Monostatic Synthetic Aperture Radar Research Articles

Mining Deformation Monitoring Based on Lutan-1 Monostatic and Bistatic Data

Coal mining leads to surface subsidence, landslides, soil erosion and other problems that seriously threaten the life and property safety of residents in mining areas, and it is urgent to obtain mining subsidence information using high-frequency, high-precision and large-scale monitoring methods. Therefore, this paper mainly studies the deformation monitoring of the Datong mining area using Lutan-1 monostatic and bistatic SAR data. Firstly, the latest Lutan-1 bistatic data are used to reconstruct the DSM, and the interferometric calibration method is used to improve the accuracy of the DSM. Then, the surface deformation monitoring of the mining area is implemented by using DInSAR, SBAS-InSAR and Stacking-InSAR with the reconstructed DSM data and Lutan-1 monostatic SAR data. Finally, the deformation monitoring results are compared with the surface deformation results based on the TanDEM data, and both the results are evaluated using the filed leveling data. Taking 20 images covering the Datong mining area as the data sources, the surface deformation results obtained using different InSAR methods in the mining area were quantitatively evaluated and analyzed. The results indicated that: (1) the DSM obtained using the Lutan-1 bistatic SAR data was assessed and demonstrated with the ICESat laser altimetry data an error of 2.8 m, which meets the Chinese 1:50,000 scale DEM cartographic accuracy standard, and the difference analysis with the TanDEM data shows that the terrain changes are mainly distributed in mountainous areas; (2) Due to the improvement in resolution, the registration accuracy of the SAR images and LT-DSM is higher than that of the TanDEM data in the range direction and azimuth direction; (3) Via evaluation with the filed leveling data, it is found that the surface deformation measurement results based on LT-DSM are less affected by terrain, and the accuracy of LT-DSM-SBAS and LT-DSM-DInSAR is improved by 11.5% and 16.3%, respectively, compared with TanDEM-SBAS and TanDEM-DInSAR, which demonstrates the effectiveness of the Lutan-1 bistatic and monostatic data for mine deformation monitoring.

First Assessment of Bistatic Geometric Calibration and Geolocation Accuracy of Innovative Spaceborne Synthetic Aperture Radar LuTan-1

LuTan-1 (LT-1) is a bistatic synthetic aperture radar (BiSAR) system consisting of two identical L-band SAR satellites. The bistatic mode of LT-1 plays a critical role in generating high-precision digital elevation models (DEMs), which requires precise geometric calibration of initial range and azimuth times for both SARs to ensure the reliability and quality of geolocation. However, existing geometric calibration methods predominantly focus on monostatic SAR systems, with limited literature on slave SAR calibration in bistatic systems. This research addresses this gap by establishing geometric calibration models for both SARs based on signal echo history and the range–Doppler model. The geometric errors are effectively resolved using corner reflector data from Xinjiang, China. Through statistical analysis of LT-1 SAR images acquired between July and November in bistatic mode, this paper has demonstrated range delay accuracy of better than 5 ns and azimuth time accuracy of better than 0.1 ms. This level of precision translates into a positional accuracy better than 0.8 m. The proposed models have been successfully applied to geometric calibration, providing precise geolocation for LT-1, thus enhancing its utility for a wide range of Earth observation applications. This paper is the first endeavor to present the assessment of the geometric calibration and geolocation accuracy of LT-1 and discuss the results of the bistatic geometric calibration of the master and slave SARs in a BiSAR formation.

