Estimating the 3D alignment of migratory insects is essential for understanding their 3D directional behavior. The existing approach reconstructs 3D alignment using azimuthal angle measurements from dual-view entomological radars. However, the measurement errors often propagate into the reconstructed 3D alignment, causing significant inaccuracies, especially under low signal-to-noise ratio conditions. To overcome this problem, this letter proposes a new method based on a multi-view, multi-frequency, and full-polarization entomological radar system. The method directly estimates insect 3D alignment by integrating polarization scattering matrices (SMs) from multiple views and frequencies, leveraging the assumption of scattering symmetry in insect bodies. For symmetric targets, the off-diagonal SM elements vanish when the polarization direction aligns with the symmetry plane. Based on this theory, an optimization problem is formulated to estimate 3D alignment by minimizing the sum of the powers of off-diagonal elements across multi-view and multi-frequency SMs. Both simulations and field experiments demonstrate that the proposed method achieves substantially higher accuracy than the traditional method.

Miniaturized and lightweight unmanned aerial vehicles (UAV) provide a flexible platform for synthetic aperture radar (SAR). The application of UAV interferometric SAR (InSAR) is gradually increasing in interferometric measurement fields. Leveraging the P-band signal and the capability to penetrate leaf clusters, these UAV InSAR systems demonstrate significant potential for topographic mapping and deformation monitoring, even in challenging surface conditions. This paper introduces the primary challenges associated with UAV InSAR, with a specific focus on analyzing the coherence of UAV InSAR. Additionally, we present interferometric measurement results obtained by our self-developed P-band UAV InSAR system and the processing flow we proposed. These results effectively address key challenges and validate the feasibility of the system for repeat pass interferometric measurements.

Interferometric synthetic aperture radar (InSAR) has been a valuable tool for mapping topography and subtle deformations. However, dealing with a wide imaging integral angle (IIA), especially for low-frequency band unmanned aerial vehicle (UAV) InSAR systems, introduces challenges. The conventional interferometric phase model depends on the difference in two slant ranges between the synthetic aperture centers and the target in two observations. Accuracy limitations emerge when variations are encountered in differences of slant range history across the entire wide IIA. This article explores the impact of IIA on interferometric measurements and proposes a modified interferometric phase model to address these limitations. For a wide IIA, the proposed model focuses on the integral of differences in slant range history throughout IIA by considering the nonlinear trajectory of the UAV platform. Additionally, measurement models for the IIA are deduced, in which an additional scale factor expanded by the Bessel function is introduced. Simulated and experimental datasets are utilized to demonstrate improvements in the accuracy of topography and deformation measurements. These results validate the effectiveness of the modified model in overcoming the challenges posed by wide IIAs in UAV InSAR systems.

Radar echo signals may experience the significant 2-D space dependence when it comes to the nonlinear trajectory of the synthetic aperture radar (SAR). The backprojection (BP) imaging algorithm is generally effective for achieving satisfactory focused SAR images under this condition. However, the conventional BP algorithm usually selects a uniform reference imaging plane, regardless of the actual topography of the observation scene. In undulating topographies, it has been proved that the range migration of the actual target and its projection point on the reference imaging plane may not remain consistent, leading to residual uncompensated phase errors and resulting in imaging defocusing during nonlinear trajectories. To address this problem, this article proposes an improved imaging method that involves the optimal topographic imaging plane reconstruction based on the image quality evaluation. The coarse plane and subsequent partitioned subplanes are sequentially constructed to create a topographic imaging plane that closely resembles the digital elevation model (DEM). The BP imaging algorithm is then applied to the reconstructed topographic imaging plane to overcome the defocusing problem. Both simulated and actual experiment datasets validate the effectiveness of the proposed method. Moreover, the proposed method significantly alleviates registration difficulties.

As an essential component of interferometric synthetic aperture radar (InSAR) measurements, phase unwrapping (PU) is a critical process that significantly impacts the accuracy and reliability of topography and deformation measurements. As an effective approach that can overcome the limitations of the Itoh condition, the multi baseline (MB) PU method is widely used in PU; however, when it comes to unmanned aerial vehicles (UAVs) InSAR systems that use a single antenna and repeat-pass mode for interferometric measurements, the time-varying baseline can pose a challenge since the airflow disturbance can prevent the repeat flight paths from remaining parallel. This makes the combination of baselines more complicated, which can impede the feasibility of using the MB PU for the UAV InSAR. As a result, using the relationship between different frequencies for PU is a promising alternative method. This article demonstrates that the frequency ratio design is a crucial factor in the success of the multifrequency (MF) PU method. An optimal frequency ratio design method for MF PU that maximizes the minimum Euclidean distance between the intersection vectors determined by the integer ambiguity vectors is proposed. The proposed method is validated using the simulated and experimental datasets, which provide evidence that PU accuracy can be greatly enhanced with the optimal frequency ratio.

