Synthetic Aperture Radar Geometry Research Articles

Ultra-High-Resolution Spaceborne and Squint SAR Imaging for Height-Variant Geometry Using Polynomial Range Model

In this article, we propose an entire processing chain that addresses the geometrical defocusing problems caused by a large orbital arc, a high squint, and topography variations in ultra-high-resolution (UHR) synthetic aperture radar (SAR) operations. Slant-range histories are formulated using fifth-order polynomials to accurately express radar signals with a UHR spaceborne and squint SAR geometry. SAR focusing is first conducted with a constant height assumption. Thereafter, residual topography errors are compensated. Several beneficial contributions are included in the proposed processing chain. First, to achieve constant-height SAR focusing, we improve the typical least-square decomposition-based Stolt interpolations in terms of the image quality and computation time. Second, we clarify how illuminated areas are mapped in a two-dimensional imaging domain after polynomial-based focusing, which is completely different from the well-known relationship between the closest range and zero-Doppler time. Third, a generalized blockwise postfocusing method is devised to correct the range and azimuth defocusing effects induced by height variations. These contributions are verified using numerical simulations. Thus, we can conclude that the proposed method can provide focused SAR images for a height-variant geometry in UHR spaceborne and squint operations.

Multi-Electromagnetic Jamming Countermeasure for Airborne SAR Based on Maximum SNR Blind Source Separation

Synthetic aperture radar (SAR) may be attacked by multifarious kinds of the active-jamming, which will lead to the ineffectiveness of SAR in complex electromagnetic environment. In this paper, a novel multi-electromagnetic jamming counter-measure for the airborne SAR is proposed based on maximum signal-to-noise ratio (SNR) blind source separation. Firstly, the imaging geometry and multi-component mixed signal model of airborne SAR are established. Then, based on multi-component mixed signal matrix, a blind source separation (BSS) method based on the maximum SNR is proposed to separate the real target echo signal from the multi-electromagnetic jamming signals. After real target echo signal identification, the high resolution images of the interested target area can be achieved by the corresponding SAR imaging method. The simulated and measured data results are present to prove the feasibility and effectiveness of the proposed method.

An Efficient Full-Aperture Approach for Airborne Spotlight SAR Data Processing Based on Time-Domain Dealiasing

The two-step approach (TSA) is an efficient full-aperture method to solve the Doppler spectrum aliasing when processing data acquired by a synthetic aperture radar (SAR) system operating in beam steering mode. This simple approach solves the spectral aliasing by implementing an azimuth convolution between the raw data and a chirp signal, thus avoiding complex subaperture division and recombination of subaperture approaches. However, as aliasing reoccurs in the slow time-domain after the convolution, the estimation and compensation for residual motion error by autofocus cannot be performed immediately, which is crucial for airborne and high-resolution spaceborne SAR processing. The extended TSA solves this problem by implementing full-aperture azimuth scaling, but it is inefficient when the scaling factor deviates from unity severely, which is common in the data acquisition geometry of an airborne SAR. Aiming at addressing the existing shortcomings, this article combines the TSA with autofocus by the time-domain dealiasing and provides an efficient full-aperture processing framework of airborne spotlight SAR data. Simulated and experimental airborne spotlight SAR data with the transmission signal bandwidth of 1.2 GHz and a coherent integration angle of 15<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> are processed by the proposed algorithm and the clarity of the processed results shows its effectiveness.

System Concepts and Potential Applications of a Tri-Beam Spaceborne SAR Mission

Multitemporal synthetic aperture radar interferometry (MT-InSAR), capable of detecting both surface deformation and elevation with high precision, is used for many applications in earth observation. Conventional synthetic aperture radar (SAR) missions with a single beam only detect deformation along the line of sight (LOS) and relative elevation due to the undetermined model of phase wrapping. In a multisatellite SAR mission, measurements from different SAR geometry improve the sensitivity of the detectable deformation, especially to the deformation along the north–south (N-S) direction. However, it is difficult to combine the measurements from varying viewing angles since the absolute phase cannot be reconstructed without a ground control point. In this article, a tri-beam SAR system is introduced to detect 3-D deformation and derive multiview 3-D surface model from a single spaceborne platform. The accuracy of the 3-D deformation from the tri-beam SAR is exploited with varying squint and incident angles to obtain the optimal parameters of the three beams. Then a multidimensional coherent scattering model is used to simulate the multitemporal SAR data with different viewing angles. Regarding the tri-beam SAR, potential applications in earth observation including 3-D deformation monitoring, geodetic stereo SAR, and multiview 3-D forest reconstruction are investigated subsequently. The results of this study indicate that the tri-beam SAR is able to measure 3-D deformation and reconstruct 3-D surface model without ground control point.

