Search

The filtered backprojection (FBP) algorithm is viewed as a preferred candidate for general bistatic synthetic aperture radar (BiSAR) imaging since it does not pose any restrictions on SAR configurations or flight paths. However, high-efficient autofocus methods such as phase gradient autofocus (PGA) or Mapdrift (MD) cannot be effectively integrated with the FBP algorithm due to the unknown properties of the BiSAR FBP imagery spectrum. In this article, a novel Fourier-based interpretation of the BiSAR FBP algorithm is presented. Based on the new viewpoint, spectral characteristics of the BiSAR FBP imagery in the wavenumber domain, including range spectral ambiguity, space-variant spectral support, and the structural 2-D phase error, are derived in detail. Using these characteristics, a computationally efficient 2-D autofocus approach is proposed. First, a preprocessing is performed to eliminate the range spectral ambiguity and to align the skewed spectrum support, which facilitates the following phase error estimation and correction. Then, an estimation of the 1-D azimuth phase error (APE) is applied by combining multiple estimation results from different subband data. Finally, the 2-D phase error is computed directly from the estimated APE by exploiting the derived analytical structure of the 2-D phase error, which is then applied to restore the BiSAR FBP image. The simulation results are presented to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Ambiguity clutter for airborne radar systems is usually caused by a uniform pulse repetition interval (UPRI) waveform, which significantly degrades target detection and location performance. To address this issue, this article proposes an ambiguity clutter suppression method resorting to a pseudorandom pulse repetition interval (PrPRI) waveform. First, an airborne radar clutter model accounting for multiple range rings with PrPRI waveform is developed. Next, a nonuniform coherent processing framework is introduced to eliminate the clutter folded in the range and Doppler domain. In particular, the reasons for the enlargement of the area free of clutter corresponding to PrPRI mode are analyzed, as well as the maximum unambiguous Doppler frequency, maximum unambiguous range, and design principles for PRI are derived. Finally, numerical examples are designed to verify that the nonuniform coherent processing framework can enlarge the clutter-free area and achieve unambiguity target detection and location. [ABSTRACT FROM AUTHOR]

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

Numerous deep-learning methods have been successfully applied to semantic segmentation (SS) and height estimation (EH) of remote-sensing imagery. It has also been proved that such a framework can be reusable for multiple tasks to reduce computational resource overhead. However, there are still some technical limitations due to the semantic inconsistency between 3-D and 2-D features and the strong interference of different objects with similar spectral–spatial properties. Previous works have sought to address these issues through hard (HPS) or soft parameter sharing (SPS) schemes. But due to unintentional integration, the specific information transmitted between multiple tasks is not clear or in a lot of redundancy. Furthermore, tuning the weights by hand between classification and regression loss functions is challenging. In this article, a novel multitask learning (MTL) method, termed associatively segmenting semantics and estimating height (ASSEH), is proposed to associatively segment semantics and estimate height from monocular remote-sensing imagery. First, considering semantic inconsistency across tasks, we design a task-specific distillation (TSD) module containing a set of task-specific gating units (TSGUs) for each task at the cost of fewer parameters. The module allows for task-specific features to be tailored from the backbone while allowing for task-shared features to be transmitted. Second, we leverage the proposed cross-task propagation (CTP) module to construct and diffuse the local pattern graphlets at the common positions across tasks. Such a high-order recursive method can bridge two tasks explicitly to effectively settle semantic ambiguities caused by similar spectral characteristics with less computational burden and memory requirements. Third, a dynamic weighted geometric mean (DWGeoMean) strategy is introduced to dynamically learn the weights of each task and be more robust to the magnitude of the loss function. Finally, the results of the ISPRS Vaihingen dataset and the urban semantic 3-D (US3D) dataset well demonstrate that our ASSEH achieves state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Due to the constraint of minimum antenna area, 2-D ambiguity resolving is a challenging task in ship focusing of single-channel SAR mounted on high-speed maneuvering platforms. In order to accommodate the issues, a ship focusing and positioning algorithm based on 2-D ambiguity resolving is proposed. First, we analyze the constraint of minimum antenna area and the distribution of the 2-D ambiguity area. An optimal-PRF SAR concept is proposed, where the signal ambiguity is evenly distributed to the range and azimuth directions. In this concept, the timing sequence of the orthogonal phase-coded waveform is designed to make the target echoes in different regions orthogonal. Then, an orthogonal matching filter is used to suppress the signal energy in range ambiguity regions. Aiming at the target defocus and position shift caused by the Doppler ambiguity, we propose an azimuth ambiguity resolving method. The Doppler ambiguity number can be estimated by residual envelope inclination. Subsequently, the target can be relocated and accurately focused by the estimated Doppler parameters. After the operation of each target is completed, the focusing SAR image of the whole scene can be obtained. Finally, simulation results and real data processing are presented to validate the proposed algorithm. [ABSTRACT FROM AUTHOR]

It is hard to tackle the near-range clutter when range ambiguity exists in the non-sidelooking moving target detection (MTD) application. The angle-Doppler spectra of the far- and near-range clutter cannot be aligned simultaneously in this case due to the range dependence, which would significantly degrade the performance of the space–time adaptive processing (STAP) technology. To address this problem, an elevation element multifrequency subpulse coding (EMFSPC) array framework is proposed in this article. For each pulse duration, the main-lobe beam of the proposed framework can automatically sweep the full space by coding the subpulses and the transmitting elements, which steers the subpulses to different directions. Besides, these multiple subpulses occupy different range-frequency bands, and thus corresponding bandpass filters could be carefully designed to extract the unambiguous signals. After that, one can align the clutter spectra centers and employ the full-dimensional or dimension-reduced STAP techniques to achieve clutter cancellation. Furthermore, the simulation experiments are conducted to demonstrate the validity of the proposed EMFSPC system in near-range strong clutter suppression. [ABSTRACT FROM AUTHOR]

