the requirement for large-compression-ratio compression in space-borne multichannel SAR, this paper proposes a data compression method that uses the adaptive bit allocation BAQ method in the Doppler domain of space-borne multichannel SAR. Specifically, 3MBAQ, which denotes multichannel, multipulse, multiweight block-adaptive quantization, performs signal reconstruction through a Krieger filter to obtain the Doppler spectrum under azimuthal multichannel and multipulse conditions and then achieves nonuniform bit allocation by using the multiple weight contributions between subband spectra. Furthermore, large-compression-ratio compression can be realized in homogeneous scenarios by using the adaptive bit allocation BAQ method together with the improved bit error control (BEC) algorithm. In this paper, the effectiveness of the 3MBAQ method is verified on GF3 measured data. Moreover, compared to the SQNR and NMSE of the BAQ, A-BAQ, A-BAQ-BEC, MCBAQ-ASQ, and MCBAQ-BEC methods under the same conditions, it is shown that there is an optimal 1.3434 dB improvement in SQNR and a 0.0241 improvement in NMSE using the 3MBAQ algorithm, and the complexity of the algorithm for 3MBAQ is O (N 2 l o g (N)) , which is within acceptable limits, clearly proving the superiority of the 3MBAQ method. [ABSTRACT FROM AUTHOR]

Airborne circular synthetic aperture radar (CSAR) can realize high-resolution imaging of the scene over 360 degrees azimuth angle variation. Aiming at the problem of focusing of buildings for the airborne CSAR, this paper first analyzes the phase errors of CSAR buildings focusing in detail, and the analytic relationship between the scatterer height and azimuth focusing quality is deduced. Then, a focusing method of CSAR buildings based on the back projection algorithm is proposed. This method adopts the processing strategy of multi-layers imaging, and it is able to improve azimuth focusing quality of the buildings which have large height dimension. The proposed method is especially suitable for the high-resolution imaging and monitoring of the urban site with high-rise buildings in the airborne CSAR scenario. The correctness of the theoretical analysis and the validity of the proposed method are verified by using both simulation results and Ku-band airborne CSAR real data processing results. [ABSTRACT FROM AUTHOR]

In this study, repeat-pass synthetic aperture radar interferometry (repeat-pass THz InSAR) is first extended to the terahertz band, and it has tremendous potential in the application of high-resolution three-dimensional (3D) imaging due to its shorter wavelength, larger bandwidth, and greater sensitivity to elevation variation. The super-resolution and high sensitivity of THz InSAR pose greater demands on the baseline calibration for high-precision digital elevation model (DEM) generation. To meet the elevation accuracy requirement of THz InSAR, we propose a baseline calibration method relying on the estimation of the azimuth fringe frequency (EAFF) of the interferometric phase. Initially, a model for non-parallel sampling path errors within the squint SAR repeat-pass interferometry was established, and then, we conducted the theoretical analysis of the phase errors induced by the non-parallel errors. Following this, using a reference DEM, the relationship between the fringe frequency of the error phase and the bias in the repeat-path positioning was established. This allowed the estimation of the position errors to be transformed into the frequency spectrum estimation based on the FFT, which would mitigate the impact of unknown SAR sampling positions. Ultimately, we investigated the accuracy of the proposed EAFF calibration method, and the simulation showed that it can achieve the theoretical accuracy when the correlation coefficient exceeds 0.3. Furthermore, we configured the repeat-pass THz InSAR system with the 0.3 THz stepped-frequency radar. Compared to the conventional calibration based on ground control points (GCPs), the 3D reconstruction of both a knife and a terrain model, calibrated using the proposed EAFF algorithm, demonstrated that the elevation accuracy can achieve millimeter-level precision across the entire image swath. The above results also proved the great potential of THz InSAR in high-precision 3D imaging and remote sensing. [ABSTRACT FROM AUTHOR]

Due to the complex range migration characteristics of large squint angle synthetic aperture radar (SAR), it is difficult for traditional SAR deceptive jamming algorithms to balance focusing ability and computational efficiency. There is an urgent demand for proposing a deceptive jamming algorithm against large squint angle SAR in the field of SAR jamming. This article proposes a deceptive jamming algorithm against SAR with large squint angles based on non-linear chirp scaling and low azimuth sampling reconstruction (NLCSR). The NLCSR algorithm uses a high-order approximation of a high-precision model to accurately construct the jammer's frequency response (JFR) function. In line with the notion of low azimuth sampling processing of the transformation domain, the construction of the space-variant azimuth modulation phase item is completed using the non-linear chirp scaling method. Compared with the traditional deceptive jamming algorithms against the large squint angle SAR, the NLCSR algorithm only needs Fourier transform and complex multiplication while ensuring the focusing ability, which is easier to implement on an efficient parallel digital signal processor based on fast Fourier transform (FFT). Simulation results prove the superior property of the NLCSR algorithm in focusing ability and computational efficiency. Compared to the existing large squint angle SAR deceptive jamming algorithm, the focusing ability of the NLCSR algorithm is almost the same, and the calculation efficiency is improved by at least 52.1%. [ABSTRACT FROM AUTHOR]

The measurement of bidirectional reflectivity for ground-based objects is a highly intricate task, with significant limitations in the capabilities of both ground-based and satellite-based observations from multiple viewpoints. In recent years, unmanned aerial vehicles (UAVs) have emerged as a novel remote sensing method, offering convenience and cost-effectiveness while enabling multi-view observations. This study devised a polygonal flight path along the hemisphere to achieve bidirectional reflectance distribution function (BRDF) measurements for large zenith angles and all azimuth angles. By employing photogrammetry's principle of aerial triangulation, accurate observation angles were restored, and the geometric structure of "sun-object-view" was constructed. Furthermore, three BRDF models (M_Walthall, RPV, RTLSR) were compared and evaluated at the UAV scale in terms of fitting quality, shape structure, and reflectance errors to assess their inversion performance. The results demonstrated that the RPV model exhibited superior inversion performance followed, by M_Walthall; however, RTLST performed comparatively poorly. Notably, the M_Walthall model excelled in capturing smooth terrain object characteristics while RPV proved applicable to various types of rough terrain objects with multi-scale applicability for both UAVs and satellites. These methods and findings are crucial for an extensive exploration into the bidirectional reflectivity properties of ground-based objects, and provide an essential technical procedure for studying various ground-based objects' in-plane reflection properties. [ABSTRACT FROM AUTHOR]