On Autonomous Reconfiguration of SAR Satellite Formation Flight With Continuous Control

Satellites clusters for Earth observation purposes entail precise orbit monitoring and control to satisfy application needs efficiently. Fast technological progress in GNSS receivers, intersatellite communications/vision links, and propulsion technologies have inspired and fostered autonomous orbit determination and control techniques, allowing more efficient ground segment operations. Moreover, new distributed satellite missions have been enabled by autonomous formation flying, with unprecedented Earth observation potential. These missions may adopt varying observational modes associated with different relative orbital configurations and also transit among these modes as required by mission control. In this article, we consider a hypothetic distributed synthetic aperture radar (SAR) mission with a main SAR illuminator, as CONAE's SAOCOM 1 satellites, and one or more companions able to adopt different bistatic SAR geometries, enabling interferometry, tomography, or specular acquisition. To approach this problem, we formulate a basic task for any actively controlled companion satellite (deputy satellite) consisting of following a reference maneuver relative to the chief satellite orbit. This task is performed by means of a feedback control law based on newly introduced relative orbital elements (ROEs) and suitable to continuous actuators (e.g., electric propulsion) with bounded thrust. As a main result, we prove the asymptotic stability of the maneuver orbit tracking task for low Earth, nonequatorial, and near-circular chief orbits. This required a reformulation of the relative orbit tracking problem and the associated ROEs. A control allocation along the orbit is also proposed to reduce the propellant consumption and the transient time between SAR modes. The theoretical results are validated with simulated controlled transitions between different acquisition modes.

A modified design method of pulse repetition frequency for synthetic aperture radar system based on the single point equivalent squint model

Pulse repetition frequency (PRF) is an essential parameter in synthetic aperture radar (SAR). However, a small PRF value will cause spectrum ambiguity and a large value will increase the computational complexity. In highly squinted SAR imaging with maneuvering platform, the traditional PRF design methods used are airborne and space borne. SAR systems perform with a low precision because of the complex geometric configuration and system deviations. In order to adapt to the maneuvering platform SAR system, a modified design method of PRF is proposed in this paper. First, the azimuth spectrum of echoes is analyzed by establishing the SAR geometry base on the single point equivalent squint (SPES) model. Subsequently, the calculation of azimuth bandwidth is transformed into an optimization problem, and the lower limit of PRF is obtained by the Golden Section Method. Besides, the criteria of spectrum unambiguity and time sequence constraints in PRF design is also discussed in detail. Simulation experiments demonstrate the feasibility and accuracy of the proposed method.

Endfire Synthetic Aperture Radar for a Cryobot for Exploration of Icy Moons and Terrestrial Glaciers

An endfire synthetic aperture radar (SAR) for use on a cylindrical ice-penetrating cryobot is presented. The SAR facilitates obstacle detection and mapping inside ice for subsurface exploration using such a cryobot vehicle. The SAR is comprised of four azimuthally arranged directional log periodic antenna elements flush-mounted onto the cryobot’s surface. Aperture synthesis is facilitated by the downward trajectory of the cryobot as it slowly melts through ice. The radar front end and back end are designed using commercial-off-the-shelf (COTS) components and a customized field-programmable gate array (FPGA)-based digital design for signal generation, reception, and processing. Theoretical analysis of the SAR geometry is presented for the case of a point target in which the maximum likelihood estimation (MLE) approach is used for position estimator development. The novelty of this system lies in the use of pairs of antennas, with fixed baselines between them, to implement multiple coherent monostatic SARs to estimate target position in three dimensions. Specifically, range estimation is implemented by conventional chirp processing, polar (or elevation) angle estimation is achieved by SAR processing, and azimuth angle estimation is facilitated using pairs of four azimuthally arranged antennas that can be analyzed as multiple fixed baseline interferometric radars. Radar signal coherency tests and experimental validation of point target estimation and spatial resolution performed in a laboratory environment using the endfire SAR are presented in this study.

Potential performance of polarimetric reference function of SAR data processing by coherent target decomposition

Significant employment of polarimetric synthetic aperture radar (SAR) is the classification of the Earth’s surface, which includes several processing algorithms, labelling, and representation options. This paper investigated the potential performance of the polarimetric reference function in SAR data processing to apply in coherent decomposition. The proposed methodology employed the simulated radar cross section of dihedral and trihedral corner reflector under a SAR geometry using physical optics (PO) and geometrical optics (GO) to produce the polarimetric reference function for azimuth compression in the processing of SAR data. The Pauli and the Krogager decompositions processed the compressed SAR data to investigate the effect and performance of the polarimetric reference function. The colour clustering results based on k-mean clustering algorithm could deliver more related scattering characteristic. The image pixel classification was strongly associated with the polarimetric reference function in processing step. These findings indicated that the obtained decomposition and clustering results could provide a better performance in visual impact and quantitative evaluation according to the decomposition term, as well as its physical interpretation.

