J.M. Yang

South China University of Technology | SCUT

Microwave photonic technology has revolutionized conventional radar systems, enabling the imaging of critical components on non-cooperative airborne targets, such as engines and wings. However, the wide bandwidth and extensive rotation angle of Microwave Photonic Inverse Synthetic Aperture Radar (MWP-ISAR) pose significant challenges for achieving...

Microwave Photonics Inverse Synthetic Aperture Radar (MWP-ISAR) is an emerging imaging radar system that integrates photonics technology. By utilizing low-frequency ultra-wideband signals, MWP-ISAR achieves centimeter-level imaging precision for high-value targets. However, challenges persist when attempting to achieve high-precision imaging of man...

Forward-looking imaging and target detection are highly desirable in many military and civilian fields, such as search and rescue, sea surface surveillance, airport surveillance, and guidance. However, during the processing procedure, imaging and target detection are usually regarded as two independent parts, which means that the imaging result wil...

Geosynchronous synthetic aperture radar (GEO-SAR) can provide long-duration and wide beam coverage over the interested target scene, which is an ideal illuminator for bistatic SAR acquisitions. As a particular system configuration, the GEO bistatic SAR with maneuvering platform as the receiver (GEO-MP-BiSAR) can achieve continuous observation of th...

Parameter extraction of radar signals is an important but challenging task in electronic warfare. In the modern electromagnetic environment, the radiation sources greatly increase, causing different radar signals overlap, making the parameter extraction of radar signals difficult. Meanwhile, using radar signal parameter extraction methods that are...

Sea clutter suppression plays a crucial role in maritime moving target indication. However, in the bistatic SAR (BiSAR) system, traditional space-time adaptive processing (STAP) method can’t satisfy the expected performance due to severe range cell migration (RCM), Doppler frequency migration (DFM), nonstationary clutter, and spatio-temporal spectr...

Automatic target recognition (ATR) holds a crucial position in synthetic aperture radar (SAR) image interpretation. Despite deep learning advancements have significantly propelled SAR ATR, addressing the challenge of target recognition with a few training data remains a vital concern in SAR applications. Two main issues still exist: 1) In few-shot...

To enable the synthetic aperture radar (SAR) automatic target recognition (ATR) system to continuously adapt to new recognition scenarios, it is necessary to equip the system with the ability to quickly update models. However, when these models learn new tasks, the knowledge of old tasks is quickly forgotten, a phenomenon known as catastrophic forg...

Synthetic Aperture Radar (SAR) is widely used in various fields due to its all-weather and all-day working characteristics. With the increasing use of SAR on small platforms, SAR is facing a series of problems due to the large volume of echo data. Imaging methods based on compressed sensing (CS) use the sparsity prior of the scene to reconstruct im...

Synthetic aperture radar automatic target recognition (SAR ATR) methods often struggle due to inadequate training data. In this letter, we introduce a causal interventional ATR method (CIATR), specifically designed to address the challenges posed by limited synthetic aperture radar (SAR) data. This approach is key in revealing the underlying causal...

Deep neural networks have shown remarkable effectiveness in SAR target recognition. However, the explainability problem for deep neural networks remains insufficiently addressed. One approach to tackle this challenge is the SHAP method. It enhances the explainability of deep neural networks in SAR target recognition by observing how the target, sha...

High-resolution Synthetic Aperture Radar (HR-SAR) is extensively used in ground remote sensing applications, including disaster monitoring and resource crop assessment. This is attributed to its exceptional high-resolution imaging capabilities. Microwave photonics technology plays a crucial role in enhancing the performance of SAR systems. It enabl...

Synthetic aperture radar (SAR) target recognition plays an indispensable role in interpreting SAR images. However, differences in radar parameters (including factors such as imaging modes and imaging angles) often lead to resolution differences between training and test data, posing challenges for existing methods in recognizing SAR targets under c...

Deconvolution methods can be applied in airborne scanning radar to enhance its angular resolution for improving the collision avoidance ability in forward-looking direction. However, as the movement speed of the airborne platform increases, the traditional convolution signal model cannot be applied because of the model errors in the amplitude profi...