Deploying Passive Multistatic Radar (PMR) on mobile platforms provides covert and cost-effective monitoring over a large area, offering certain advantages in countermeasure. However, mobile PMR faces significant challenges, such as Doppler distortion and phase deviations. A multi-parameter space target detection method is proposed for mobile PMR to achieve target detection in three-dimensional environments. By estimating the Doppler Frequency Rate (DFR), applying bistatic range phase compensation, and implementing azimuth time integration, frame division, and data fusion, the detection accuracy and the Signal-to-Noise Ratio (SNR) are improved. Simulation results indicate that the proposed method significantly enhances the SNR and produces accurate detection results, demonstrating its efficacy. [ABSTRACT FROM AUTHOR]

Maritime moving target imaging using synthetic aperture radar (SAR) demands high resolution and wide swath (HRWS). Using the variable pulse repetition interval (PRI), staggered SAR can achieve seamless HRWS imaging. The reconstruction should be performed since the variable PRI causes echo pulse loss and nonuniformly sampled signals in azimuth, both of which result in spectrum aliasing. The existing reconstruction methods are designed for stationary scenes and have achieved impressive results. However, for moving targets, these methods inevitably introduce reconstruction errors. The target motion coupled with non-uniform sampling aggravates the spectral aliasing and degrades the reconstruction performance. This phenomenon becomes more severe, particularly in scenes involving multiple moving targets, since the distinct motion parameter has its unique effect on spectrum aliasing, resulting in the overlapping of various aliasing effects. Consequently, it becomes difficult to reconstruct and separate the echoes of the multiple moving targets with high precision in staggered mode. To this end, motivated by deep learning, this paper proposes a novel Transformer-based algorithm to image multiple moving targets in a staggered SAR system. The reconstruction and the separation of the multiple moving targets are achieved through a proposed network named MosReFormer (Multiple moving target separation and reconstruction Transformer). Adopting a gated single-head Transformer network with convolution-augmented joint self-attention, the proposed MosReFormer network can mitigate the reconstruction errors and separate the signals of multiple moving targets simultaneously. Simulations and experiments on raw data show that the reconstructed and separated results are close to ideal imaging results which are sampled uniformly in azimuth with constant PRI, verifying the feasibility and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

An efficient spectrum reconstruction algorithm based on the Tikhonov regularization for terahertz (THz) synthetic aperture radar (SAR) azimuth non-uniform sampling is proposed in this article. The high bandwidth, high azimuth resolution, and high frame rate characteristics of THz SAR contribute to its wide application prospects in both military and civilian remote sensing fields. However, the higher azimuth sampling rate also leads to the more severe non-uniform sampling issues of THz SAR. Traditional methods based on the hardware adjustment of pulse repetition frequency (PRF) and simple interpolation for azimuth resampling struggle to meet the higher imaging quality requirements. The back projection algorithm (BPA) can accurately focus non-uniformly sampled data but requires significant computational resources. The algorithm proposed in this paper, which can reconstruct the wavenumber spectrum of SAR azimuth non-uniformly sampled signals, transforms the spectrum reconstruction problem into a linear equation system and solves it using Tikhonov regularization, thereby exhibiting higher computational efficiency compared to BPA. Furthermore, the proposed algorithm is derived from precise theoretical formulations and controls the solution error by utilizing a regularization parameter, leading to a superior imaging quality compared to the azimuth resampling algorithm. In this paper, an accurate spectrum reconstruction formula of non-uniform sampling signals with a finite length is derived, the influence of noise error on the solution is analyzed, and the THz SAR azimuth non-uniform sampling signals are processed from the wavenumber domain. Finally, simulation and experimental results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The F-SCAN principle is a better alternative to the scan-on-receive technique (SCORE) based on digital beamforming (DBF), which can avoid low gain caused by a conventional broad beam in the case of a wide swath. In F-SCAN SAR, a pencil beam scans the entire target area from far to near, providing high energy independent of the position and ensuring a low range ambiguity-to-signal ratio (RASR). Moreover, echo compression can be achieved via appropriate system parameter configuration, significantly shortening the receive window and reducing the amount of data. A wider range swath can, therefore, be achieved. However, for this novel F-SCAN SAR working mode, signal modeling and imaging processing are key issues that needed to be addressed. In this paper, the far-field synthetic antenna pattern of the space–time coding array (STCA) is first derived and analyzed, based on which the signal modeling of the F-SCAN SAR is carried out. Then, according to the signal model and echo characteristics, a novel imaging processing method based on the hybrid correlation algorithm is presented for the F-SCAN SAR. First, the dechirp operation is performed to compensate for the quadratic phase of the range time. The range compressed result is obtained after a range Fourier transform, where different range targets are successfully separated and range aliasing is avoided. Then, the modified azimuth reference function is correlated with the echo at each range cell to complete range cell migration correction (RCMC) and azimuth compensation. The received signal parameters and the Doppler parameters of each range cell are derived to update the azimuth reference function. Finally, accurate focused results are obtained in the range-frequency, azimuth-time domain. The simulation results indicate that the signal model based on the STCA can satisfy the requirements of the F-SCAN principle, and the proposed imaging algorithm can complete the precise focusing processing of the F-SCAN SAR echo. [ABSTRACT FROM AUTHOR]