Precise Topographic Model Assisted Slope Displacement Retrieval from Small Baseline Subsets Results: Case Study over a High and Steep Mining Slope.

Due to the intrinsic side-looking geometry of synthetic aperture radar (SAR), time series interferometric SAR is only able to monitor displacements in line-of-sight (LOS) direction, which limits the accuracy of displacement measurement in landslide monitoring. This is because the LOS displacement is only a three dimensional projection of real displacement of a certain ground object. Targeting at this problem, a precise digital elevation model (DEM) assisted slope displacement retrieval method is proposed and applied to a case study over the high and steep slope of the Dagushan open pit mine. In the case study, the precise DEM generated by laser scanning is first used to minimize topographic residuals in small baseline subsets analysis. Then, the LOS displacements are converted to slope direction with assistance of the precise DEM. By comparing with ground measurements, relative root mean square errors (RMSE) of the estimated slope displacements reach approximately 12–13% for the ascending orbit, and 5.4–9.2% for the descending orbit in our study area. In order to validate the experimental results, comparison with microseism monitoring results is also conducted. Moreover, both results have found that the largest slope displacements occur on the slope part, with elevations varying from −138 m to −210 m, which corresponds to the landslide area. Moreover, there is a certain correlation with precipitation, as revealed by the displacement time series. The outcome of this article shows that rock mass structure, lithology, and precipitation are main factors affecting the stability of high and steep mining slopes.

Feasibility Study and Conceptual Design of Missile-Borne Synthetic Aperture Radar

In this paper, feasibility study along with conceptual design of missile-borne synthetic aperture radar (SAR) has been accomplished, which can effectively improve the detection capability and the blow precision of a missile. First, SAR echo signal modeling, geometry configuration for missile-borne SAR scenario, and an appropriate image formation algorithm are presented. Then, a system block diagram along with complete discussions about different parts and system design considerations of the SAR seeker are explained. Finally, simulation of the whole system along with raw data generation considering the imaging geometry of the missile-borne SAR seeker has been performed. Experimental results show that the proposed system is capable of imaging and targeting in the complicated geometry of missile-borne SAR.

High-Resolution Wide-Swath SIMO and MIMO SAR Imaging Using Short-Term Shift Orthogonal Code

Conventional single antenna synthetic aperture radar (SAR) has a conflict between wide imaging swath width and fine cross-range resolution. Single input multiple output (SIMO) and multiple input multiple output (MIMO) radars are the two methods to overcome this limitation. In order to separate the signals of MIMO radar, the codes are expected to be orthogonal for all delays. This is impossible in SAR. Due to the special imaging geometry of SAR, short-term shift orthogonal (STSO) codes were proposed to be used in MIMO SAR. This letter compares the SIMO SAR structure and MIMO SAR structure using STSO codes. We draw a conclusion that the number of receivers of MIMO structure is less than that of SIMO structure.

Terahertz Bistatic Synthetic Aperture Radar for 1-D Near-Field High-Resolution Imaging

Considering the difficult transceiver-isolation problem of the monostatic synthetic aperture radar (SAR) in the terahertz (THz) band, this paper proposes a compact THz bistatic SAR (BiSAR) geometry. The system allows the separately distributed transmitter and receivers. At the receiving end, there are a direct-wave receiver and an echo receiver, both operating at the heterodyne and in-phase mode. The echo receiver runs along a linear rail to fulfill the scene scanning, while the direct-wave one is fixed as a reference. Furthermore, assuming that the receivers are synchronized, both the problem of synchronization between the separated transmitter and receivers and the problem of timing at the signal acquisition would be solved by utilizing the high coherence between the echo and the direct wave. Based on such a system, the application of THz BiSAR for one-dimensional imaging is taken into consideration. Then, a high-resolution imaging algorithm is proposed benefitting from the total least squares estimating signal parameters via rotational invariance techniques (TLS-ESPRIT) and the spatial smoothing process (SSP). The imaging performance is then demonstrated by both simulations and the experiments in the 0.183 THz.

Nadir Echo Removal in Synthetic Aperture Radar via Waveform Diversity and Dual-Focus Postprocessing

Synthetic aperture radar (SAR) remote sensing allows high-resolution imaging independent of weather conditions and sunlight illumination and is, therefore, very attractive for the systematic observation of dynamic processes on the earth’s surface. However, as a consequence of the pulsed operation and side-looking geometry of SAR, nadir echoes may significantly affect the SAR image quality, if the pulse repetition frequency is not conveniently constrained in the design of the SAR system. As the nadir interference constraint typically limits both the swath width and the ambiguity performance of the SAR system, the investigation of novel concepts for nadir echo removal is of great interest. This letter describes how to design an SAR system without the nadir interference constraint and how to remove (not only smear) the nadir echoes by means of waveform diversity on transmit and appropriate postprocessing. The proposed technique yields improved image quality and can be exploited in a similar manner for range ambiguity suppression with remarkable benefits for the design of novel SAR systems.

