Passive Synthetic Aperture Radar Research Articles

A 10.31 ENOB 3.125MHz BW fully passive 2nd-order noise-shaping SAR ADC for low cost IoT sensor networks

A 10.31 ENOB 3.125MHz BW fully passive 2nd-order noise-shaping SAR ADC for low cost IoT sensor networks

EM Scattering Center Model-Guided Passive SAR Deception Using Diverse Frequency Time-Modulation

EM Scattering Center Model-Guided Passive SAR Deception Using Diverse Frequency Time-Modulation

Performance Analysis and System Implementation for Energy-Efficient Passive UAV Radar Imaging System

Due to the superior flexibility and cost-efficiency, unmanned aerial vehicle (UAV) is becoming an indispensable platform for advanced remote sensing applications. In this paper, the performance and implementation of the energy-efficient passive UAV radar imaging system is investigated. Equipped with a synthetic aperture radar (SAR) receiver, the UAV platform passively reuses the backscattered signal of an external illuminator, and achieves SAR imaging and data communication. Firstly, we present the system concept and block diagram. Then, the imaging performance and feasibility are analyzed for the typical illuminators. It is found that the system can achieve distinct mission performance with different kinds of illuminators, which offers more alternatives for various mission requirements. A set of mission performance evaluators is established to comprehensively assess the capability of the system, including UAV navigation, passive SAR imaging and communication. An energy-efficient path planning method is then presented to generate a UAV path with optimized mission performance. Numerical simulations are conducted to verify the effectiveness of the performance evaluators and path planning method. Finally, a real implementation of the system is given. The imaging results of an airborne passive SAR experiment using external illuminator further validates the imaging capability and performance analysis of the system.

Clean processing for direct signal cancellation using sparse representation in passive synthetic Aperture Radar based on DVB-T Signal

Clean processing for direct signal cancellation using sparse representation in passive synthetic Aperture Radar based on DVB-T Signal

GNSS-Based Passive Inverse SAR Imaging

The utilization of global navigation satellite system (GNSS) signals for remote sensing has been a hot topic recently. In this article, the feasibility of the GNSS-based passive inverse synthetic aperture radar (P-ISAR) is analyzed. GNSS-based P-ISAR can generate the two-dimensional image of a moving target, providing an estimation of the target size, which is very important information in target recognition. An effective GNSS-based P-ISAR moving target imaging algorithm is proposed. First, a precise direct path interference (DPI) suppression method is derived to eliminate the DPI power in the detection channel. Then, the P-ISAR signal processing method is established. Due to the large synthetic aperture time, the Doppler profile of the ISAR image will defocus if directly performing the Fourier transform. As a solution, a parametric autofocusing and cross-range scaling algorithm is specially tailored for the GNSS-based P-ISAR. The proposed algorithm cannot only focus and scale the ISAR image, but also provide an estimation of the cross-range velocity of the target. Simulation with an airplane target is designed to test the signal processing method. Finally, an experiment is conducted with a civil airplane as the target and GPS satellites as the illumination source. Focused ISAR image is successfully acquired. The estimated length and velocity of the target are approximately consistent with ground truth, which are obtained by the flight record. The potential of the GNSS-based P-ISAR on multistatic operations is also illustrated by the fusion of the ISAR images obtained using different satellites as illumination sources.

Passive GNSS-based SAR imaging with sub-apertures combination

Passive GNSS-based SAR imaging with sub-apertures combination

Multichannel SDR Platforms for Mobile PCL Applications

This article presents a brief overview of hardware platforms with multiple RF input channels that can be employed in the area of passive coherent location (PCL) and passive synthetic aperture radar. Two families of the platforms are considered, i.e., field-programmable gate array based development boards and general-purpose software-defined radio receivers. Practical solutions that have been validated in field experiments are described: a high-performance four-channel platform and its lightweight version that perfectly suits the needs of low-power moving installations. The preliminary results of target detections are presented, which are obtained from the signals acquired with the lightweight PCL platform. Our results prove that, besides its simplicity, the small and low-power platform can be successfully used in PCL applications that use digital audio broadcasting transmitters as the source of illumination.