The high-squint airborne Synthetic Aperture Radar (SAR) has the ability to detect the target area flexibly, and the detection swath is significantly increased compared with the side-looking SAR system. Therefore, it is of great significance to carry out research on high-precision imaging methods for high-squint airborne SAR. However, the high-squint SAR echoes have large Range Cell Migration (RCM), resulting in severe range–azimuth coupling and strong spatial variation. In this paper, a Modified Range Doppler Algorithm (MRDA) is proposed to cope with these effects introduced by the significant RCM in high-squint airborne SAR imaging. The bulk compensation preprocessing is first adopted to remove the considerable RCM and severe cross-coupling in a two-dimensional frequency domain. Then, Non-Linear Chirp Scaling (NLCS) in the range direction is utilized to equalize the range-variant chirp rate caused by the residual RCM and coupling and, therefore, the consistent range phase compensation can be fulfilled in range frequency domain. The modified correlation processing is executed to compensate the residual Doppler phase modulation, the residual RCM and the range-variant cubic phase modulation, which guarantees the characteristics of high efficiency and high precision. The simulations have demonstrated that the MRDA can focus the SAR echoes with large squint angles more effectively than the algorithms based on the Linear Range Walk Correction (LRWC) method. [ABSTRACT FROM AUTHOR]

Shipborne high-frequency surface wave radar (HFSWR) has a wide range of applications and plays an important role in moving target detection and tracking. However, the complexity of the sea detection environment causes the target signals received by shipborne HFSWR to be seriously disturbed by sea clutter. Sea clutter increases the difficulty of azimuth estimation, resulting in a challenging problem for shipborne HFSWR. To solve this problem, a novel azimuth correction method based on adaptive boosting error feedback dynamic weighted particle swarm optimization extreme learning machine (APO-ELM) is proposed to improve the azimuth estimation accuracy of shipborne HFSWR. First, the sea clutter is modeled and simulated. Then, we study its characteristics and analyze the influence of its characteristics on the first-order clutter spectrum and target detection accuracy, respectively. In addition, the proposed improved particle swarm optimization (PSO) and adaptive neuron clipping algorithm are used to optimize the input parameters of the ELM network. Then, the network performs error feedback based on the optimized parameter performance and updates the feature matrix, which can give a minimum clutter-error estimation. After that, it iteratively trains multiple weak learners using the adaptive boosting (AdaBoost) algorithm to form a strong learner and make strong predictions. Finally, after error compensation, the best azimuth estimation results are obtained. The sample sets used for the APO-ELM network are obtained from field shipborne HFSWR data. The network training and testing features include the wind direction, sea current, wind speed, platform speed, and signal-to-clutter ratio (SCR). The experimental results show that this method has a lower root-mean-square error than the back-propagation neural network and support vector regression (SVR) azimuth correction methods, which verifies the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In existing imaging algorithms for wide-beam multiple-receiver synthetic aperture sonar (SAS) systems, the double-square-root (DSR) range history of each receiver is generally converted into the sum of a single-square-root (SSR) range history and an error term using displaced phase center aperture (DPCA) approximation. Therefore, before imaging, each receiver's error term needs to be individually compensated in the azimuth frequency domain, which is computationally expensive. As a result, a novel wide-beam multiple-receiver SAS system algorithm with low complexity and high precision is suggested. First, the translation relationship between the range histories of the reference receiver and other receivers is used to derive an SSR approximation range history that takes into account the azimuth variance of the non-stop-hop-stop time while ignoring differential range curvature (DRC) between the range histories from different receivers. Then, using the principle of stationary phase (POSP), the two-dimensional (2-D) spectrum of the point target is obtained. Finally, the multiple-receiver data are transformed into monostatic SAS-equivalent data for imaging after phase correction, time delay correction, and azimuth reconstruction. The range-Doppler (RD) algorithm is used as an example to explain the specific steps of the proposed approach. Simulation data and ChinSAS data experiments verify that the proposed algorithm achieves an imaging performance that is comparable to that of the existing wide-beam algorithm, but with much higher computational efficiency, making it suitable for real-time imaging. [ABSTRACT FROM AUTHOR]

The transmitter and receiver of unmanned aerial vehicle (UAV) bistatic synthetic aperture radar (Bi-SAR) are respectively carried on different UAV platforms, which has the advantages of flexible movement and strong concealment, and has broad application prospects in remote sensing fields. However, the range cell migration (RCM) and azimuth non-linear phase (ANP) of UAV Bi-SAR are seriously spatially variant along the range and azimuth directions, while the UAV Bi-SAR has a short operating range, complex trajectory and wide azimuth beam. Aiming at the problem that the RCM and ANP of UAV Bi-SAR in spotlight mode are difficult to correct and equalize due to the severe two-dimensional (2D) spatial variation, an RCM correction (RCMC) and ANP equalization (ANPE) method based on Doppler domain blocking is proposed. First, the azimuth spatial variance of RCM is eliminated by Doppler blocking, and the range spatial variant RCMC is realized by RNCS. Second, by combining Doppler blocking with azimuth nonlinear chirp scaling (ANCS), this method can adapt to ANPE with larger width and more severe spatial variation. At last, the criteria of Doppler blocking are given in detail, and the effectiveness of the proposed method is verified by UAV Bi-SAR real data and computer simulation. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) is capable of monitoring the ocean all day, regardless of weather conditions. However, moving ships exhibit azimuth defocus in SAR images, which severely hampers ship recognition performance. Ships typically move in a linear motion at sea. For refocusing linear moving ships, existing SAR autofocus algorithms cannot accurately extract defocus information and require multiple iterations. To overcome the poor focusing quality and high computational complexity of existing refocusing algorithms, this paper proposes a fast and accurate refocusing scheme for moving ships in SAR imagery based on Fractional Fourier Transform (FrFT). Firstly, the azimuth line with the strongest energy in the SAR image is selected as the best azimuth line representing its motion property. Then, according to the entropy variation law of the azimuth line after FrFT, the azimuth line's optimal rotation order is determined by the proposed minimum entropy search method, which can accurately and quickly obtain defocus information. In the final refocusing module, the scheme provides two ways, i.e., fast or fine refocusing approaches, to generate well-focused images. The fast refocusing approach performs FrFT on each azimuth line at the optimal rotation order of the best azimuth line. The fine refocusing approach takes the optimal rotation order of the best azimuth line as the initial value and further searches for the optimal rotation order of other azimuth lines. In order to verify the effectiveness of the proposed scheme, experiments are carried out on a number of Gaofen-3 SAR images in different acquisition modes. The experimental results show that the proposed fast refocusing approach can achieve the fastest speed, which is 2.1% of the traditional FrFT-based method's processing time. Moreover, the proposed fine refocusing approach has the best focusing performance, achieving the lowest image entropy among existing methods. [ABSTRACT FROM AUTHOR]