Ground-based multiple-input multiple-output (GB-MIMO) radar is capable of performing structural health monitoring through vibration monitoring. However, when a target’s vibration frequency is comparable to the image acquisition frequency of MIMO radar, its vibration can affect the vibration parameters estimation based on the pixel’s phase series. In this letter, the impact of target vibration on the pixel series is analyzed. A robust method for vibration parameter estimation is proposed by operating iteration between the series compensation and estimation. The correctness and effectiveness of proposed method is verified by both simulation and calibrator experiments.

Time-series interferograms acquired on a deep pit with a Ground-Based Synthetic Aperture Radar (GB-SAR) system showed that the atmospheric phase (AP) could be complexly space variant due to rapid changes of the weather conditions and steep topography. Conventional compensation methods that simulate the AP with typical parametrical models are no longer applicable. Based on the theoretical path integral model of the AP, a grid partition (GP) method is proposed. By dividing one interferogram into a certain number of small grids, the refraction variation inside each grid is assumed to be a constant. A system of linear equations is first built based on sufficient permanent scatterers (PSs). Then, bounds and inequality constraints are set to limit the refraction variation of each grid. A constrained linear least-square problem is solved with two-step process to estimate and compensate the AP. To fully validate the feasibility of the GP method, simulated phase interferograms based on four conventional AP models and with the consideration of deformation areas and noise phase are first processed. Then, four experimental interferograms with different types of AP components are processed and made comparisons with the conventional parametrical methods. The quantitative comparisons of the simulated and experimental data sets both proved that the GP method can well reduce the AP errors.

Linear-array multiple-input–multiple-output (LA-MIMO) synthetic aperture radar (SAR) can obtain 3-D radar images by only one pass. However, it is sensitive to time-variant measurement errors of curved track and time-variant attitude angles, meaning that autofocus processing for the LA-MIMO SAR tomography is necessary. The existing autofocus methods cannot be used to estimate thetime-variantand3-D space-variantmotion errors (3-D SVME) of the LA-MIMO SAR. To solve this problem, a new autofocus approach based on multiple local autofocusing and the LA-MIMO SAR time-variant motion error estimation is proposed. First, the local motion error estimation based on the fast local spectral analysis (SPECAN) 3-D imaging and the maximum contrast optimization 2-D local autofocusing is performed to estimate the local time-variant motion errors. Then, based on the linear-array motion error model, the time-variant 3-D trajectory deviations of the array center and attitude angles are estimated by the weighted least square estimation (WLSE) to solve the 3-D SVMEs. Last, the 3-D fast factorized backprojection (FFBP) is performed to obtain the well-focused 3-D image of the whole beam. The proposed approach has been applied for the tomography of a new crawler-type unmanned-ground-vehicle (UGV) LA-MIMO SAR. Both the simulation and real data experiments verify the effectiveness of the proposed approach.

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

A long aperture time is required to achieve a high signal-to-noise ratio and high azimuth resolution in geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR) system for moving target indication (MTI). The range walk migration because of the target's motion cannot be ignored for such a long time, and the second-order range model fails for the moving target. In this paper, an adaptive MTI method is proposed for GEO SA-BSAR with a long aperture time, ensuring the moving target's detection and location. Firstly, an adaptive spatial filter modified by the accurate GEO SA-BSAR multichannel signal model is applied to clutter suppression and beamforming. Next, we adopt the generalized Radon-Fourier transform to maximize the signal-to-noise ratio of the moving target with unknown motion parameters. Then, the moving target can be detected, and its position has been obtained. Finally, the simulation experiments are conducted to show the effectiveness of our technique.

An experiment which involves the simultaneous deployment of three ground-based multiple-input multiple-output (GB-MIMO) radar systems to measure 3-D deformation of a displaceable corner reflector (DCR) is outlined in this letter. The DCR successively displaces in three mutually orthogonal directions and each radar measures 1-D deformation independently. Since the displacement directions of the DCR cannot be measured, they are estimated by solving a nonlinear equation set based on the rotation relationship between two 3-D coordinate systems, whose effectiveness is verified by simulation. Considering that the measurement accuracies of the DCR’s displacements along three axial directions of a 3-D coordinate system, that is, 3-D deformation, are related with how the coordinate system is built, the geometric dilution of precision (GDOP) is then utilized to take accuracy analysis. The measured and theoretical GDOP are rather close, which validates the feasibility of 3-D deformation measurement with three radar systems.