The surface wave investigation and monitoring (SWIM) aboard the China-France Oceanography Satellite (CFOSAT), a pioneer conically scanning wave spectrometer, was successfully launched on October 29, 2018. Its innovative configuration composed of one nadir and five rotating near-nadir beams is designed to simultaneously observe the directional wave spectrum at a global scale. In this study, we systematically implement the spectral analysis of the radar backscattering with the periodogram technique to obtain the fluctuation spectrum for each azimuth direction. The 2-D fluctuation spectrum of the three spectral beams ($\theta = 6^\circ $ , 8°, and 10°) combines all the azimuth directions within one entire rotation of 360°. The case study demonstrates that the wave features (peak wavelength and direction) are roughly consistent between the estimated fluctuation spectrum and the collocated WaveWatch III wave slope spectrum. A marked up-to-downwave asymmetry of the fluctuation spectrum with larger spectral level in the upwave direction for all the three spectral beams is observed. A ratio is defined between the fluctuation spectrum within the [0°, 180°] sector relative to the [180°, 360°] sector. Statistics display that this ratio is greater than 1 when it denotes the up-to-downwave ratio and smaller than 1 for the down-to-upwave ratio. This observed spectrum asymmetry is linked to the asymmetric modulation from upwind to downwind. In addition, we employ such finding to help remove the 180° wave direction ambiguity from a practical point of view. Preliminary results of the direction ambiguity removal display a bias of 41.3°, 40.6°, and 36.7° for the beams. The 10° beam shows slightly better performance compared to the other two beams in terms of bias and standard deviation. This shall lay a strong basis for the operational implementation of such algorithm to resolve the direction ambiguity. [ABSTRACT FROM AUTHOR]

Hybrid-polarimetric architecture may become a new option for spaceborne quadrature-polarimetric (quad-pol) synthetic aperture radar (SAR) mainly due to the range ambiguity improvement without loss of polarization information. To inherit the analytical methods developed for the conventional quad-pol SAR data, it is necessary to transform the hybrid quad-pol SAR data into a linear polarimetric basis. However, this operation will result in deterioration of azimuth ambiguity performance. The theoretical analysis on range and azimuth ambiguities in quad-pol SAR has been relatively complete, which is also summarized in this article. Yet, there is no real data to verify the equivalence of polarization information and to compare the ambiguity levels. Based on P-band airborne experiment, real hybrid and conventional quad-pol SAR data are used for comparative verification. In addition, considering that polarimetric target decomposition is often used in the practical applications, we suggest a new perspective from target decomposition for the ambiguities in quad-pol SAR. Identical polarimetric processing results for two sets of comparative data verify that hybrid quad-pol SAR data are indistinguishable from conventional quad-pol SAR data. The demonstrated intensity images and decomposed RGB images with azimuth ambiguities, acquired by the two quad-pol modes, completely conform to the theory. [ABSTRACT FROM AUTHOR]

Modality translation, which aims to translate images from a source modality to a target one, has attracted a growing interest in the field of remote sensing recently. Compared to translation problems in multimedia applications, modality translation in remote sensing often suffers from inherent ambiguities, i.e., a single input image could correspond to multiple possible outputs, and the results may not be valid in the following image interpretation tasks, such as classification and change detection. To address these issues, we make the attempt to utilizing time-series data to resolve the ambiguities. We propose a novel multimodality image translation framework, which exploits temporal information from two aspects: 1) by introducing a guidance image from given temporally neighboring images in the target modality, we employ a feature mask module and transfer semantic information from temporal images to the output without requiring the use of any semantic labels and 2) while incorporating multiple pairs of images in time series, a temporal constraint is formulated during the learning process in order to guarantee the uniqueness of the prediction result. We also build a multimodal and multitemporal dataset that contains synthetic aperture radar (SAR), visible, and short-wave length infrared band (SWIR) image time series of the same scene to encourage and promote research on modality translation in remote sensing. Experiments are conducted on the dataset for two cross-modality translation tasks (SAR to visible and visible to SWIR). Both qualitative and quantitative results demonstrate the effectiveness and superiority of the proposed model. [ABSTRACT FROM AUTHOR]

This article deals with the synthesis and analysis of quasi-orthogonal nonlinear frequency modulation (NLFM) waveforms to mitigate the impairments of ambiguous returns in quadrature-polarimetric (quad-pol) synthetic aperture radars (SARs). To this end, focusing on signals with a continuous piecewise linear instantaneous frequency, the design of a waveform pair exhibiting both a low cross correlation energy (CCE) and low peak to sidelobe ratios (PSLRs), is considered. To handle the resulting nondeterministic polynomial (NP) hard problem, a coordinate descent (CD) method is employed, where, at each step, the marginal minimization is tackled via a MATLAB optimization toolbox. Hence, transmission/reception schemes jointly capitalizing quasi-orthogonal NLFM waveforms and azimuth phase coding (APC) techniques are proposed to suppress ambiguity interference. Moreover, a systematic framework for the evaluation of the resulting azimuth ambiguity-to-signal ratio (AASR) and range ambiguity-to-signal ratio (RASR) is provided. Finally, detailed simulation experiments based on the LuTan (LT-1) parameters are carried out to verify the practicability and effectiveness of the newly proposed transceiver schemes. [ABSTRACT FROM AUTHOR]

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

A nonlinear trajectory of a radar platform in synthetic aperture radar (SAR) may lead to severe coupling between the range and the azimuth, which may make the ambiguity function (AF) analysis complicated. The numerical algorithm-based AF analysis may be computationally expensive, while the existing analytical algorithm-based AF analysis may cause large errors because it does not consider the coupling between the range and the azimuth. By observing that the singular value decomposition (SVD) is good to deal with the coupling problem, in this article, we propose an effective AF analysis based on SVD. The key idea is to first use a small amount of sampling points for SVD of the coupled term in the AF and then the decoupled vectors are fitted to high-order polynomials for the analytical AF calculation. It converts the double integral into the product of two single integrals in the calculation. From the proposed SVD-based AF analysis, three parameters, namely, 3-dB resolution, peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR), are then effectively computed. The simulated results verify the good performance of the proposed SVD-based AF analysis. [ABSTRACT FROM AUTHOR]

Phase decorrelation, as one of the main error sources, limits the capability of interferometric synthetic aperture radar (InSAR) for deformation mapping over areas with low coherence. Although several methods have been realized to reduce decorrelation noise, for example, by phase linking and spatial and temporal filters, their performances deteriorate when coherence estimation bias exists. We present an arc-based approach that allows reconstructing unwrapped interval phase time-series based on iterative weighted least squares (WLS) in temporal and spatial domains. The main features of the method are that phase optimization and unwrapping can be jointly conducted by spatial and temporal iterative WLS and coherence matrix bias has negligible effects on the estimation. In addition, the linear formation makes the implementation suitable with small subset of interferograms, providing an efficient solution for future big SAR data. We demonstrate the effectiveness of the proposed method using simulated and real data with different decorrelation mechanisms and compare our approach with the state-of-art phase reconstruction methods. Substantial improvement can be achieved in terms of reduced root-mean-square error (RMSE) in the simulation data and increased density of coherent measurements in the real data. [ABSTRACT FROM AUTHOR]