A Monostatic Forward-Looking Staring Spotlight SAR Raw Data Generation and Hybrid-Domain Image Formation Modifications Based on Extended Azimuth Nonlinear Chirp Scaling Autofocusing

Forward-looking staring spotlight synthetic aperture radar (FSS-SAR) offers operational advantages over conventional squinted SAR counterparts. However, due to its complex observation configuration, pixel anomalies occur when processing raw data. For instance, in the forward-looking geometry, symmetrically distributed point scatterers along the flight path have the same Doppler history, resulting in azimuth ambiguities, whereas staring observation narrows and skews the 2D received spectrum, reducing signal orthogonality and causing spectral folding. As a result, not only is the Doppler frequency gradient too small to be precisely measured in the FSS-SAR mode, limiting the ability to achieve high azimuth angular resolution, but it also suffers from azimuth ambiguities when forming an image. To overcome such azimuth-variant characteristics known as inherent resolutional anomalies, a hybrid-domain image formation algorithm (IFA) based on azimuth scaling is modified here. As an approach, radiometric bias correction (RBC) techniques in conjunction with an extended azimuth nonlinear chirp scaling (ANCS) algorithm capable of equalizing range space variance in the azimuth direction, which benefits from an embedded autofocusing step, have been designed for raw data processing. Given the fact that the platform experiences trajectory deviations under a real-flight condition compared to an ideal trajectory, a pre-processing motion compensation (MOCO) step based on Kalman filtering is included within the IFA. The entire proposed IFA solution tackled the inherent resolutional anomalies of FSS-SAR and succeeded in reconstructing the focused image without azimuthal anomalies. To further assess the IFA, a modified Cartesian back-projection (BP) algorithm was developed along with other objective evaluation scenarios, all of which confirm that the proposed hybrid-domain extended ANCS algorithm is valid for the FSS-SAR application.

A Modified NLCS Algorithm for High-Speed Bistatic Forward-Looking SAR Focusing with Spaceborne Illuminator

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

Joint Clutter Suppression and Moving Target Indication in 2-D Azimuth Rotated Time Domain for Single-Channel Bistatic SAR

Moving target indication (MTI) in bistatic synthetic aperture radar (BiSAR) is a promising task in both civilian and military fields. However, it suffers severe challenges under the influence of clutter. MTI in BiSAR mainly faces three challenges: 1) the range cell migration (RCM) of BiSAR is larger than that of monostatic synthetic aperture radar; 2) the clutter range-Doppler spectrum is severely extended; and 3) the clutter characteristic is closely related to geometrical configuration, with nonhomogeneity and nonstationarity. To solve these problems, based on single-channel BiSAR, a joint clutter suppression and MTI method is proposed. First, to ensure that the energy of an arbitrary target is concentrated in one range cell, RCM correction (RCMC) is completed by the first-order keystone transform (KT) and high-order RCMC. Then, an important step named increased dimension rotation (IDR) is applied, which mainly consists of two stages. One is increased dimension processing, which introduces a 2-D azimuth rotated time domain (ARTD). The other is rotation processing, which makes signals in one range cell rotated to 2-D ARTD. After that, the distribution characteristic between the moving target and stationary clutter in 2-D ARTD is analyzed. Next, an optimal filter for clutter suppression is designed according to the characteristics of signal distribution in 2-D ARTD. Furthermore, the corresponding inverse IDR processing and fractional Fourier transform (FrFT) are performed, and finally, MTI can be realized accurately. Generally, the proposed method has good robustness and low system complexity, and its effectiveness is proven by numerical simulations.

Monostatic-Equivalent Algorithm via Taylor Expansion for BiSAR Ship Target Imaging

It is well known that the bistatic synthetic aperture radar (BiSAR) can obtain high-resolution imaging in the forward direction of radar, which is not possible with the conventional monostatic SAR systems. However, most studies on BiSAR imaging mainly focus on stationary targets, and the research on moving targets and ship targets is relatively scarce. In this article, a monostatic-equivalent (ME) algorithm via Taylor expansion for BiSAR imaging of ship target is proposed. The monostatic equivalence method based on Taylor expansion is adopted to approximate BiSAR to monostatic model; besides, the method based on the midpoint of baseline is also analyzed for comparison. Then, the hybrid SAR-ISAR technology is utilized for ship target imaging under the ME model. Finally, the experimental results are given to substantiate the effectiveness and robustness of the proposed algorithm.