SDR-Implemented Passive Bistatic SAR System Using Sentinel-1 Signal and Its Experiment Results

A fixed-receiver mobile-transmitter passive bistatic synthetic aperture radar (MF-PB-SAR) system, which uses the Sentinel-1 SAR satellite as its non-cooperative emitting source, has been developed by using embedded software-defined radio (SDR) hardware for high-resolution imaging of the targets in a local area in this study. Firstly, Sentinel-1 and the designed system are introduced. Then, signal model, signal pre-processing methods, and effective target imaging methods are presented. At last, various experiment results of target imaging obtained at different locations are shown to validate the developed system and the proposed methods. It was found that targets in a range of several kilometers can be well imaged.

Optimal GNSS-Based Passive SAR Large Field-of-View Imaging via Multistatic Configuration: Method and Experimental Validation

In terms of the global coverage provided by global navigation satellite system (GNSS) signals, radar images of a large field-of-view can be obtained via passive synthetic aperture radar (SAR) using these signals of opportunity. Usually, large field-of-view imaging is challenging using conventional SAR methods owing to the space-variant resolution. In addition, only a moderate range resolution can be provided by the GNSS transmitters in the passive SAR system. In this paper, an optimal imaging method for a large field-of-view using GNSS-based passive SAR is proposed, which exploits the inherent multistatic nature of GNSS. At first, the spatial resolution of each scatterer in the observation area relative to each GNSS transmitter is calculated according to the geometry. Then, the selection of the transmitter set is modeled as an optimization problem, where the minimal resolution cell is used as the optimal criterion. After that, an evolutionary algorithm is applied to solve the optimization problem. Finally, the space-time combination of the echoes over a long dwell time concerning selected GNSS transmitters is performed to form the radar image with a minimal spatial resolution. The proposed method is extensively validated using two experimental datasets, where the passive radar consists of BeiDou satellites and a fixed receiver. The spatial resolution improvement and the large field-of-view imaging capability of the proposed method are forcefully demonstrated according to the experimental results.

A Single-Opamp Third Order CT ΔΣ Modulator With SAB-ELD-Merged Integrator and Three-Stage Hybrid Compensation Opamp

This paper proposes a 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> order continuous-time delta-sigma modulator (CTDSM) with a single amplifier biquad (SAB) and excess loop delay (ELD) merged integrator. The integrator enables a 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> order noise-shaping together with ELD compensation with just a single Opamp and feedback DAC. A three-stage Opamp with a hybrid frequency-compensation scheme is presented, which achieves high gain and large unity-gain bandwidth (UGBW) with low power. The circuit secures an extra order noise-shaping through a passive noise-shaping SAR (NS-SAR) quantizer (QTZ) while further incorporating a preliminary sampling and quantization (PSQ) technique, the 1 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> order NS QTZ can run at 1.5 GHz with 6b. The design, implemented in 28 nm, obtains 74.4 dB SNDR with 50 MHz bandwidth while consuming 10.4 mW from 1.5 V and 1 V power supplies. The prototype attains a dynamic range of 80.6 dB with a Schreier FOM of 171.2 dB. With the presented integrator and Opamp, the loop filter only consumes 14 % of the total DSM power consumption.

Performances of the Passive SAR Imaging of Jupiter’s Icy Moons

With the development of the JUICE/RIME (ESA) and Europa-Clipper/REASON (NASA) instruments, designed to study the subsurface of the Galilean moons, interest has been growing to study the performances of sounding radar orbiting these bodies. In the presence of strong Jupiter’s radio emissions, probing in a passive mode using these emissions as the emitter is considered. However, radar performances in this bistatic mode are dependent on the entire geometry of observation: the position of the source of emission, the spacecraft trajectory, and on the region probed. 3D Simulations are necessary to estimate the performances of these measurements. We analyze the influence of the geometry of observation by approximating Jovian radio bursts as radio impulses, simulating the signal scattered by a point target in a realistic 3D geometry and computing the resolution. This allows a preliminary identification of scenarios of observation best suited for this radar mode. The influence of the correct localization of Jupiter’s emissions on the SAR image is investigated as well, and interest in recovering the true position of Jupiter’s source is highlighted.