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

Precise extraction of ionospheric total electron content (TEC) observations with high precision is the precondition for establishing high-precision ionospheric TEC models. Nowadays, there are several ways to extract TEC observations, e.g., raw-code method (Raw-C), phase-leveled code method (PL-C), and undifferenced and uncombined precise point positioning method (UD-PPP); however, their accuracy is affected by multipath and noise. Considering the limitations of the three traditional methods, we try directly to use the phase observation based on zero-difference integer ambiguity to extract ionospheric observations, namely, PPP-Fixed method. The main goal of this work is to: 1) deduce the expression of ionospheric observables of these four extraction methods in a mathematical formula, especially the satellite and receiver hardware delays; 2) investigate the performance and precision of ionospheric observables extracted from different algorithms using two validation methods, i.e., the co-location experiment by calculating the single difference for each satellite, and the single-frequency PPP (SF-PPP) test by two co-location stations; and 3) use the short arc experiment to demonstrate the advantages of the PPP-Fixed method. The results show that single-difference mean errors of TEC extracted by PL-C, UD-PPP, and PPP-Fixed are 1.81, 0.59, and 0.15 TEC unit (TECU), respectively, and their corresponding maximum single-difference values are 5.12, 1.68, and 0.43 TECU, respectively. Compared with PL-C, the precision of the TEC observations extracted by the PPP-Fixed method is improved by 91.7%, while it is 67.3% for UD-PPP. The SF-PPP experiment shows that PPP-Fixed is the best among these methods in terms of convergence speed, correction accuracy, and reliability of positioning performance. Moreover, the PPP-Fixed method can achieve high accuracy even when the observed arc is short, e.g., within 40 min. [ABSTRACT FROM AUTHOR]

Attributed to the maneuverability, the shipborne high-frequency surface wave radar (HFSWR) enables a larger coverage in ocean wind measurement than a shored-based system does. However, the antenna aperture of shipborne radar is usually limited by the ship size, which troubles the direction of arrival (DOA) estimation accuracy. In addition, the wind direction ambiguity caused by monostatic radar illumination remains challenging. In this article, an unambiguous wind direction estimation method based on a compact shipborne HFSWR is proposed. An equivalent dual-station model combining the successive radar data collected at two close locations is developed to solve the DOA ambiguity in wind direction estimation. A direction-finding algorithm incorporating the Doppler shifts due to ship motion and current shear is adopted to estimate wind direction from the ratio of the positive and negative Bragg peak powers. Moreover, three different wave directional spreading models are applied for performance comparison. Numerical simulation is conducted to evaluate the effect of dual-station configuration on the estimation accuracy. Finally, field experimental results are given to verify the correctness of the method. Radar-derived wind direction field agrees well with that provided by a numerical weather model. [ABSTRACT FROM AUTHOR]

Traditional synthetic aperture radar (SAR) imaging is limited to achieve the high-resolution image of the side-looking areas. Nevertheless, equipped with a small size linear array across the trajectory, forward-looking multichannel SAR (FLMC-SAR) is capable of reconstructing the high-resolution image of the front area. In FLMC-SAR imaging framework, the left-right Doppler ambiguity is expected to resolve with beamforming approaches using the multichannel system diversity. However, beamforming-based Doppler ambiguity resolving is sensitive to the array deviation angle, which causes a mismatch between the azimuth angle and Doppler frequency. In this article, we propose an array deviation angle calibration and imagery algorithm for FLMC-SAR. The space–time characteristic of FLMC-SAR is explored and the range-dependent array deviation angle model is established. Following the Doppler beam sharpening imaging, strong targets are selected to derive the mismatch of the space–time characteristic. A maximum likelihood estimation of the array deviation angle is developed to modify the matching between the azimuth angle and Doppler frequency. Therefore, the left-right Doppler ambiguity can be solved correctly, yielding high-resolution FLMC-SAR imagery. Extensive simulation and real data experiments are performed to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Multistatic geosynchronous synthetic aperture radar (GEO SAR) utilizes multiple satellites’ transmitted and received signals simultaneously to generate multiple phase centers (PCs) and to reduce the synthetic aperture time and the power budget. Two key problems of this SAR system are the design of the PC array configuration to satisfy the resolution requirements and the suppression of the grating lobes that are inherently introduced by the PC array. The resolution of the SAR can be analyzed using generalized ambiguity functions (GAFs). However, the current research on the multistatic SAR resolution and grating lobes is mostly based on specified configurations and numerical simulation methods, which cannot establish the relationship between the system parameters and the resolution. This article proposes an analytical analysis method for the multistatic GEO SAR GAF-based on the array spatial ambiguity function (ASAF). First, gradient analysis is used to obtain analytical expressions for ASAF and the multistatic SAR GAF. On this basis, an analytical resolution expression is obtained, and an orbital element design method that considers the Earth’s rotation is proposed. In addition, the lobe positions are analytically expressed based on the geometry, and the grating lobes are suppressed by designing the optimal integration time such that the null depth of the velocity ambiguity function (VAF) coincides with the grating lobe positions. Finally, simulation results at various positions for various orbit types demonstrate the accuracy of the GAF approximation formula and the satisfactory performance of the optimal time expression in suppressing the grating lobes. [ABSTRACT FROM AUTHOR]

Multiple-input-multiple-output (MIMO)-radar systems employing ultrawideband (UWB) signals promise enhanced imaging performance. In this article, the generalized ambiguity function (GAF) for an MIMO-radar system is derived by using a set of quasi-orthogonal step-frequency UWB-throb signals. The effect of the step-frequency increment on the orthogonality property of the step-frequency UWB-throb signals is first analyzed. The properties of the UWB-GAF are also described. Computer simulation plots are generated for the delay-Doppler resolution function, delay-angle resolution function, Doppler-angle resolution function, delay profile, Doppler profile, and power beampattern for various design parameters of the MIMO-radar system and the employed UWB-throb signals. For the purpose of comparison, the same resolution functions and profiles are also generated for UWB linear-frequency-modulated (LFM) chirp signals. Performance analysis is conducted to demonstrate the resolution and the clutter-suppression capabilities of the GAF of an MIMO-radar system using UWB-throb signals in comparison with that of an MIMO-radar system using UWB-LFM-chirp signals. In principle, the UWB-GAF of an MIMO-radar system offers many degrees of freedom and allows for tradeoffs between the various signal-and-system design parameters. Such tradeoffs are of importance in practice for reducing the system complexity, enhancing the performance, and achieving the cost-effectiveness. [ABSTRACT FROM AUTHOR]