Due to significant electromagnetic interference, radar interruptions, and other factors, Azimuth Missing Data (AMD) may occur in Synthetic Aperture Radar (SAR) echo, resulting in severe defocusing and even false targets. An important approach to solving this problem is to utilize Compressed Sensing (CS) methods on AMD echo to reconstruct complete echo, which can be abbreviated as the AMD Imaging Algorithm (AMDIA). However, the State-of-the-Art AMDIA (SOA-AMDIA) do not consider the influence of motion phase errors, resulting in an unacceptable estimation error of the complete echo reconstruction. Therefore, in order to enhance the practical applicability of AMDIA, this article proposes an improved AMDIA using Sparse Representation Autofocusing (SRA-AMDIA). The proposed SRA-AMDIA aims to accurately focus the imaging result, even in the Phase Error AMD (PE-AMD) echo case. Firstly, a Phase-Compensation Function (PCF) based on the phase history of the scene centroid is designed. When the PCF is multiplied with the PE-AMD echo in the range-frequency domain, a coarse-focused sparse representation signal can be obtained in the range-Doppler domain. However, due to the influence of unknown PE, the sparsity of this sparse representation signal is unsatisfying, breaking the sparse constraints requirement of the CS method. Therefore, we introduced a minimum entropy autofocusing algorithm to autofocus this sparse representation signal. Next, the estimated PE is compensated for this sparse representation signal, and a more sparse representation signal is obtained. Hence, the non-PE complete echo can be reconstructed. Finally, the estimated complete echo can be used with classic imaging algorithms to obtain high-resolution imaging results under the PE-AMD condition. Simulation and real measured data have verified the effectiveness of the proposed SRA-AMDIA. [ABSTRACT FROM AUTHOR]

Wind parameters play a vital role in studying atmospheric dynamics and climate change. In this study, a vehicle-mounted coherent wind measurement Lidar (CWML) with a wavelength of 1.55 µm is demonstrated based on a four-beam vertical azimuth display (VAD) scanning mode, and a method to estimate wind vector from power spectrum is proposed. The feasibility of the application of wind profile Lidar in vehicles is verified by calibration tests, comparison experiments, and continuous observation experiments, successively. The effective detection height of Lidar can reach 3 km. In contrasting experiments, the correlation coefficients of the magnitude and direction of horizontal wind speed measured by vehicle-mounted Lidar and fixed Lidar are 0.94 and 0.91, respectively. The experimental results reveal that the accuracies of wind speed and direction measurements with the vehicle-mounted CWML are better than 0.58 m/s and 4.20°, respectively. Furthermore, to understand the role of the wind field in the process of energy and material transport further, a proton-transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) is utilized to measure the concentration of volatile organic compounds (VOCs). Relevant experimental results indicate that the local meteorological conditions, including wind speed and humidity, influence the VOC concentrations. [ABSTRACT FROM AUTHOR]

The LuTan-1(LT-1), known as the L-band differential interferometric synthetic aperture radar (SAR) satellite system, is an essential piece of civil infrastructure in China, providing extensive applications such as surface deformation monitoring and topographic mapping. To achieve high-resolution and wide-swath (HRWS) observation abilities, the LT-1 takes the dual receiving antenna (DRA) imaging mode as its working mode. However, amplitude and phase errors between channels lead to a mismatch between the reconstruction filter and the multichannel echo signal, worsen the reconstructed azimuth spectrum, and introduce ambiguity targets in the final imaging results, seriously affecting the final imaging quality. In order to better evaluate the channel error and azimuth ambiguity performance of the LT-1 system, this paper proposed an advanced channel consistency correction method and conducted many measured data experiments. The experimental results show that the proposed method is effective, and the LT-1 system has excellent channel error control and azimuth ambiguity performance. [ABSTRACT FROM AUTHOR]

Due to the substantial electromagnetic interference, radar interruptions, and other factors, the SAR system may fail to receive valid data in some azimuth areas. This phenomenon is known as Azimuth Missing Data (AMD). If classical SAR imaging algorithms are performed directly using AMD echo, the imaging results may be defocused or even display false targets, which seriously affects the accuracy of the image. Thus, we proposed a Sub-echo Segmentation and Reconstruction Azimuth Missing Data SAR Imaging Algorithm (SSR-AMDIA) to solve the problem of incomplete echo SAR imaging in this article. Instead of using the motion compensation step of the Polar Format algorithm (PFA) to recover the full echo from the AMD echo, the proposed SSR-AMDIA eliminates the effect of the planar approximation in PFA and expands the maximum depth of focus (DOF). The raw AMD echo was first subjected to range compression and Range Cell Migration Correction (RCMC), after which the AMD-RCMC echo was divided along the range direction. Then, we constructed a series of phase compensation functions based on the sub-segment AMD-RCMC echoes to guarantee the perfect recovery of the full RCMC echoes corresponding to the sub-scenes. Finally, we combined them to obtain the complete RCMC echo, and an excellent focused imaging result was then obtained via azimuth compression. Simulation and experimental data verified the effectiveness of the proposed algorithm. Furthermore, we derived the mathematical expressions for the two-dimensional maximum DOFs of the proposed algorithm. In contrast to the State-Of-the-Art (SOA) AMDIA, the SSR-AMDIA can obtain a superior imaging performance in a larger imaging scope under the conditions of most AMD cases. [ABSTRACT FROM AUTHOR]