An Extended Frequency Scaling Algorithm for Bistatic SAR With High Squint Angle

Bistatic synthetic aperture radar (BiSAR) is an extended and complementary observation method to conventional monostatic SAR remote sensing. When high range and azimuth resolution are required in BiSAR, the transmitting platform, i.e., the LEO satellite, should work in the spotlight or sliding spotlight mode, which means a wide bandwidth Chirp signal is transmitted, and the targets are illuminated for a long enough time as well. In order to reduce the sampling frequency in the receiving system and improve the efficiency of the focusing procedure for this BiSAR configuration, the echoes should be dechirp received. A bistatic extended frequency scaling algorithm (Bi-EFSA) is proposed in this paper to deal with the dechirp received bistatic SAR echoes. The first step of Bi-EFSA is the range walk correction in the 2-D time domain, which reduces the space variance of the range curvatures and removals the serious coupling between range and azimuth caused by the high squint angle. After that, the range compression is achieved by secondary range compression (SRC) and bulk shift. Then, the space variance of the azimuth frequency modulation rate, introduced by the range walk correction step, is corrected by implementing the azimuth nonlinear chirp scaling (ANCS) operation. Following this, the focused results in the range frequency and azimuth time domain are obtained by the azimuth compression. The point targets and extended-scene simulations validate the effectiveness of the proposed algorithm.

Deep Learning for Mapping Tropical Forests with TanDEM-X Bistatic InSAR Data

The TanDEM-X synthetic aperture radar (SAR) system allows for the recording of bistatic interferometric SAR (InSAR) acquisitions, which provide additional information to the common amplitude images acquired by monostatic SAR systems. More concretely, the volume decorrelation factor, which can be derived from the bistatic interferometric coherence, is a reliable indicator of the presence of vegetation and it was used as main input feature for the generation of the global TanDEM-X forest/non-forest map, by means of a clustering algorithm. In this work, we investigate the capabilities of deep Convolutional Neural Networks (CNNs) for mapping tropical forests at large-scale using TanDEM-X InSAR data. For this purpose, we rely on a U-Net architecture, which takes as input a set of feature maps selected on the basis of previous preparatory works. Moreover, we design an ad hoc training strategy, aimed at developing a robust model for global mapping purposes, which has to properly manage the large variety of different acquisition geometries characterizing the TanDEM-X global data set. In addition to detecting forest/non-forest areas, the CNN has also been trained to detect water surfaces, which are typically characterized by low values of coherence. By applying the proposed method on single TanDEM-X images, we achieved a significant performance improvement with respect to the baseline clustering approach, with an average F-score increase of 0.13. We then applied such a model for mapping the entire Amazon rainforest, as well as the other tropical forests in Central Africa and South-East Asia, in order to test its robustness and generalization capabilities, and we observed that forests are typically well detected as contour closed regions and that water classification is reliable, too. Finally, the generated maps show a great potential for mapping temporal changes occurring over forested areas and can be used for generating large-scale maps of deforestation.

Polarimetric analysis of L-band DFSAR data of Chandrayaan-2 mission for ice detection in permanently shadowed regions (PSRs) of lunar South polar craters