Hyperspectral unmixing aims at identifying a set of elementary spectra and the corresponding mixture coefficients for each pixel of an image. As the elementary spectra correspond to the reflectance spectra of real materials, they are often very correlated, thus yielding an ill-conditioned problem. To enrich the model and reduce ambiguity due to the high correlation, it is common to introduce spatial information to complement the spectral information. The most common way to introduce spatial information is to rely on a spatial regularization of the abundance maps. In this article, instead of considering a simple but limited regularization process, spatial information is directly incorporated through the newly proposed context of spatial unmixing. Contextual features are extracted for each pixel, and this additional set of observations is decomposed according to a linear model. Finally, the spatial and spectral observations are unmixed jointly through a cofactorization model. In particular, this model introduces a coupling term used to identify clusters of shared spatial and spectral signatures. An evaluation of the proposed method is conducted on synthetic and real data and shows that results are accurate and also very meaningful since they describe both spatially and spectrally the various areas of the scene. [ABSTRACT FROM AUTHOR]

We report the analysis of opposite-side ambiguities in single-pass radar sounding interferometry. Nadir pointing radar sounders suffer inherent cross track ambiguities that cannot be separated with the power image alone. Interferometry can be used to interpret these ambiguities when data are collected with multichannel receivers. However, opposite-side surface clutter, volume scattering, and cross track range misalignment create unique interferometric phase and correlation signatures. Such signatures are observed experimentally in data collected by the Polarimetric Airborne Radar Ice Sounder (POLARIS) P-band multichannel radar sounder. We derive analytic expressions to predict the observations and validate them with simulation. In addition, we observe and explain a correlation dropout feature that is due to volume scattering competing with surface clutter in the null of the cross track antenna pattern. The purpose of this article is to explain opposite-side ambiguity signatures in radar sounder interferometry and provide models and techniques for scientific interpretation of interferograms. [ABSTRACT FROM AUTHOR]

Radar interferograms provide a map of the phase difference between the reference and repeat acquisitions modulo ${2\pi }$. Under ideal conditions, the phase can be unwrapped to provide an absolute phase connection across the map, although there is always an unknown integer phase ambiguity (i.e., ${N2\pi }$) for the entire map. Here, we demonstrate a practical time series method to solve for these integer ambiguities in order to recover the absolute phase change between the first and last SAR images. An important first step is to correct the phase of each SAR image for the well-known solid earth tide, which typically produces a line of sight offset ±150 mm, as well as, trends along and across each image of ~20 mm. This tide correction significantly reduces the noise in the InSAR time series, especially at the L-band. These tidally corrected interferograms are then unwrapped and used to solve for a set of integer ambiguities that achieves phase closure when summing around loops in the stack. There is an infinite number of ambiguity combinations that achieve loop closure; thus, regularization is required. In contrast to previous studies that use a least-squares approach to find the ambiguities, we adopt an ${L}_{1}$ -norm approach to find the minimum number of ambiguity corrections needed to achieve loop closure. We note that the split-spectrum ionospheric correction can introduce ${N\pi }$ ambiguities and suggest two approaches for correcting both ${N2\pi }$ and ${N\pi }$ ambiguities. [ABSTRACT FROM AUTHOR]

Nonvolume decorrelation ($\gamma _{\mathrm {Nonvol}}$) united with the unknown ground contribution will bring a 2-D ambiguity to volume-only coherence, making the inversion underdetermined even when multiple baselines are available. In the context of random volume over ground (RVoG) model and three-stage algorithm, this paper theoretically presented the varied response of different baselines to both $\gamma _{\mathrm {Nonvol}}$ and ground contribution, and then proposed a new multi-baseline inversion method to reduce the 2-D ambiguity. The proposed method includes two steps, calculating the common overlapped ambiguity from different baselines and fixing the extinction coefficient, to more accurately retrieve the volume-only coherence and forest height. It makes no assumptions on $\gamma _{\mathrm {Nonvol}}$ and ground contribution. The method was validated and compared with three single-baseline inversions and two published multi-baseline inversions by using the airborne P-band polarimetric SAR interferometry (PolInSAR) data and the reference data of LiDAR canopy height model (CHM) over a dense rainforest site. Results showed that the developed multi-baseline method successfully reduced the combined influence of both $\gamma _{\mathrm {Nonvol}}$ and ground contribution, and performed better than any single baseline, improving the ${R}^{2}$ from 0.60 to 0.77 and unbiased root-mean-square error (RMSE) from 1.32 to 1.04 m at the scale of ca. $100 \times 140\,\,\text{m}^{2}$. Moreover, the multi-baseline scheme is relatively robust among different baseline combinations. [ABSTRACT FROM AUTHOR]

In this paper, a new algorithm is presented to image ground moving targets in a synthetic aperture radar (SAR) system based on range frequency reversal transform-fractional Fourier transform (RFRT-FrFT). In this algorithm, a range compressed signal is initially transformed into the range frequency domain and then RFRT is proposed to directly compensate the range migration via multiplying the signal in the range frequency domain by its reversed data according to the equal interval sampling of range frequency variable, which can significantly decrease the computational complexity in target envelope migration elimination. Then, FrFT is applied to accomplish the target motion parameter estimation after range migration alignment. Finally, a ground moving target is well focused after motion compensation. The effectiveness of the proposed algorithm is validated by both simulated and real SAR data. [ABSTRACT FROM AUTHOR]