Knowledge of the ocean backscatter at various azimuth angles is critical to the radar detection of the ocean environment. In this study, the modified two-scale model (TSM), which introduces a correction term in the conventional TSM, is improved based on the empirical model, CMOD5.n. Then, the influences of different directional wave spectra on the prediction of azimuthal behavior of ocean radar backscatter are investigated by comparing the simulated results with CMOD5.n and the Advanced Scatterometer (ASCAT) measurements. The results show that the overall performance of the single spectra of D, A, E, and H18 and the composite spectra of AH18 and AEH18 in predicting ocean backscatter are different at different wind speeds and incidence angles. Generally, the AH18 spectrum has better performance at low and moderate wind speeds, while the A spectrum works better at high wind speed. Nevertheless, the wave spectra have little effect on the prediction of the azimuthal fluctuation of scattering, which is highly dependent on the directional spreading function. The relative patterns of azimuthal undulation produced by different spreading functions are rather different at different wind speeds, but similar under different incidence angles. The Gaussian spreading function generally has better performance in predicting the azimuthal fluctuation of scattering. [ABSTRACT FROM AUTHOR]

A typical ultrasonic sensor has a major lobe that extends beyond 45 degrees. Because the wide beam of the ultrasonic sensor's main lobe, which is used for straightforward distance measurement, has a low angular resolution, conventional methods such as incidence angle and linear angle measurements cannot accurately determine the azimuthal angle. Determining whether one or more objects are present in a single beam is also challenging. In this study, the azimuthal angles of two or more objects placed beneath a single beam are determined by the Doppler frequency shift. An ultrasonic sensor is mounted on an automobile to transmit and receive an ultrasound when the car moves towards stationary objects. The sensor picks up the object's reflected Doppler shift signal. The azimuth angle of the objects is determined by estimating the received Doppler shift signal using a standard signal processing method. Near-field motion detection systems and autonomous driving heavily rely on the ability to evaluate the azimuthal angle of objects in a vehicle's surroundings using the Doppler Effect. These are examples of low-cost technology and active safety, which the experimental results support. Based on the results and error estimation, there is an average error of less than 3% between measured and computed values. [ABSTRACT FROM AUTHOR]

Field-tower-based observations were used to estimate the Doppler velocity of deep water plunging breaking waves. About 1000 breaking wave events observed by a synchronized video camera and dual-polarization Doppler continuous-wave Ka-band radar at incidence angles varying from 25 to 55 degrees and various azimuths were analyzed using computer vision methods. Doppler velocities (DVs) associated with breaking waves were, for the first time, directly compared to whitecap optical velocities measured as the line-of-sight projection of the whitecap velocity vector (LOV). The DV and LOV were found correlated; however, the DV was systematically less than the LOV with the ratio dependent on the incidence angle and azimuth. The largest DVs observed at up-wave and down-wave directions were accompanied by an increase of the cross-section polarization ratio, HH/VV, up to 1, indicating a non-polarized backscattering mechanism. The observed DV was qualitatively reproduced in terms of a combination of fast specular (coherent) and slow non-specular (incoherent) returns from two planar sides of an asymmetric wedge-shaped breaker. The difference in roughness and tilt between breaker sides (the front face was rougher than the rear face) explained the observed DV asymmetry and was consistent with previously reported mean sea surface Doppler centroid data and normalized radar cross-section measurements. [ABSTRACT FROM AUTHOR]

The coupling and spatial variation of range and azimuth parameters is the biggest challenge for bistatic forward-looking SAR (BFSAR) imaging. In contrast with the monostatic SAR and translational invariant bistatic SAR (TI-BSAR), the range cell migration (RCM), and Doppler parameters of high-speed bistatic forward-looking SAR (HS-BFSAR) have two-dimensional spatial variation characteristics, which makes it difficult to obtain SAR images with satisfactory global focusing. Firstly, based on the configuration of the spaceborne illuminator and high-speed forward-looking receiving platform, the accurate range-Doppler domain expression of the echo signal is derived in this paper. Secondly, using this analytical expression, a range nonlinear chirp scaling (NLCS) is proposed to equalize the RCM and equivalent range frequency modulation (FM) rate so that they can be uniformly processed in the two-dimensional frequency domain. Next, in the azimuth processing, the proposed method decomposes the Doppler contribution of the transmitter and receiver, respectively. Then, an azimuth NLCS is used to eliminate the spatial variation of the azimuth FM rate. Finally, a range-dependent azimuth filter is constructed to achieve azimuth compression. Simulation results validate the efficiency and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The Second Generation Global Imager (SGLI) on the Global Change Observation Mission—Climate (GCOM-C) "SHIKISAI" has polarization observation channels at wavelengths of red (673.5 nm—P1) and near infrared (868.5 nm—P2), and it is expected to extract information of aerosols on land with higher accuracy than conventional observation methods by utilizing the scattering by atmospheric particles obtained by polarization observation. The polarization observation of SGLI adopts a method to derive the Stokes parameters I, Q, and U by observing three polarized azimuths. In this paper, the polarization observation accuracy means the polarization degree accuracy and polarization azimuth accuracy, which can be expressed as a relative value of I, Q, and U, and does not include the accuracy of radiance. In order to evaluate the polarization observation accuracy of SGLI on orbit, variations of the Q/I and U/I have been investigated using three kinds of calibration data. The effects of calibration methods and aging have been successfully eliminated by comparing independent evaluations of three kinds of calibration data. As a result, it was concluded that the variations of Q/I and U/I are achieved within a slight variation range of ±0.07% at the P1 telescope and ±0.04% at the P2 telescope. [ABSTRACT FROM AUTHOR]