Optimal Attitude Maneuvering Analyses for Imaging at Squint Staring and Sliding Spotlight Modes of SAR Satellite

In this study, we analyzed the imaging maneuver time, retargeting maneuver time, and attitude maneuvering characteristics in the imaging section (Phase 1) and retargeting maneuver section (Phase 2) when taking multiple-target images in squint spotlight mode in a single pass of a passive SAR satellite. In particular, the synthetic aperture time and attitude maneuvering characteristics in the staring and sliding spotlight modes that can image the wider swath width while maintaining high resolution were compared and analyzed. In the sliding spotlight mode, the rotation center was located below the ground surface when the satellite was maneuvering towards the target. Steering and sliding maneuvers were performed when targeting, and the synthetic aperture time of the sliding spotlight was longer than that of the staring spotlight because overlapping imaging was performed on the point target. The satellite maneuvering during imaging can be considered as a time-fixed problem, because it was performed within synthetic aperture time according to resolution, incidence angle, swath width, etc., by minimizing the Doppler centroid variation. In order to optimize the retargeting maneuver time, an optimal analysis of the attitude maneuvering was carried out and the validity of the optimal analysis algorithm was confirmed. Finally, the scenario was analyzed by assuming a problem of imaging four targets with 5 × 5 km swath width in a 20 km × 20 km densely populated area. It was confirmed that if a squint angle of ±12 degrees is provided in a single pass, four high resolution images of 5 km × 5 km can be imaged in the sliding spotlight mode.

Passive Synthetic Aperture Radar Imaging Using Kalman Reflection Coefficients Estimation Algorithm with DVB-T Signal

In this paper, a new method is presented for image formation in a Multistatic Passive Synthetic Aperture Radar (SAR), whose receiver is moving and transmitters are stationary in a multistatic structure, and the signal used to create the image is DVB-T. The proposed method uses multiple transmitters of opportunity to improve the range resolution of a Passive SAR. First, a linear observation model is developed for multistatic structure of the Passive SAR system. Then, the image of the underlying scene is obtained through a new Kalman-based estimation algorithm. In this algorithm, range migration error is completely corrected, and the use of Kalman recursive filter reduces the computational complexity of the reflection coefficients estimation algorithm. Experimental results indicate that the proposed algorithm is effective.

Passive Synthetic Aperture Radar Imaging Using Radio-Astronomical Sources

Recent work has demonstrated a passive radio sounding approach that uses the Sun as a source for echo detection and ranging. As the Sun is a moving source with a position that is known <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> , we evaluate this technique’s capabilities to measure the echo’s phase history, map topography, and perform synthetic aperture radar (SAR) focusing. Here, we present our approach to implementing passive SAR using a compact, temporally incoherent radio-astronomical source as a signal of opportunity. We first evaluate the passive system’s capabilities to obtain an echo from a rough surface by determining the critical signal-to-noise ratio (SNR) for reliably observing the Sun’s echo reflection with our passive instrument. We then demonstrate that our technique can detect the necessary changes in range, phase, and reflectivity of an echo from the Sun. We next present the experimental results of our passive radar testing using the Sun at Dante’s View, Death Valley, to highlight this technique’s ability to perform 2-D imaging. Finally, with synthetic data, we demonstrate that we can use time-domain backprojection to focus a planar white noise signal, perform passive SAR imaging, and improve the measurement’s SNR and azimuth resolution. The results of passive SAR focusing on white noise highlight the potential for the Sun and Jupiter’s radio emissions to perform surface and subsurface imaging for planetary and terrestrial observations.

Decimetre Level Range Resolution for Beidou B3I Signal-Based Passive SAR Imaging—Proof-of-Concept Experimental Demonstrations