In this paper, we propose a long-time coherent integration method for a maneuvering target with the first-, second-, and third-order range migrations, and the complex Doppler frequency migration. In this method, after range compression, the echo signal is first transformed into the range-frequency and Doppler domain based on series reversion, and then an azimuth matched filtering procedure is implemented in the 2-D frequency domain. It can eliminate the coupling effects between range and azimuth jointly caused by the radial velocity, radial acceleration, and radial acceleration rate of a moving target. Due to the linear transform property, the proposed method can work well under low signal-to-clutter and noise ratio. In addition, the Doppler ambiguities, when target azimuth spectrum either is within a pulse repetition frequency (PRF) or spans over neighboring PRF bands, can be well solved. Both simulated and real synthetic aperture radar data processing results are provided to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Imaging of a ground moving target (GMT) with synthetic aperture radar (SAR) is a challenging task, particularly when the Doppler ambiguity happens. This paper proposes a novel GMT range model and a novel Doppler ambiguity-tolerated GMT imaging algorithm based on modified keystone transform. In the proposed GMT range model, the range from radar antenna to the scattering center on the target is divided into two parts: the range from radar antenna to the target centroid and the projection length on the light of sight from the target centroid to the scattering center. Based on the new range model, a Doppler ambiguity-tolerated range cell migration correction (RCMC) method is proposed, in which keystone transform is modified to realize the differential RCMC by interpolation with nonzero phase sinc kernel. Finally, the GMT image is obtained in the range-Doppler domain by matched filtering in the slow-time domain and is restored into the 2-D space domain. The effectiveness of our proposed model and imaging method is demonstrated by both simulated and real airborne SAR data. [ABSTRACT FROM AUTHOR]

We present a new algorithm for suppressing azimuth ambiguities when measuring surface currents with an along-track interferometric (ATI) synthetic aperture radar in heterogeneous scenes, such as coastal waters or rivers. The key of the proposed algorithm involves a careful analysis of a parameter called the eigenvalue spectrum entropy (EVSE), which is defined as the entropy of the eigenvalue spectrum of the ATI covariance matrix computed in the Doppler domain. The physical meaning of EVSE is that it serves as a descriptor for the degree to which an unambiguous signal component and an ambiguous one are mixed. With the help of EVSE, azimuth ambiguities can be suppressed. Simulation results demonstrate that as compared with the conventional ATI method without azimuth ambiguity suppression, the proposed algorithm allows for a pronounced improvement in the current measuring accuracy. Other advantages of the proposed algorithm lie in the fact that it is not only adaptive, due to its ability to automatically capture the useful Doppler band whose width and position may both vary for different radar and scene parameters, but it also needs a minimal number of user inputs, making it a quite attractive algorithm for routine implementation. [ABSTRACT FROM AUTHOR]

Coherent point (including persistent and distributed scatterers) selection and phase ambiguity treatment (or parameter estimation) are the key tasks involved in multitemporal InSAR (MTInSAR) algorithms, which are usually conducted separately with empirical thresholds. It is not rare to see that due to the discrepancies on threshold setting, even for the same MTInSAR technique with the same data sets, it will raise different (sometimes quite notable) results and affect the applicability of InSAR techniques. We propose here an integrated MTInSAR estimator that combines the coherent point selection and phase vector unwrapping into a single step. Essentially, the estimator aims to recover the unwrapped phase vector at coherent points. Therefore, it could serve as an alternative solution of spatial–temporal phase unwrapping problem. In the estimator, wrapped phase at all pixels in short baseline interferograms are taken as observations. Starting from the phase differences at arcs of a fully connected network of pixels, based on the residual analysis and spatial closure of phase triangularity, the estimator can detect and delete the arcs having unacceptable phase noise and phase ambiguities. By integrating the phase differences at the remained arcs, the unwrapped phase at coherent points in consecutive acquisition intervals can be obtained. Impressively, the estimator is immune to the bias raised by improper deformation model. The performance of the proposed estimator is evaluated via semisynthetic and real data tests. Considering that the phase enhancement algorithms (e.g., phase-linking and Extended Minimum Cost Flow-Small BAseline Subset) that can reconstruct high-quality wrapped phases are gaining popularity, the proposed estimator can also be implemented as a postprocessing module of these algorithms for retrieval of unwrapped phase vectors at coherent points. [ABSTRACT FROM AUTHOR]

Vibration or rotation on a target or any structure of a target might induce a frequency modulation on the returned radar signal, which is called micro-Doppler effect, and is widely used for many of the remote sensing applications such as target detection, classification, and recognition. However, the micro-Doppler frequency could be large and it may cause micro-Doppler ambiguities which are undesirable in these applications. In this paper, we propose a novel and flexible method to resolve the micro-Doppler ambiguities based on the time-delayed cross correlation processing of wideband radar echoes for range-spread targets. Variable-sized shrinkage ratio can be obtained to reduce the micro-Doppler frequency of the signal to an appropriate numerical value, and the micro-Doppler ambiguities can be resolved in different situations. The effectiveness of the proposed method is validated by simulations and real data experiments. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a phase-derived-range (PDR) method for direct sampling of linear-frequency-modulated radar signals. This method is capable of measuring multiple scatterers' ranges of a target and yields root-mean-squared range error values at subwavelength level; therefore, it has great potential to measure micromotions of moving targets and is of significant importance for target recognition. The main challenge that we have solved is extracting ambiguous Doppler phases from high-resolution range profiles generated through a match filter. For guiding the implementation in radar systems, restraint conditions of radar parameters have been systematically justified based on the principle of ambiguity resolution. We have provided a systematic algorithm flowchart for PDR, especially for wideband direct sampling radars. Both simulated and experimental results under different radar parameter settings are presented and validate the performance. [ABSTRACT FROM PUBLISHER]

This paper describes a clutter suppression approach and the corresponding moving target imaging algorithm for a multichannel in azimuth high-resolution and wide-swath (MC-HRWS) synthetic aperture radar (SAR) system. Incorporated with digital beamforming processing, MC-HRWS SAR systems are able to suppress the Doppler ambiguities to allow for HRWS SAR imaging and null the clutter directions to suppress clutter for ground moving target indication. In this paper, the degrees of freedom in azimuth for the multichannel SAR systems are employed to implement clutter suppression. First, the clutter and moving target echoes are transformed into the range compression and azimuth chirp Fourier transform frequency domain, i.e., coarse-focused images formation, when the clutter echoes are with azimuth Doppler ambiguity. Considering that moving targets are sparse in the imaging scene and that there is a difference between clutter and a moving target in the spatial domain, a series of spatial domain filters are constructed to extract moving target echoes. Then, using an extracted moving target echo, two groups of signals are formed, and slant-range velocity of a moving target can be estimated based on baseband Doppler centroid estimation algorithm and multilook cross-correlation Doppler centroid ambiguity number resolving approach. After the linear range cell migration correction and azimuth focus processing, a well-focused moving target image can be obtained. In addition, the proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases. Some simulation experiments are taken to demonstrate our proposed algorithms. Finally, some real measured data results are presented to validate the theoretical investigations and the proposed approaches. [ABSTRACT FROM PUBLISHER]