Azimuth multichannel (AMC) technology is one of the mainstream technical approaches to realize high-resolution wide-swath (HRWS) imaging. It has been successfully applied to several synthetic aperture radar (SAR) satellites in orbit. However, the inevitable imbalance between channels can seriously affect the azimuth reconstruction spectrum, introducing ghost targets into the final imaging results and degrading the SAR image quality. In order to address this issue, this paper proposes a channel imbalance estimation method based on minimizing the sum of the sub-band norm (MSSBN) for the reconstructed azimuth spectrum. First, the amplitude imbalance is calibrated in the range-Doppler domain. Then, the echo in each channel with phase imbalances is reconstructed by filters separately and converted to the range-Doppler domain. Finally, the global optimization algorithm is used to find the phase error of each channel so that the reconstructed postcompensation spectrum has the smallest sub-band spectrum norm sum. By two-dimensional blocking, this method can also estimate the space-varying phase imbalance in the range dimension and the time-varying phase imbalance in the azimuth dimension. Experimental results using simulated and actual AMC SAR data from the GF-3 system validate the proposed algorithm's high estimation accuracy and excellent computational efficiency. [ABSTRACT FROM AUTHOR]

With the growth of residential rooftop PV adoption in recent decades, the problem of effective layout design has become increasingly important in recent years. Although a number of automated methods have been introduced, these tend to rely on simplifying assumptions and heuristics to improve computational tractability. We demonstrate a fully automated layout design pipeline that attempts to solve a more general formulation with greater geometric flexibility that accounts for shading losses. Our approach generates rooftop areas from satellite imagery and uses MINLP optimization to select panel positions, azimuth angles and tilt angles on an individual basis rather than imposing any predefined layouts. Our results demonstrate that shading plays a critical role in automated rooftop PV optimization and significantly changes the resulting layouts. Additionally, they suggest that, although several common heuristics are often effective, they may not be universally suitable due to complications resulting from geometric restrictions and shading losses. Finally, we evaluate a few specific heuristics from the literature and propose a potential new rule of thumb that may help improve rooftop solar energy potential when shading effects are considered. [ABSTRACT FROM AUTHOR]

Due to the advantages of flexible configuration, bistatic synthetic aperture radar (BiSAR) has the ability to effectively observe from various visual angles, such as forward view area and squint area, and has good anti-jamming characteristics. It can be applied to the surveillance of ship targets on the sea and is gradually gaining an increasing amount of attention. However, for ship targets with complex motions on the sea surface, such as maneuvering targets or ship targets under high sea conditions, the high-order Doppler frequency of the scattering points is always spatial variation (related to the spatial position of scattering points), which poses a considerable challenge for the imaging of maritime ship targets in BiSAR. To resolve this problem, a BiSAR maritime ship target imaging algorithm based on cubic phase time-scaled transformation is proposed in this paper. First, through pre-processing of echo such as Doppler prefiltering and keystone transform, the translation compensation of the BiSAR maritime ship target is completed, and the scattering point energy is corrected to within one range unit. Then, the azimuth signal is modeled as a multi-component cubic phase signal. Based on the proposed cubic phase time-scaled transformation, the Doppler centroid, frequency rate, and third-order frequency of scattering points are estimated. Eventually, the BiSAR imaging of maritime ship targets is realized. This algorithm has excellent noise immunity and low cross-terms. The simulation leads to the verification of the validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Doppler Centroid Analysis (DCA) technique is one of the major techniques that do permit a direct retrieval of ocean surface velocity from synthetic aperture radar (SAR) data. However, azimuth ambiguities in the SAR images severely restrict the capability of DCA technique to obtain accurate ocean surface Doppler velocities. Therefore, it is necessary to investigate how the azimuth ambiguities impact the Doppler velocity estimation performance and to evaluate how significant the impact is. In this paper, a model for ocean surface Doppler velocity estimation affected by azimuth ambiguities is developed resorting to jointly circular Gaussian processes, and its statistic is derived. The impact of azimuth ambiguities on Doppler velocity estimation performance in terms of Doppler centroid estimation bias and the standard deviation of Doppler centroid estimates is analyzed. The theoretical results are validated through simulation and Doppler velocities retrieved from Chinese Gaofen-3 (GF-3) SAR Doppler centroid estimates affected by azimuth ambiguities. This study will help researchers better understand the impact of azimuth ambiguities on Doppler velocity estimation, and will provide a theoretical reference for subsequent research on how to reduce the impact of azimuth ambiguities more effectively. [ABSTRACT FROM AUTHOR]

The block adjustment method can correct systematic errors in the bistatic Synthetic Aperture Radar Interferometry (InSAR) satellite system and effectively improve the accuracy of the InSAR-generated Digital Elevation Model (DEM). Presently, non-parametric methods, which use the polynomial to model the systematic errors of InSAR-generated DEMs, are most frequently used in spaceborne InSAR-DEM adjustment. However, non-parametric methods are not directly related to the physical parameters in the InSAR imaging process. Given the issue, this paper conducts adjustments in the parameter domain and proposes a three-dimensional block adjustment method for spaceborne bistatic InSAR systems based on the Range-Doppler-Phase (RDP) model. First, we theoretically analyze the sensitivities of spatial baseline, azimuth time, and slant range to the RDP geolocation model and confirm the analysis method with a simulated geolocation result. Second, we use total differential and differential geometry theories to derive adjustment equations of available control data based on sensitivity analysis. Third, we put forward an iterative solution strategy to solve the corrections of parallel baseline, azimuth time, and slant range to improve the plane and elevation accuracies of InSAR-generated DEMs. We used 29 scenes of TanDEM-X Co-registered Single look Slant range Complex (CoSSC) data to conduct simulated and real data experiments. The simulated results show that the proposed method can improve the accuracies of baseline, range, and timing to 0.05 mm, 0.1 m, and 0.006 ms, respectively. In the real data experiment, the proposed method improves the plane and elevation accuracies to 4.14 m and 1.34 m, respectively, and effectively suppresses the fracture phenomenon in the DEM mosaic area. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) radar uses waveform diversity technology to form a virtual aperture to improve the azimuth resolution of forward-looking imaging. However, the super-resolution imaging capability of MIMO radar is limited, and the resolution can only be doubled compared with the real aperture. In the radar forward-looking image, compared with the whole imaging scene, the target only occupies a small part. This sparsity of the target distribution provides the feasibility of applying the compressed sensing (CS) method to MIMO radar to further improve the forward-looking imaging resolution. At the same time, the forward-looking imaging method for a MIMO radar based on CS has the ability to perform single snapshot imaging, which avoids the problem of a motion supplement. However, the strong noise in the radar echo poses a challenge to the imaging method based on CS. Inspired by the low-rank properties of the received radar echoes and the generated images, and considering the existing information about sparse target distribution, a forward-looking super-resolution imaging model of a MIMO radar that combines sparse and double low-rank constraints is established to overcome strong noise and achieve robust forward-looking super-resolution imaging. In order to solve the multiple optimization problem, a forward-looking image reconstruction method based on the augmented Lagrangian multiplier (ALM) is proposed within the framework of the alternating direction multiplier method (ADMM). Finally, the results of the simulation and the measurement data show that the proposed method is quite effective at improving the azimuth resolution and robustness of forward-looking radar imaging compared with other existing methods. [ABSTRACT FROM AUTHOR]