The construction of the Beidou B3 satellite system, a new-generation global navigation satellite system, has been completed worldwide, however the respective implementation studies remain in the start-up stage. Accordingly, studies of passive Beidou B3I signal-based synthetic aperture radar (Beidou B3I-SAR) are very meaningful in terms of promoting the rapid development of the Beidou technique. This paper proposes methods for Beidou B3I SAR imaging of decimetre level range resolution. To separate aliased reflected B3I signals at range domain, we presented cascaded secondary order differentiation operator (Diff2) and cascaded Teager-Kaiser (TK) operator, applied them to the regions where exists range compressed pulses, respectively. Thereafter to eliminate the obvious side-lobes which brought by the proposed operators and with the values less than zero, zero thresholding scheme is employed. To obtain the final range compressed signals with decimetre range resolution, phase recovery component is performed to the respective zero thresholded pulses. To validate the proposed methods, both proof of concept simulation and the experiment with field Beidou B3I signal raw data are carried out for comparison. The results show that indeed main-lobe width of range compressed pulse can reach the level 0.4 m. This reveals that decimetre level range resolution can be achieved for Beidou B3I-SAR on the basis of proposed methods, in contrast to the current best result of meters level in passive GNSS-based SAR related studies. Meanwhile, in a comparison of the proposed methods on the basis of cascaded Diff2 operator and cascaded TK operator, the later is outer-performed, since the respective brought interference level in background region is less.

Sea Ice Concentration Estimation: Using Passive Microwave and SAR Data With a U-Net and Curriculum Learning

Ice concentration estimates are typically acquired from algorithms using passive microwave satellite data, and from image analysis charts, but these have limitations. Estimates acquired from passive microwave data have coarse spatial resolution, may have errors due to atmospheric contamination, and often perform poorly in marginal ice zones. Image analysis charts are not as precise, subject to analyst interpretation, and only available over specific geographic areas. We have implemented a U-net with synthetic aperture radar images as inputs and use ice concentration estimates retrieved from passive microwave data as training labels. The U-net, due to not being sensitive to patch size, is shown to be an improvement over previous work with convolutional neural networks that use fully connected layers at the output. Data augmentation and an L1 loss function were applied along with a novel training scheme that leverages curriculum learning. In this training scheme, the model is first trained with samples from open water and consolidated ice regions before incorporating samples from marginal ice regions. In a tenfold cross validation experiment, we achieve 3–4% mean absolute error comparing to estimates using passive microwave data and observe curriculum learning models having more stable training. Predictions on four with-held SAR scenes with difficult ice conditions were evaluated with image analysis charts. A mean absolute error of 7.18% is achieved, which is lower than errors associated with passive microwave data alone. Qualitative improvements in marginal ice zone estimates are achieved, while still preserving smooth consolidated ice regions, and openings in ice cover.

Retrieval of forest vertical leaf area index and clumping index through field measurement and remote sensing techniques: A review

Forest vertical stratification directly affects the transfer of solar radiation and water evapotranspiration in the canopy. Consequently, leaf photosynthesis varies in different parts of the canopy, affecting the growth of trees and the succession process of the plant community. The vertical distribution of forest structural parameters, such as the leaf area index (LAI) and clumping index (CI), is critical not only for understanding of the forest carbon, nitrogen, and water cycles and remote sensing radiative transfer processes, but also for forest monitoring and management practices. Forest vertical LAI and CI can be obtained through field measurement and remote sensing inversion methods. For field measurements, LAI-2200, digital hemispherical photography, and photosynthetically active radiation sensors are frequently used instruments. Vertical structural measurements are usually carried out through destructive sampling, tower-base measurement, and mobile elevators. In general, field measurements are more accurate; however, they are time-consuming and laborious, making them unsuitable for large-scale applications. Remote sensing technology uses the passive optical method, the light detection and ranging (LiDAR) technology, and synthetic aperture radar (SAR) methods to estimate forest vertical LAI and CI. The classical passive optical method is based on either the empirical vegetation index estimation method or physical model inversion method. The vegetation index method establishes an empirical relationship between vegetation structural parameters and vegetation indices. Subsequently, the relationship is used to estimate the structural parameters for different layers. The physical model inversion method is based on a physical radiative transfer model. In general, the application of both passive optical and SAR methods in forest vertical parameter retrieval is limited. As an active remote sensing technology, the LiDAR technology has shown its unique advantages in the inversion of vertical structural parameters. Based on the platform used, LiDAR can be classified into three categories: Terrestrial laser scanning (TLS), airborne laser scanning (ALS), and spaceborne laser scanning. The basic rationale of the LiDAR technology is based on the Beer-Lambert Law, which estimates canopy LAI and CI from the canopy gap fraction; both empirical statistical and physical inversion methods are used during the process. The use of LiDAR to estimate LAI and CI is gaining popularity worldwide, but most of the research is based on TLS and ALS. The development of new space-based LiDAR technologies, such as the Global Ecosystem Dynamics Investigation on the International Space Station, will greatly advance the acquisition of forest vertical structural information on a global scale. However, the relatively complex operation and data processing requirements have limited its widespread application. The vertical distribution of forest LAI can be represented by the normal, Weibull, beta, chi-square, and Johnson’s S-B distributions. The CI values usually decrease with the increase in canopy height because the upper part of the canopy usually has larger gaps. However, mature global vertical LAI and CI products that can meet the application requirements are currently unavailable. Due to the limits of ground measurements, forest vertical LAI and CI retrieved from remote sensing lack sufficient ground validation. In field measurements, the LAI values of trees, shrubs, and herbs should be acquired simultaneously in order to validate the remote sensing LAI. The development of wireless sensor networks and unmanned aerial vehicles provides convenient and effective methods to obtain a large amount of vertical structural information useful for validation purposes. Forest vertical LAI and CI have been applied in land surface and radiative transfer models and forest management studies. In future research, new field measurement and remote sensing inversion methods should be explored. Various LiDAR data sources can be used to generate high-quality vertical structural products, and these vertical products should be fully validated to better meet the requirements proposed by the research and management communities.