The wind retrieval performance of a fixed fan-beam scatterometer operating at C-band in VV polarization [Advanced SCATterometer (ASCAT) type] is well established in the range of 0-25 m/s. This work evaluates prospective extensions with HH- and VH-polarized beams aimed at improving retrievals at extreme wind speeds, from 25 to 65 m/s. The geophysical model functions for C-band VV-, HH-, and VH-polarized backscatter used in the wind retrieval simulations are defined, along with an objective assessment of the quality scores ascribed to the optional beam configurations. Our study finds that the introduction of a VH capability in the midbeam improves the determination of wind speed over the entire scatterometer swath, with wind speed root-mean-square (rms) errors of about 0.5 m/s. The introduction of HH beams in the fore/aft antennas improves the determination of the ocean surface wind vector (wind speed and direction) but over a more limited portion of the outer swath, with wind vector rms errors as low as 6 m/s, but conditioned to a priori information to resolve the directional ambiguity. If the determination of wind speed primes over the determination of wind vectors at high wind speeds, then the introduction of a single VH capability in the midbeam antenna comes forth as the most simple and cost-effective manner to extend the wind retrieval capabilities of an ASCAT-type scatterometer into the domain of extreme winds. [ABSTRACT FROM PUBLISHER]

This paper presents an opportunity to cancel range ambiguities in synthetic aperture radar (SAR) configuration. One of the limitations of SAR systems is the range ambiguity phenomenon that appears with long delayed echoes. The reflected signal corresponding to one pulse is detected when the radar has already transmitted the next pulse. Thus, this signal is considered as an echo from the next pulse. This paper investigates the opportunity of coding the transmitted pulses using an orthogonal frequency-division multiplexing pulse. The results show that coded-OFDM signals outperform conventional chirp signal and make it possible to relax constraints placed upon the pulse repetition frequency. [ABSTRACT FROM PUBLISHER]

An alternative approach to sea surface wind retrieval using synthetic aperture radar (SAR) stripmap (SM) data is explored in this paper, using both the polarization residual Doppler frequency (PRDF) - the difference between the VV and HH Doppler centroids - and the normalized radar cross section (NRCS). The PRDF not only enables the possible elimination of unwanted biases present in both VV and HH Doppler estimates but also helps decrease the number of wind ambiguities down to two. In order to successfully infer the wind field from the PRDF, the use of a geophysical Doppler model function, such as the general curvature model (GCM)-Dop, is necessary. Using such a function, a simulated version of the PRDF at X-band is analyzed in terms of the sea surface wind field at various incidence angles. Simulations first show that the PRDF increases with increasing incidence angle regardless of wind field conditions. Actual PRDF measurements also exhibit strong correlation with radial components of the wind speed. An alternate SAR wind retrieval procedure, incorporating both the PRDF and the NRCS, is tested on a series of dual-polarized SM TerraSAR-X scenes carefully selected along the Norwegian coast. The geophysical model functions used for this analysis are the GCM-NRCS and GCM-Dop. A 1.13-m/s bias, with a correlation of 0.85 and a 1.86-m/s rmse, exists between the mean estimated wind speeds and in situ measurements, while a 15.43° bias, with a 0.93 correlation coefficient and a 34.1° rmse, is found between the mean estimated wind directions and in situ measurements. [ABSTRACT FROM PUBLISHER]

The paper investigates the possibility to enhance the TerraSAR-X (TSX) azimuth resolution by means of staring spotlight imaging in combination with an extended azimuth pattern steering. The current TSX spotlight modes are briefly reviewed, and the azimuth steering limitations are discussed. Based on a realistic TSX azimuth pattern simulation and performance estimation using a Kepler orbit and the WGS84 reference ellipsoid, the key performance parameters are estimated for an increasing azimuth pattern steering angle span. The azimuth ambiguity performance is identified to be the driving performance parameter. Experimental TSX staring spotlight high-resolution images are presented. They demonstrate and verify the envisaged performance estimation. The paper concludes with a concept for a high-resolution TSX staring spotlight mode that serves as baseline for the upcoming operational implementation. [ABSTRACT FROM PUBLISHER]

An innovative technique to estimate the local azimuth ambiguity-to-signal ratio (AASR) in synthetic aperture radar (SAR) images is presented. Unlike the backscatter-based (BB) technique, the proposed one, which is based on the spectral properties of the image, does not require that the areas responsible for the ambiguity lie within the focused image. Analysis of real TerraSAR-X data shows that the estimates of the proposed technique are consistent with the BB ones. Moreover, according to simulations, the proposed technique seems to provide more accurate estimates than the BB method, especially for high values of the local AASR. [ABSTRACT FROM AUTHOR]

Using multichannel in azimuth to suppress the Doppler ambiguities allows for high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) imaging, thus overcoming the minimum antenna area constraint of the conventional space-borne SAR. If the degrees of freedom in azimuth are used for the clutter suppression, the ground moving target indication (GMTI) can be achieved. Therefore, a space-borne multichannel SAR system for GMTI has the potential to offer HRWS imaging capability to some extent. However, here, the GMTI performance may suffer from the Doppler ambiguity caused by the undersampling. This paper focuses on the analysis of the influence of pulse repetition frequency (PRF) on GMTI performance in Doppler ambiguity. The multichannel signal models of the clutter and the moving target with Doppler ambiguity are derived in complex image domain. Considering the Doppler ambiguity and the multichannel spatial ambiguity, the influence of PRF on the output signal-to-clutter-plus-noise ratio after adaptive clutter suppression and the signal-to-noise ratio loss after SAR imaging is discussed. Accordingly, the design considerations of PRF for optimizing GMTI performance in multichannel SAR systems with HRWS imaging capability are given, along with a simulation example. Finally, the real-data experiments verify the theoretical investigations. [ABSTRACT FROM PUBLISHER]

In this paper, a general scheme for complete model-based decomposition of the polarimetric synthetic aperture radar (POLSAR) coherency matrix data is presented. We show that the POLSAR coherency matrix can be completely decomposed into three components contributed by volume scattering and two single scatterers (characterized by rank-1 matrices). Under this scheme, solving for the volume scattering power amounts to a generalized eigendecomposition problem, and the nonnegative power constraint uniquely determines the minimum eigenvalue as the volume scattering power. Furthermore, in order to discriminate the remaining components, we propose two approaches. One is based on eigendecomposition, and the other is based on model fitting, both of which are shown to properly resolve the surface and double-bounce scattering ambiguity. As a result, this paper in particular contributes to two pending needs for model-based POLSAR decomposition. First, it overcomes negative power problems, i.e., all the decomposed powers are strictly guaranteed to be nonnegative; and second, the three-component decomposition exactly accounts for every element of the observed coherency matrix, leading to a complete utilization of the fully polarimetric information. [ABSTRACT FROM PUBLISHER]