On Signal Modeling of Moon-Based Synthetic Aperture Radar (SAR) Imaging of Earth

The Moon-based Synthetic Aperture Radar (Moon-Based SAR), using the Moon as a platform, has a great potential to offer global-scale coverage of the earth’s surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the “stop-and-go” assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of ‘stop-and-go’ assumption are first estimated, and then characteristics of Moon-Based SAR imaging’s azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D) spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing.

Bistatic Synthetic Aperture Radar With Undersampling for Terahertz 2-D Near-Field Imaging

To avoid the difficult transceiver-isolation problem of a monostatic synthetic aperture radar (SAR) for terahertz (THz) near-field azimuth-range imaging, a compact bistatic SAR geometry is demonstrated in this paper. The system consists of one fixed transmitter, one moving echo receiver and one fixed direct-wave receiver. The transmitter emits wideband signals for range resolution, and the echo receiver moves along a designed trajectory for the cross-range resolution, and the direct-wave receiver is taken as a reference for synchronization. Since the wavelength of THz is in the order of millimeter or submillimeter, the requirement on subwavelength interval of spatial sampling by the Nyquist theory aggravates the measurement difficulty. To break this limitation, a compressed sensing-based imaging algorithm is presented. Allowing the undersampling both in spatial domain and frequency domain, the proposed algorithm can provide high-resolution performance with few measurements. Thus, the balance between the resolution and the amount of measurements can be made. The system geometry and imaging performance are then demonstrated by both the simulations and the experiments in the 0.178–0.188 THz band.

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine–based data fusion system

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

Fusing Meter-Resolution 4-D InSAR Point Clouds and Optical Images for Semantic Urban Infrastructure Monitoring

Using synthetic aperture radar (SAR) interferometry to monitor long-term millimeter-level deformation of urban infrastructures, such as individual buildings and bridges, is an emerging and important field in remote sensing. In the state-of-the-art methods, deformation parameters are retrieved and monitored on a pixel basis solely in the SAR image domain. However, the inevitable side-looking imaging geometry of SAR results in undesired occlusion and layover in urban area, rendering the current method less competent for a semantic-level monitoring of different urban infrastructures. This paper presents a framework of a semantic-level deformation monitoring by linking the precise deformation estimates of SAR interferometry and the semantic classification labels of optical images via a 3-D geometric fusion and semantic texturing. The proposed approach provides the first “SARptical” point cloud of an urban area, which is the SAR tomography point cloud textured with attributes from optical images. This opens a new perspective of InSAR deformation monitoring. Interesting examples on bridge and railway monitoring are demonstrated.

Nonlinear Model for InSAR Baseline Error

Synthetic aperture radar (SAR) interferometric baseline parameters form important input for SAR interferometry. In this paper, a nonlinear error model is established for the SAR interferometric baseline and parameterized as a polynomial based on the natural nonlinearity of the orbit of a satellite. Unlike conventional models, the proposed model takes into account the nonlinear part of the baseline error. A theoretical derivation is performed based on the imaging geometry of interferometric SAR, and the results of the analysis show that the parameters of the nonlinear baseline error model can be obtained from the relationship between the orbit, the nominal baseline, the baseline error, and the residual interferogram phase. A sample data set from the Japanese Earth Resources Satellite-1 (JERS-1) L-band SAR is used to validate the proposed model, and the results indicated that the compensation of the residual interferogram phase of the test data is superior to that provided by conventional models.

Vector-based approach for combining ascending and descending persistent scatterers interferometric point measurements

The combination of ascending and descending persistent scatterers interferometric (PSI) data by means of resampling and/or spatial interpolation, separately for each synthetic aperture radar geometry, is a commonly followed procedure, limited though by the reduced spatial coverage and the introduced uncertainties from multiple rasterization steps. Herein, an alternative approach is proposed for combining different PSI line-of-sight observables in the vector domain, based on the geographic proximity of PS point targets. In the proposed nearest neighbour vector approach all necessary analysis steps are performed by means of attributes transfer and calculations between features geodatabases, prior to any rasterization. By increasing the number of input point vectors during subsequent interpolation, the overall error budget coming from spatial interpolation is being reduced. The advantages of the proposed vector-based approach compared to the commonly used grid-based procedure are being demonstrated using real data.