A 2-D Pseudospectral Time-Domain (PSTD) Simulator for Large-Scale Electromagnetic Scattering and Radar Sounding Applications

This article discusses the implementation of a 2-D pseudospectral time-domain (PSTD) full-wave simulator for solving large-scale low-frequency (e.g., HF) electromagnetic (EM) scattering problems with the application of radar sounding of planetary subsurfaces. Compared to other computational EM algorithms, the PSTD solver is both memory-efficient and accurate for sounding applications. New domain designs are developed to efficiently simulate 2-D scattering of half-space media for normal and oblique incidence from arbitrary wave sources. As a validation of the PSTD simulator, the simulated 2-D scattering radar cross width (RCW) is compared with the analytical solutions of both point targets (dielectric cylinders) and distributed targets (random rough surfaces), for the first time, where the frequency and angular (bistatic scattering) dependence are studied with various choices of grid sampling resolution. Furthermore, the PSTD solver is applied to passive synthetic aperture radar (SAR) sounding problems (single transmitter and several receivers), for the first time, where various scenarios (e.g., cylinder, surface, and volume) are demonstrated and the targets are correctly resolved after focusing, indicating an accurate simulation of the phase history. Finally, an example of using the solver is shown for emulating 3-D large-scale radar sounding problems with cross-track surface and subsurface scattering. This is particularly useful to simulate radar sounding returns and SAR-focused imagery of large-scale subsurface structures to better support planetary missions with radar sounding instruments.

Improved Passive SAR Imaging With DVB-T Transmissions

This article investigates passive synthetic aperture radar (SAR) image formation using Terrestrial Digital Video Broadcast (DVB-T) transmitters of opportunity and an airborne receiver. The proposed airborne system does not use separate channels for direct and reflected signal reception. The proposed image formation algorithm suppresses artifacts due to the presence of the direct signal in radar echo data using modified CLEAN method and accounts for unknown irregularities in airborne platform motion using a map-drift autofocus (MDA) technique. The algorithms are theoretically derived and experimentally confirmed via an appropriate airborne campaign, and their experimental performance is measured.

Sparse Imaging-Based Clutter Suppression and Refocusing of MTs in Passive Bistatic SAR

A sparse-imaging-based methodology for the clutter suppression and refocusing of multiple slow-moving targets (MT) in passive bistatic synthetic aperture radar (SAR) is proposed in this paper. The defocused regions of MTs in the bistatic imagery are utilized here. A joint radar projection operator for the static and moving objects is formulated and employed to construct a source separation problem. The Lp norm and square difference maximization constraint are utilized to promote the separation of MT data and the suppression of clutter. After the joint sparse processing, static-scene imagery and MT imagery can be derived simultaneously. Finally, numerical simulations can verify the validity of the proposed methodology.