Orientation angle compensation was incorporated into model-based decomposition to cure overestimation of the volume scattering contribution for interpretation of polarimetric synthetic aperture radar (PolSAR) data. The compensation is based on rotating the coherency matrix to minimize the cross-polarization term. However, this processing cannot always guarantee that the double- and odd-bounce scattering components will be rotated back to zero orientation angle and left with zero cross-polarization power. As a result, built-up patches with large orientation angles may still suffer from the scattering mechanism ambiguity. In this paper, double- and odd-bounce scattering models were generalized to fit the cross-polarization and off-diagonal terms, by separating their independent orientation angles. A general decomposition framework is proposed that utilizes all elements of a coherency matrix. The residual minimization criterion is used for model inversion. All the model parameters are simultaneously obtained using a nonlinear least squares optimization technique. The manual intervention, branch conditions, and negative power issues are avoided. The performance and advantages of this approach are demonstrated and evaluated with spaceborne L-band ALOS/PALSAR and airborne X-band Pi-SAR PolSAR data sets. Comparison studies are also carried out and demonstrate that further improved decomposition performance is achieved by the proposed method, especially in oriented built-up areas. [ABSTRACT FROM PUBLISHER]

Synthetic aperture radar (SAR) ship detection is an important application in the field of maritime security. Azimuth ambiguities caused by the aliasing of the Doppler phase history of each point are often visible in SAR images particularly in ocean areas of low wind speed condition, e.g., in coastal areas, in harbors, etc. The main sources of azimuth ambiguities are man-made metallic structures over the ocean, e.g., ships, oil platforms etc., and over land near the coast, e.g., big tanks, bridges' pylons etc., that have a high SAR backscatter responses. Although the ambiguities' backscatter is generally low, in many situations, it is above the surrounding ocean clutter and are mistaken by classic detection techniques, like constant false alarm rate, as real targets causing false positives. This paper addresses both the discrimination of real targets from non-trivial false positives, namely those due to azimuth ambiguities and the detection itself using a Generalized-K distribution approach. The methodology is firstly proposed and demonstrated over a significant data set of full polarimetric X-band SAR data, which have been acquired by the German satellite TerraSAR-X during the experimental dual receive antenna campaign in April and May 2010. It is based on the intrinsic configuration of monostatic two-channel PolSAR systems and relies on the different signature of azimuth ambiguities in cross-polarized channels. Automatic Identification System messages collected and collocated with the data set analyzed are used as ground truth to evaluate and validate the proposed methodology. [ABSTRACT FROM AUTHOR]

A new cloud dynamics and radiation database (CDRD) precipitation retrieval algorithm for satellite passive microwave (PMW) radiometer measurements has been developed. It represents a modification to and an improvement upon the conventional cloud radiation database (CRD) algorithms, which have always been prone to ambiguity. This part 2 paper of a series describes the methodology of the algorithm and the modeling verification analysis involved in creating a synthetic CDRD database for the Europe/Mediterranean basin region. This is followed by a proof-of-concept analysis, which demonstrates that the underlying CDRD theory based on use of meteorological parameters for reducing retrieval ambiguity is valid. This paper uses a regional/mesoscale model, applied in cloud resolving model (CRM) mode, to produce a large set of numerical simulations of precipitating storms and extended precipitating systems. The simulations are used for selection of millions of meteorological/microphysical vertical profiles within which surface rainfall is identified. For each of these profiles, top-of-atmosphere brightness temperature (TB) vectors are calculated (the vector dimension associated with the number of relevant cm–mm wavelengths and polarizations), based on an elaborate radiative-transfer equation (RTE) model system (RMS) coupled to the CRM. This entire body of simulation information is organized into the CDRD database, then used as a priori knowledge to guide a physical Bayesian retrieval algorithm in obtaining rainfall and associated precipitation parameters from the PMW satellite observations. We first prove the physical validity of our CRM-RMS simulations, by showing that the simulated TBs are in close agreement with observations. Agreement is demonstrated using dual-channel-frequency TB manifold sections, which quantify the degree of overlap between the simulated and observed TBs extracted from the full manifolds. Nevertheless, the salient result of this paper is a proof that the underlying CDRD theory is valid, found by combining subdivisions of the invoked meteorological parameter ranges of values and showing that such meteorological partitioning associates itself with distinct microphysical profiles. It is then shown that these profiles give rise to similar TB vectors, proving the existence of ambiguity in a CRD-type algorithm. Finally, we show that the CDRD methodology provides significant improvements in reducing retrieval ambiguity and retrieval error, especially for land surface backgrounds where contrasts are typically small between the rainfall TB signatures and surface emission signatures. [ABSTRACT FROM AUTHOR]

Ambiguity function (AF) provides an effective way for analysis of the resolving performance of a radar system. With the development of ultra-wideband (UWB) and multiple-input-multiple-output (MIMO) radio techniques, recently, the combination of them-the concept of UWB MIMO radar has been proposed and received much attention. For a UWB MIMO radar, first, the signal waveform with an exponential expression which is widely adopted in narrowband cases is not appropriate anymore. Second, the MIMO radar sensors are typically organized in a certain spatial topology, which greatly impacts the performance of the MIMO system. In addition, for a typical MIMO radar application scenario, generally, there are relative motions existing between the radar sensors and the targets. The presence of the relative motions would further complicate the performance analysis of the system. In fact, for a MIMO radar, the overall performance of the system is jointly determined by the parameters, such as the signal waveform, the topology, and the relative motions. Each of the parameters impacts the resolving performance in a particular way. In order to evaluate the contribution of each individual parameter of interest, in this paper, a UWB MIMO AF is developed and factorized into several factors. By this means, each individual parameter can be evaluated via the corresponding factor to examine a certain specific characteristic of the system, instead of via the complicated whole MIMO AFs. [ABSTRACT FROM PUBLISHER]