To confirm the presence of water on the moon, many scientists of the world are making continuous efforts through remote sensing data of different missions. In this direction, the Dual Frequency Synthetic Aperture Radar (DFSAR) sensor of the Chandrayaan-2 mission adds a very important chapter which is the world's first Planetary SAR mission of fully polarimetric capability with L- and S-band. This study utilizes the L-band fully polarimetric DFSAR data of Chandrayaan-2 mission for the PolSAR parameters-based analysis and ice detection in permanently shadowed regions (PSRs) of the lunar South Polar craters. The PSR IDs SP_875930_3125710, SP_837670_3387710, and SP_874930_3578760 of the lunar South Pole were selected for the polarimetric analysis using DFSAR L-band. Based on previous studies ((Li et al., 2018), two out of three PSR Ids (SP_875930_3125710 and SP_874930_3578760) were easy to identify for surface ice. That is why only two PSR IDs were used for polarimetric SAR analysis of DFSAR data for surface ice characterization and detection. The hybrid polarimetric simulation was also performed to the fully polarimetric L-band data to study stokes vectors and associated child parameters for the selected study area. The analysis of polarimetric distortions confirms the persistence of the polarimetric quality of the SAR data and for this, the polarimetric distortion analysis was performed with co-pol and cross-pol channels. Wave dichotomy-based Huynen decomposition and Barnes decomposition models were implemented to the fully polarimetric quad-pol DFSAR data. The eigenvalue-eigenvector-based decomposition model was also implemented to characterize the scattering behavior of the PSRs. A high correlation was obtained between Circular Polarization Ratio (CPR), entropy, and alpha for the 200 hundred points randomly collected from the image. Diversity index also showed a high positive correlation with CPR. The polarimetric quality of the data was evaluated with the scatterplot between the cross-polarimetric channels and it was observed that the L-band quad-pol data of DFSAR satisfies the criteria for PolSAR data of a monostatic SAR system. Analysis of the results obtained from the polarimetric SAR data indicated that the high volumetric scattering and CPR for the PSR ID SP_875930_3125710 may be due to ice clusters within the permanently shadowed region. Polarimetric analysis of the PSR (SP_874930_3578760) at Howarth Crater using L-band DFSAR data shows a low amount of volumetric scattering and a low CPR for most locations in the PSR. The different ranges of CPR and volume scattering for both craters indicate that polarimetric parameters and indices should be studied in conjunction with geomorphological parameters of the lunar surface, for unambiguous identification of surface ice clusters in the PSR.

An Autofocus Scheme of Bistatic SAR Considering Cross-Cell Residual Range Migration

Benefiting from the capability of forward-looking imaging, ability of receiver radio silence and resistance of jamming, bistatic SAR has extensive potential applications. However, due to its independent dual platform movement, motion error of bistatic SAR is usually more complicated than monostatic SAR and could easily exceed range resolution cell, which will result in both azimuth and range defocusing if not properly compensated. In this paper, an autofocus scheme for bistatic SAR considering cross-cell residual range migration is proposed. In this scheme, cross-cell residual range migration is firstly compensated by estimating bistatic range error through time-frequency analysis. Meanwhile, azimuth phase error is coarsely compensated by using bistatic range error estimation result. Secondly, maximum image sharpness autofocus method is cascaded to further compensate for azimuth residual phase error and enhance the quality of bistatic SAR image. The effectiveness of proposed scheme is verified by simulation and experiment results.

Sidelobe Control for Bistatic SAR Imaging

This letter presents coherent and incoherent nonlinear apodization methods for bistatic synthetic aperture radar (SAR) imaging. The methods are developed on the principle of nonlinear apodization for monostatic SAR imaging and a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\omega \,\,-\,\,k$ </tex-math></inline-formula> relationship representing the bistatic region of support. This relationship plays an important role in designing 2-D windows for the apodization methods. The simulation results show that the presented apodization methods work efficiently with bistatic SAR imaging. In the experiment with a coherent dual apodization (CDA) method presented in this letter, the sidelobe attenuates very fast, and the peak sidelobe is reduced about 16 dB, while the resolutions in azimuth and range are maintained.

Change Detection for Monostatic Pursuit SAR GMTI—Theories and Experimental Results

Monostatic pursuit refers to the operating mode formed by two monostatic SAR systems that follow an identical orbit with a separation in time of several seconds. The detected changes between SAR scenes with several seconds time difference are most likely the changes caused by ground moving targets. Hence, this operating mode opens an opportunity to detect ground moving targets by SAR change detection methods. The paper investigates this possibility to detect ground moving targets using change detection and to combine change detection and GMTI for GMTI. In this combination, a GMTI method will help to classify the detected changes obtained with a change detection method. Some GMTI results are provided in the paper based on the measurements in the monostatic pursuit mode with deployed targets, conducted by TerraSAR-X and TanDEM-X in Sweden in early 2015.

Time-Domain and Monostatic-like Frequency-Domain Methods for Bistatic SAR Simulation.