Coherence-based synthetic aperture radar (SAR) tomography (TomoSAR) exploits the complex coherences of SAR images to achieve 3-D imaging. Utilizing two-sensor spaceborne SAR formation flying to realize coherence-based TomoSAR has attracted increasing attention because temporal decorrelation-free interferograms can be constructed; therefore, TomoSAR has excellent potential for inverting the vertical structures of natural scenes such as forests and glaciers. However, low earth orbit (LEO) TomoSAR is disadvantaged by limited data and nonuniform sampling in the elevation direction. Geosynchronous (GEO) TomoSAR can overcome these limitations owing to its short revisit time of no more than 24 h. For the first time, this article discusses coherence-based TomoSAR exploiting GEO SAR formation flying. The benefits of GEO-formation coherence-based TomoSAR, including the low cost of slave satellites, rich data sets, and uniform sampling, are noted. The key problems of system design, including the formation design and data acquisition, are discussed. A formation design method based on the minimum along-track baseline is proposed that can realize uniform elevation sampling. The geometric correlation of a general SAR observation geometry is derived; on this basis, an optimal data acquisition method based on the optimal height measurement Cramer-Rao lower bound (CRLB) is proposed. Finally, the performance of GEO-formation coherence-based TomoSAR is analyzed; in particular, the ambiguity height in the altitude direction, the Rayleigh resolution in the altitude direction, and the theoretical optimal geometric correlation are evaluated. Finally, computer simulations validate the proposed formation design method, data acquisition scheme, and performance analysis formula.

Traditional SAR imaging methods are based on point target scattering model, hence are not capable of recovering the shapes of distributed targets such as cylinders. The cylinder target is usually shown as two endpoints in the traditional single-angle SAR images. However, the distributed SAR can provide multi-angle observation information of the cylinder target. To improve the SAR image quality, we propose a distributed SAR imaging method for the cylinder target with a sparse distributed SAR configuration. The proposed method reconstructs the cylinder target by estimating the parameters from the SAR image, and then identity the cylinder target from the distributed SAR echo. When positive decision is made, the shape of the cylinder target can be recovered with these parameters. Numerical simulations have been conducted to demonstrate the effectiveness of the proposed method.

The passive Synthetic Aperture Radar with Global Navigation Satellite System (GNSS) employs GNSS satellites as transmitters and receivers mounted near the ground. Since GNSS constellations are designed for global, reliable and persistent operation, the most important advantage of such a system is the potential of permanent monitoring on the area which is overlooked by a fixed receiver. In the paper, an experimental prototype of GNSS-based SAR for the purpose of obtaining larger scene images as well as the development progress was introduced at the first place. And then a latest imaging experiment of GNSS-Based SAR for railway bridge was carried out and the image was obtained with high quality when it was firstly used for China Railway High-Speed (CRH) railway bridge imaging. The positive imaging result suggested that it is possible to achieve change information extraction using GNSS-based SAR for the further safety evaluation of CRH operation in China.

Ground-based synthetic aperture radar (GB-SAR) technique has been widely applied for the deformation monitoring and measurement of the natural and engineered slopes. To extend the 2-D deformation measurement from the conventional 1-D measurement along the radar-target line of sight (LOS), multiple aperture interferometry (MAI) techniques based on phase differences between interferograms of the forward-looking and backward-looking subapertures are tackled in this letter. The optimal subaperture selection is analyzed considering the typical signal-to-noise ratios and correlations in GB-SAR applications. Simulations prove that the coherent integration (CIM) can be utilized to improve the measurement accuracy of the MAI method. Besides, GB-SAR experiments are carried out to validate the feasibility and effectiveness of the 2-D deformation measurement method based on MAI. Accuracy comparison of deformation measurement with the MAI and cross correlation methods is also taken. Experimental results show that the accuracy of deformation measurement along the perpendicular direction to LOS based on MAI and CIM can reach millimeter level for displaceable corner reflector.

The detection of a power transmission tower in a synthetic aperture radar (SAR) image has been widely studied. However, few works consider the geometric features of the power transmission tower. In a high-resolution SAR image, the geometric features of the power transmission tower are more obvious and can be used to further reduce the false-alarm probability. In this letter, a new power transmission tower detection method is proposed, which takes into account the geometric features of the target and obtains lower false-alarm probability than the traditional methods. First, the polar coordinate semivariogram is proposed, which has the advantages of low computational complexity and high sensitivity to the shape of the targets. Then, a three-layer neural network is employed to detect the power transmission tower, taking the geometric features as the input vector. Finally, the validity of the proposed method is illuminated by the experimental measurement results of the airborne data with 0.5-m resolution.

The ionospheric scintillation induced by local ionospheric plasma anomalies could lead to significant degradation for geosynchronous earth orbit synthetic aperture radar (SAR) imaging. As radar signals pass through the ionosphere with locally variational plasma density, the signal amplitude and phase fluctuations are induced, which principally affect the azimuthal pulse response function. In this paper, the compensation of signal amplitude and phase fluctuations is studied. First, space-variance problem of scintillation is addressed by image segmentation. Then, SPECAN imaging algorithm is adopted for each image segment, because it is computationally efficient for small imaging scene. Furthermore, an iterative algorithm based on entropy minimum is derived to jointly compensate the signal amplitude and phase fluctuations. Finally, a real SAR scene simulation is used to validate our proposed method, where both the simulated scintillation using phase screen technique and the real GPS-derived scintillation data are adopted to degrade the imaging quality.