In this paper, a real-time algorithm that operates on data provided by a network of weather radars in the form of moments is presented. The algorithm implementation, performance, and abilities are presented and discussed. As part of this paper, a methodology for mapping from native spherical coordinates to a common network grid is developed and demonstrated. Metrics which gauge the quality of mapping and quality of data are derived, and their use from a network point of view is demonstrated. The main product of the algorithm, which is an implementation of a vector velocity estimation technique based on a maximum likelihood approach, is shown, and its results are displayed, compared, and discussed. The application of a methodology for velocity unfolding and reflectivity display enhancement is presented as well. [ABSTRACT FROM AUTHOR]

For along-track multichannel synthetic aperture radar, this paper proposes a novel ground moving target signal model in the high-resolution complex image domain. Based on the range-Doppler imaging of static scene, the 2-D complex response of an isolated rectilinearly moving target is derived via the stationary phase principle (SPP) approximations. It is shown that moving targets in complex domain can be divided into three types according to the 2-D motion distribution and the SPP approximation conditions. Different from the known peaklike response of a static target, different amplitude and phase modulations will appear for different types of moving targets. Moreover, a single target can be split into two targets in the image when its Doppler spectrum spreads over two ambiguous Doppler zones. All types of targets will have the same Doppler interferometric effect along multichannel images, which is decided by the target's ambiguous Doppler frequency. Furthermore, with the proposed signal model, the complex image properties can be completely described and analyzed. Finally, some numerical experiments are also provided to demonstrate the effectiveness of the proposed signal model and analysis. [ABSTRACT FROM AUTHOR]

In this paper, a vector velocity estimation approach based on the maximum likelihood technique operating on moment data within the overlapping area of a network of Doppler radars is presented. The relationships between the estimated vector velocity, the statistics of the measured signal, the characteristics of the observing geometry and volume, and the hardware and signal processing parameters are all derived. The most relevant error sources to the network measurements are derived and incorporated into the overall estimation process. The relationship between the measurement and estimation errors is identified, and exploited, so that estimation performance can be measured and, if necessary, improved through the means of error norm minimization. Techniques for mitigating errors in the synthesized reflectivity and velocity folding are presented as well. Results with error metrics are shown for several typical weather observation scenarios that include error sources and simulated data. Finally, it is shown how the technique may be used to provide useful information for the design and intercomparison of various Doppler radar network geometries. [ABSTRACT FROM AUTHOR]

It is well known that the motion of a target induces range migration, especially for high-resolution synthetic aperture radar (SAR) systems. Ground moving target imaging necessitates the correction of the unknown range migration. To finely refocus a moving target, one must accurately obtain the motion parameters for compensating the target trajectory. However, in practice, these parameters usually cannot be precisely estimated. This paper proposes a new imaging approach for ground moving targets without a priori knowledge of their motion parameters. In the devised method, the azimuth compression function is constructed in range frequency domain, which can eliminate the coupling effect between range and azimuth. Theoretical analysis confirms that the methodology can precisely focus targets without interpolation procedure. The effectiveness of the proposed imaging technique is demonstrated by both simulated and real airborne SAR data. [ABSTRACT FROM AUTHOR]

In this paper, we propose a least-squares-based method for multitemporal synthetic aperture radar interferometry that allows one to estimate deformations without the need of phase unwrapping. The method utilizes a series of multimaster wrapped differential interferograms with short baselines and focuses on arcs at which there are no phase ambiguities. An outlier detector is used to identify and remove the arcs with phase ambiguities, and a pseudoinverse of the variance–covariance matrix is used as the weight matrix of the correlated observations. The deformation rates at coherent points are estimated with a least squares model constrained by reference points. The proposed approach is verified with a set of simulated data. [ABSTRACT FROM AUTHOR]

This paper describes an ambiguity resolving approach for slant-range velocity estimation which utilizes the wideband characteristic of the transmitted signal (multiple wavelengths). Based on the wavelength dual-wavelength radar data. Then, two effective approaches are introduced to focus the moving target no matter the Doppler ambiguity exists or not. The slant-range velocity is estimated by the number of azimuth cell displacements between the two focused images. Both imaging methods have different properties and advantages. A performance analysis is made, and deleterious factors in practice are analyzed in detail. The effectiveness of the unambiguous slant-range velocity estimation approach is demonstrated with the use of simulated and real data. [ABSTRACT FROM AUTHOR]

Based on a parametric model and some optimum methods, it has been previously proved that parametric velocity synthetic aperture radar (VSAR) may improve the performances of moving target detection and parameter estimation simultaneously. In this paper, multilook processing is studied for parametric VSAR. At first, statistical signal models are established for azimuth multilook processing (AMLP) and range multilook processing (RMLP), respectively. By combining the multiple AMLP sublook pixel vectors, it is shown that the clutter parameter estimation accuracy can be further improved via the maximum- likelihood estimation methods. Meanwhile, based on the adaptive implementation for the optimum processing of VSAR, RMLP can be used to improve slowly moving target detection performance via the noncoherent integration of multiple range sublooks. Furthermore, it is shown that the Doppler frequencies of moving targets vary linearly with different range sublooks due to the different carrier frequencies of sublooks. Therefore, based on a proposed novel two-step multilook diversity (TS-MLD) estimator for RMLP, the "azimuth location ambiguity" of VSAR can be well resolved via least squares linear regression, without configuration change of the conventional VSAR. Also, the estimation accuracy of target's unambiguous Doppler frequency, as well as target's azimuth location, is derived for the proposed TS-MLD method. Finally, numerical experiments and scene simulations are provided to demonstrate the effectiveness of the proposed multilook-based methods. [ABSTRACT FROM AUTHOR]

Recent analysis of a polarimetric synthetic aperture radar (PolSAR) velocity experiment has shown that azimuth ambiguities can provide useful information for the detection of moving targets with an across-track velocity component in PolSAR images using cross-polarization clutter cancellation. This paper examines this phenomenon using theoretical analysis and simulations and illustrates its application with experimental results. It is shown that, for reciprocal scatterers, the phase difference between HV and VH images is zero, whereas for HV and VH ambiguities, the phase difference is π. For land applications, clutter cancellation is essential for the detection of moving targets in PolSAR images. For maritime applications, it can be used to distinguish images from ambiguities. However, it is important to note that the underlying physical reasons for the performance of clutter cancellation are entirely different from ground moving target indication along-track interferometric SAR. It is also shown that cross-pol clutter cancellation is related to filtering of a double-rate-sampled single-channel SAR signal. [ABSTRACT FROM AUTHOR]