In recent years, an increasing interest has been devoted to bistatic SAR configurations, which can be effectively used to improve system performance and/or to increase the amount of physical information retrievable from the observed scene. Within this context, the availability of simulation tools is of paramount importance, for both mission planning and processing algorithm verification and testing. In this paper, a time domain simulator useful to obtain the point-spread function and the raw signal for the generic bistatic SAR configuration is presented. Moreover, we focus on the case of two bistatic configurations, which are of considerable interest in actual SAR applications, i.e., the translational invariant SAR and the one-stationary SAR acquisition geometries, for which we obtain meaningful expressions of the Transfer Functions. In particular, these expressions are formally equal to those obtained for the monostatic SAR configuration, so that the already available monostatic simulator can be easily adapted to these bistatic cases. The point-target raw signals obtained using the (exact) time domain simulator and the (approximated) frequency domain one are compared, with special attention to acquisition geometries that may be of practical interest in Formation-Flying SAR applications. Results show that the phase difference between raw signals simulated with the two approaches is, in all cases, smaller (and often much smaller) than about 10 degrees, except that at the very edge of the raw signals, where however, it does not exceed about 50 degrees.

A Novel Motion Compensation Algorithm Based on Motion Sensitivity Analysis for Mini-UAV-Based BiSAR System

Mini-unmanned aerial vehicle (UAV)-based bistatic synthetic aperture radar (BiSAR) is widely used due to its flexibility of system topology selection and simplicity. However, the motion compensation (MOCO) of the system is more difficult because the perturbance of mini-UAV platforms is greater and the spatial variance is more complex. In addition, the degrees of freedom of motion error are twice as those of the monostatic SAR. In this article, a novel MOCO algorithm based on a motion sensitivity model is proposed. First, a BiSAR system motion sensitivity model is established to assess the importance of each motion component error. Second, a novel MOCO method is proposed based on the determination of the main motion errors. Third, the proposed algorithm is validated by both simulations and real data sets. The final well-focused image suggests that the variant phase error after compensation with the new algorithm is much smaller than that with the traditional one.

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.

Mixed Compressive Sensing Back-Projection for SAR Focusing on Geocoded Grid

This article presents a new scheme called 2-D mixed compressive sensing back-projection (CS-BP-2D), for synthetic aperture radar (SAR) imaging on a geocoded grid, in a single measurement vector frame. The back-projection linear operator is derived in matrix form and a patched-based approach is proposed for reducing the dimensions of the dictionary. Spatial compressibility of the radar image is exploited by constructing the sparsity basis using the back-projection focusing framework and fast solving the reconstruction problem through the orthogonal matching pursuit algorithm. An artifact reduction filter inspired by the synthetic point spread function is used in postprocessing. The results are validated for simulated and real-world SAR data. Sentinel-1 C-band raw data in both monostatic and space-borne transmitter/stationary receiver bistatic configurations are tested. We show that CS-BP-2D can focus both monostatic and bistatic SAR images, using fewer measurements than the classical approach, while preserving the amplitude, the phase, and the position of the targets. Furthermore, the SAR image quality is enhanced and also the storage burden is reduced by storing only the recovered complex-valued points and their corresponding locations.

A 3-D Novel Fast Back-Projection Imaging Algorithm for Stratified Media Based on Near-Field Monostatic and Bistatic SAR

A fast back-projection (FBP) imaging algorithm is proposed to generate 3-D uniformly balanced images of an object embedded in a layered structure based on a combined near-field monostatic and bistatic synthetic aperture radar (SAR) system. The spectral layered Green's function is used in the FBP algorithm. Like conventional real-time imaging algorithms, the complexity of the imaging function is reduced via the stationary phase method, and the fast Fourier transform is implemented to accelerate the computation. Unlike conventional real-time imaging algorithms, the singularity problem associated with Green's function and antenna pattern is solved in this proposed algorithm by using a point spread function (PSF). For a real-time imaging system, besides fast image generation, an efficient data acquisition is needed. A combined monostatic and bistatic SAR configuration is used here to decrease the data collection time. The performance of this proposed FBP method is demonstrated by measurements of a stratified environment.