For the problem of traditional passive radar target detection, the cross-correlation method is a popular solution. By processing the reference signal and the target echo signal coherently, the method is able to extract the target parameters, such as distance, velocity, and azimuth. However, the estimation performance is limited by the low signal-to-noise ratio. Therefore, a new cross-correlation algorithm for passive radar target detection is proposed in this paper. The echo signal received by the echo antenna and the reference signal received by the reference antenna are processed by differential operations to transform the single signal into multiple signals. Then, the differential reference signal is used to eliminate the signal phase in the differential echo signal. With the two-dimensional Fourier transform, the coherent accumulation of multiple signals is realized based on matched filtering of the single signal. This makes the secondary accumulation of the target signal coherent, while the interference part can only obtain incoherent secondary accumulation. In this way, the signal-to-noise ratio for target detection can be greatly improved. The paper presents the theoretical derivation of the algorithm and the quantitative analysis of its performance. The results of both simulated and measured data show that the detection performance is greatly improved compared with the traditional method. [ABSTRACT FROM AUTHOR]

A multi-channel synthetic aperture radar (SAR) on board a spaceplane orbiting near the top of the atmosphere is proposed to acquire images of cruising ships. Low pulse repetition frequency (PRF) is required for high-resolution wide-swath (HRWS) imaging, leading to inevitable problems of azimuth spectrum aliasing (ASA) and azimuth Doppler ambiguity (ADA). In this work, we propose a phase matching technique to solve the ASA problem in restoring the azimuth spectrum. A multi-stage compressive-sensing (CS) technique is also proposed to solve both ADA and ASA problems. Five similar types of cruising ship are simulated to verify the efficacy of the proposed approach, at different levels of signal-to-noise ratio. Indices of geometry match, intensity match, and structural similarity are used to identify different ships from the acquired SAR images. [ABSTRACT FROM AUTHOR]

The sparsity regularization based on the L1 norm can significantly stabilize the solution of the ill-posed sparsity inversion problem, e.g., azimuth super-resolution of radar forward-looking imaging, which can effectively suppress the noise and reduce the blurry effect of the convolution kernel. In practice, the total variation (TV) and TV-sparsity (TVS) regularizations based on the L1 norm are widely adopted in solving the ill-posed problem. Generally, however, the existence of bias is ignored, which is incomplete in theory. This paper places emphasis on analyzing the partially biased property of the L1 norm. On this basis, we derive the partially bias-corrected solution of TVS and TV, which improves the rigor of the theory. Lastly, two groups of experimental results reflect that the proposed methods with partial bias correction can preserve higher quality than those without bias correction. The proposed methods not only distinguish the adjacent targets, suppress the noise, and preserve the shape and size of targets in visual terms. Its improvement of Peak Signal-to-Noise Ratio, Structure-Similarity, and Sum-Squared-Errors assessment indexes are overall 2.15%, 1.88%, and 4.14%, respectively. As such, we confirm the theoretical rigor and practical feasibility of the partially bias-corrected solution with sparsity regularization based on the L1 norm. [ABSTRACT FROM AUTHOR]

The speed and direction of a missile shifts sharply in the dive phase, making the azimuth frequency modulation (FM) rate change with the azimuthal position, leading to azimuth ambiguities and image distortion. To solve this problem, a modified nonlinear chirp scaling (NLCS) algorithm was adopted to compensate for the azimuth FM rate. First, the geometric configuration and echo signal model of the spaceborne missile bistatic synthetic aperture radar (SAR) were built, and then the Doppler frequency correction was performed, and the 2-D spectrum of the signal was derived by the method of series reversion. Next, range migration correction and range compression were finished in the 2-D frequency domain. Following this, a modified NLCS algorithm was proposed to solve the space variance of Doppler phase problem. After compensating for the azimuth FM rate, the azimuth compression focusing was completed and the imaging result was obtained. Finally, by comparing the calculation amount, imaging effect, and performance index with the traditional NLCS algorithm, it can be concluded that the algorithm reduced the calculation amount by 1.0128 × 108 floating point operations per second (FLOPs) compared with the traditional NLCS algorithm, and the azimuth focusing effect of the edge point was greatly improved. Its resolution, peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) were improved by 0.87 m, 3.32 dB, and 1.79 dB, respectively, which proved the effectiveness and feasibility of this method. [ABSTRACT FROM AUTHOR]