Low signal power density limits the performance of space-surface bistatic synthetic aperture radar (SS-BiSAR) using Global Navigation Satellite System (GNSS) satellites as illuminators. To tackle this problem, in this letter, a novel bistatic SAR image enhancement technique based on repeat-pass coherent fusion is proposed. The works in this letter include three aspects. First, repeat-pass experiments are designed to ensure the best resolution. Second, a modified CLEAN technique is applied to remove the direct signal interference from the focused BiSAR images. Third, a coherence-processing method is proposed to implement coherence of each repeat-pass BiSAR image and then they are coherently fused to obtain a quality-improved BiSAR image. Twenty-two days of repeat-pass BiSAR experiments with Beidou-2/Compass-2 inclined geosynchronous orbit satellites as illuminators have been designed and conducted. The data were processed by the proposed method. The results show that the method can obtain better image quality compared with the traditional noncoherent fusion method and the single-day imaging result, which validates the proposed method and proves the huge potential in realizing local area monitoring with SS-BiSAR using GNSS satellites as illuminators.

One of the GEO SAR's characteristics of long integration time guarantees its fine resolution. But on the contrary, the ultra-long time boosts the multiple influences and then affects the focusing severely. In this paper, a validation experiment is presented to verify the feasibility of GEO SAR imaging under the condition of long integration time of around several hundred or even thousands of seconds. The experiment employs the Chinese Beidou IGSO navigation satellites as the illuminator of opportunity. The receiver is deployed on the top of a building and then a space-surface Bistatic SAR (SS-BISAR) configuration is constructed. A transponder consisting of two antennas and an amplifier is constructed for evaluating the resolution. The images of the transponder and the natural scene are focused well, which can validate the GEO SAR imaging feasibility though the linear track and constant speed assumptions fail.

This paper analyzes the multiangle imaging results for bistatic synthetic aperture radar (BSAR) based on global navigation satellite systems (GNSS-BSAR). Due to the shortcoming of GNSS-BSAR images, a multiangle observation and data processing strategy based on BeiDou-2 navigation satellites was put forward to improve the quality of images and the value of system application. Twenty-six BSAR experiments were conducted and analyzed in different configurations. Furthermore, a region-based fusion algorithm using region-of-interest (ROI) segmentation was proposed to generate a high-quality fusion image. Based on the fusion image, typical targets such as water area, vegetation area, and artificial targets were compared and interpreted among single/multiple-angle images. The results reveal that the multiangle imaging method was a good technique to enhance image information, which might extend the applications of GNSS-BSAR.

This paper presents the theory, algorithm, and results of a new bistatic interferometry synthetic aperture radar (InSAR) method. It employs the data acquired in an innovative bistatic configuration, which uses the orbital sensors as transmitters of opportunity and the stationary receivers on the ground, to generate a digital elevation model (DEM). In the bistatic spaceborne/stationary InSAR configuration, the interferometric phase only depends on the target-receiver range, which could not be obtained directly from the measured bistatic range. Therefore, the conventional transforming relationship between the interferometric phase and the topographic height is no longer practical. In order to solve the problem, we introduce a new conversion relationship between the interferometric phase and the topographic height, which is derived by the model of the ellipsoidal projection in the bistatic configuration. Meanwhile, the error analysis of the new conversion is carried out through a simulation. Both the simulated and measured data are used to test and verify the feasibility of the new bistatic InSAR method. In the spaceborne/stationary InSAR experiment, YaoGan-3 (an L-band spaceborne SAR system launched by China) was selected as the transmitter and two stationary receivers were mounted on the top of a tall building. The generated DEM of high quality shows that the presented method performs very well in the bistatic InSAR data process.

This paper proposes an extended nonlinear chirp scaling (CS) image formation algorithm for the bistatic synthetic aperture radar systems with the squinted transmitter and a fixed receiver. Since the transmitter with the squint mode was adopted in the system, two main problems, i.e., the spatial variance of the frequency-modulation rate and cubic phase terms, were introduced in the image formation algorithm. The former problem was solved by the linearity approximation of parameter$p$and deduced$q$(the second- and third-order coefficients of CS factors in range, which could be used to remove the spatial variation and high-order phase in the range direction) along the range domain while the latter one was compensated by a cubic analytical phase term in the frequency domain. A corresponding experimental hardware system and the bistatic experiments were also described in this paper. Both the simulation and experimental results validated the proposed algorithm.