A Bistatic Analytical Approximation Model for Doppler Rate Estimation Error from Real-Time Spaceborne SAR Onboard Orbit Determination Data

Real-time spaceborne bistatic SAR imaging could significantly reduce the whole processing time and can enhance the spaceborne SAR mission availability. Onboard real-time SAR imaging relies on the Doppler parameters estimated from the real-time onboard orbit determination system (OODS) measurement, whose accuracy level is not comparable to the orbit ephemeris data in ground-based SAR processing. The investigation of the impact of error in real-time OODS measurements on bistatic SAR image quality is necessary, and it can help to clarify the key parameter limits of the real-time OODS. The monostatic analytical approximation model (MonoAAM) for spaceborne SAR reduces simulation complexity and processing time compared to the widely used numerical simulation method. However, due to the different configurations between spaceborne bistatic and monostatic SAR, simply applying the MonoAAM on spaceborne bistatic SAR cannot guarantee the desired result. A bistatic analytical approximation model (BiAAM) for Doppler rate estimation error from real-time OODS measurement in real-time spaceborne bistatic SAR imaging is proposed for characterizing the estimation error. Selecting quadratic phase error (QPE) as an evaluation variable, the proposed BiAAM model can provide QPE estimation results for each position of the satellite in its orbit and the maximum QPE estimation for the whole orbit, while revealing the different process of OODS measurement error transferring to QPE in spaceborne bistatic SAR. The correctness and reliability of BiAAM are evaluated by comparing the result with a Monte Carlo numerical simulation method. With the supporting result from BiAAM, the concept and early-stage development of a real-time onboard bistatic SAR imaging mission could be possibly benefited.

Using an Equivalence-Based Approach to Derive 2-D Spectrum of BiSAR Data and Implementation Into an RDA Processor

An equivalent range equation with a monostatic equivalent component and a bistatic synthetic aperture radar (BiSAR) compensation component was proposed. There were five monostatic equivalent parameters (MEPs) in the both components. With the MEPs, a BiSAR range equation can be expressed in a form similar to the monostatic SAR (MoSAR) expression. Then, by using the range equation and the principle of stationary phase (POSP), we analytically derive the 2-D spectrum of a point target, and this 2-D spectrum is implemented into the range Doppler algorithm (RDA) that processes the translational invariant (TI) BiSAR data. In our RDA, spatially variant range cell migration (RCM) correction and azimuth compression (AC), both of which are related to the spatially variant MEPs, are required to focus all targets in the whole scene of different range cells. Simulations under a wide range of imaging parameters are conducted to assess the equivalent range equation and the 2-D spectrums. Satisfactory results are obtained. In addition, traditional methods for motion compensation can be directly applied to our equivalent range equation. Finally, the RDA is evaluated through the analysis of acquired raw BiSAR data. Well-focused images are obtained. Therefore, the proposed equivalent range equation, derived 2-D spectrum, and RDA have been validated for forming imagery using raw BiSAR data.

Image Distortion Characterization due to Equivalent Monostatic Approximation in Near-Field Bistatic SAR Imaging

The $\omega $ – $k$ synthetic aperture radar (SAR) algorithm is a computationally efficient algorithm for near-field 3-D monostatic SAR imaging in nondestructive testing (NDT) applications. However, bistatic measurements are preferred in order to obtain high dynamic range, in particular when real-time imaging arrays are used. This article investigates the image distortion caused by using an equivalent monostatic imaging algorithm for bistatic measurements. Simulations and measurements at millimeter-wave frequencies in the Ka-band (26.5–40 GHz) are used to investigate the resultant image distortion. Furthermore, the image distortion is quantified through the root-mean-square (rms) error, which is calculated as a function of the bistatic transmitter–receiver separation distance, range, and noise power. Simulations and measurements are conducted for imaging using the raster scanning of a pair of antennas and for nonuniform imaging arrays. In addition, an approximate method for phase compensation is introduced to improve the image error from the monostatic approximation of bistatic measurement.