Medium-Earth-orbit (MEO) synthetic aperture radar (SAR) has the advantages of short revisit time and wide coverage, and thus is a potential tool for implementing ground moving target indication (GMTI) tasks. In the paper, aiming at MEO SAR's problems of low signal-to-noise ratio and limited computation resource, an efficient imaging method is proposed for MEO multichannel SAR-GMTI systems with relatively low resolution. The proposed imaging method is designed with the consideration of both static scenes and ground moving targets, and it can simultaneously correct the range cell migrations of static scenes and multiple moving targets of no Doppler ambiguity. It needs only four Fourier transforms and twice phase multiplications, and thus is computationally efficient. Moreover, moving targets' signal characteristics, including the azimuth and range displacements and along-track interferometric phase, in the SAR image obtained by the proposed imaging method are figured out. Experimental results validate the proposed imaging method and the theoretical analyses. [ABSTRACT FROM AUTHOR]

As a new high-resolution spaceborne SAR observation mode, sliding-spot imaging has the characteristics of a large squint, long aperture time, and azimuth aliasing, and because of the dechirp operation in the imaging algorithm of this mode, it is difficult to construct a direct range–Doppler equation for its geometric processing. In this paper a conformation model based on an antenna pointing vector is presented, which fully considers the influence of the dechirp operation on the range image, starts from the relative position of the dechirped range image points and the satellite, and establishes a strict conversion model between the image coordinates and geographic coordinates using the accurate satellite–ground geometric conditions. Then the forward and reverse formulas for geometric processing of the sliding-spot mode are given based on this model. Finally, geometric calibration and positioning experiments under different conditions and field spaceborne SAR data are executed. Results show that after geometric errors caused by the SAR payload have been calibrated and other factors such as atmospheric delay, platform position, and elevation error have been compensated, the uncontrolled geometric positioning accuracy can reach within 1 m–2 m, which fully proves the effectiveness of this method in the geometric positioning of high-resolution sliding-spot images. [ABSTRACT FROM AUTHOR]

Spotlight synthetic aperture radar (SAR) achieves a high azimuth resolution with long integration times. Meanwhile, the long integration times also cause defocused and smeared images of moving objects such as cruising ships This is a typical imaging mechanism for moving objects in Spotlight SAR images. Conversely, ships can be classified as stationary or moving from the amount of smearing, and this classification method is, in general, based on manual observation. This paper proposes an automatic method for detecting cruising ships using deep learning known as the "You Only Look Once (YOLO) v5 model", which is one of the frameworks of the YOLO family. In this study, ALOS-2/PALSAR-2 L-band Spotlight SAR images over the waters around the Miura Peninsula, Japan, were analyzed using the YOLO v5 model with a total of 53 ships' images and compared with Automatic Identification System (AIS) data. The results showed a precision of approximately 0.85 and a recall rate of approximately 0.89 with an F-measure of 0.87. Thus, sufficiently high values were achieved in the automatic detection of moving ships using the deep learning method with the YOLO v5 model. As for false detections, images of breakwaters were classified as ships cruising in the azimuth direction. Further, range moving ships were found to be difficult to detect. From the present preliminary study, it was found that the YOLO v5 model is limited to ships cruising predominantly in the azimuth direction. [ABSTRACT FROM AUTHOR]

Ground moving targets (GMT), due to the existence of velocity in range and azimuth direction, will lead to the deviation from their true position and defocus in the azimuth direction during the synthetic aperture radar (SAR) imaging process. To address this problem and compress the amount of echo data, a sparse SAR imaging method for ground moving targets is proposed. Specifically, we first constructed a two-dimensional sparse observation model of the GMT based on matched filter operators. Then, the observation model was solved by a deep network, GMT sparse imaging network (GMTSI-Net), which was mainly obtained by unfolding an iterative soft threshold algorithm (ISTA)-based iterative solution. Furthermore, we designed an adaptive unfolding module in the imaging network to improve the adaptability of the network to the input of echo data with different sampling ratios. The proposed imaging network can achieve faster and more accurate SAR images of ground moving targets under a low sampling ratio and signal-to-noise ratio (SNR). Simulated and measured data experiments were conducted to demonstrate the performance of imaging quality of the proposed method. [ABSTRACT FROM AUTHOR]

As an emerging technique for detection, electromagnetic vector sensor multiple-input multiple-output (EVS-MIMO) radar has attracted extensive interest recently. This paper focuses on the coherent targets issue in EVS-MIMO radar, and a spatial smoothing estimator is developed to estimate the multiple parameters. It first recovers the rank of the array data via forward spatial smoothing. Then, it estimates the elevation angles via the rotational invariance technique. Combined with the vector cross-product method, the azimuth angles are obtained. Thereafter, with the previously achieved direction angles, the polarized parameters are acquired by using the least squares technique. Unlike the existing polarization smoothing techniques, the proposed estimator is able to estimate the two-dimensional direction parameter. Furthermore, it can provide a polarized parameter of the target. In addition, the proposed estimator is computationally efficient, since it offers closed-form and automatically paired solutions to all the parameters. Numerical experiments are carried out to show its superiority and effectiveness. [ABSTRACT FROM AUTHOR]

The azimuth multichannel synthetic aperture radar (MC-SAR) is an effective means of earth observation due to its high-resolution and wide-swath (HRWS) imaging capability. Compared with the traditional MC-SAR, the two-dimensional (2D) spectrum of the squint multichannel synthetic aperture radar (SMC-SAR) is skewed, leading to the severe coupling between azimuth signals and range signals. Therefore, the traditional imaging algorithms are inapplicable to SMC-SAR. Currently, the existing imaging algorithms for SMC-SAR need interpolation or sub-aperture processing, which results in low efficiency. This paper proposes a novel imaging scheme for spaceborne SMC-SAR to handle this issue. With the squint angle known, the Doppler centroid can be compensated for by the spectrum shift function. Additionally, the frequency correlation method (FCM) is utilized to estimate the channel phase imbalance. After that, the azimuth multichannel data are reconstructed by the filter banks to eliminate the Doppler spectrum aliasing. Finally, the data are imaged based on the modified equivalent slant range model (MESRM). Both the simulation and Gaofen-3 (GF-3) data experiments demonstrate the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]