Frequency modulation continuous wave (FMCW) radar has been paid much attention in forward-looking navigation applications because of its no-blind-range capability. However, after dechirp processing, pulse interference signals may appear in the range time domain, which seriously pollutes the whole radiation direction. In this paper, a cross domain l...

The accurate estimation of target scattering characteristics is deemed crucial in modern remote sensing technology, wherein valuable prior information is provided for radar applications such as target recognition and auxiliary imaging. Ultra- wideband signals with high signal-to-noise ratios can be generated by Microwave photonic radar (MWP), allow...

Bistatic synthetic aperture radar (BiSAR) has high geometric diversity and can obtain the target information from different observation angles. With the ability of azimuth beam steering for both platforms, different bistatic imaging modes can be implemented to achieve better cooperation of beam footprints for enhanced imaging performance. For the m...

Raw data simulation is very important for system parameter design, performance evaluation and route planning of bistatic synthetic aperture radar(SAR). However, most conventional simulation methods focus on improving the efficiency of echo simulation, without considering the impact of terrain fluctuations, resulting in insufficient fidelity of simu...

This letter presents a novel method to resolve the ambiguity in forward-looking radar systems. Traditional methods for ambiguity suppression face challenges with antenna deviations and the ill-conditioning of measurement matrices. To address these limitations, we introduce a deviation-adaptive unfolding network (DAUNet), which integrates perturbed...

To overcome the effect of grid mismatch on the superresolution performance, a sparse Bayesian learning-based multichannel radar forward-looking superresolution imaging scheme is proposed in this paper. In the scheme, a coarse imaging grid is initialized firstly, and local grid refinement is performed based on the preliminary estimation results of t...

Due to the scarcity of SAR images, the SAR target recognition can be regarded as few shot problem, one of the solutions is to generate synthetic SAR images by computer simulation. However, the synthetic data is similar but unavailable, because there is a domain gap and distribution differences between synthetic and measured SAR images, causing inab...

Localization and tracking are important components for ground moving target indication (GMTI). The traditional range-Doppler (RD) localization model is always applied to locate stationary targets in bistatic synthetic aperture radar (BiSAR). However, for moving targets, this localization model is no longer applicable due to the strong coupling of p...

Forward-looking scanning radar (FLR) has been widely discussed because of its super-resolution capability. However, for the high-speed radar platform, the super-resolution performance of FLR degrades significantly due to the limited signal model accuracy. In this paper, to observe the azimuth-elevation information of multiple targets based on a hig...

Synthetic aperture radar (SAR) target recognition has entered a new era of intelligence due to the rapid development of deep learning. Naturally, an accompanying challenge arises in countering SAR intelligent target recognition technology and protecting the targets of interest from exposure risks. In this paper, a novel adversarial attack approach...

Two-dimensional (2-D) absolute velocity estimation of moving target is a key challenge for real-aperture scanning radar because 2-D velocity estimation methods suffer from low precision or heavy computation load. For example, the traditional Hough transform-based method can only estimate the along-track velocity with one-order range migration. In t...

Due to its all-day and all-weather capability, Synthetic Aperture Radar (SAR) plays an important role in many remote sensing and monitoring applications. However, conventional SAR image reconstruction methods generally perform undifferentiated imaging, complicating target detection. To address this challenge, we propose a SAR image reconstruction m...

With the echo difference between different channels, the left/right ambiguity in single channel forward-looking SAR can be resolved using dual-channel radar. However, due to the restricted channel resources, existing methods have limited performance of resolving left/right ambiguity, especially in the area along the flight path. In this paper, a no...

Recently, a sparse super-resolution method based on $L_{1}$ iterative reweighted norm (IRN) has been proposed to improve the azimuth resolution of forward-looking radar. However, this method suffers from poor adaptability and high computational complexity due to its noise-sensitive user-parameter and the necessity for high-dimensional matrix inve...

In synthetic aperture radar (SAR) information acquisition, target detection is often performed on the basis of the acquired radar images. Under low signal-to-clutter ratio (SCR) or low signal-to-noise ratio (SNR) conditions, detection by images is likely to cause loss of targets. To address this problem, we propose a joint imaging and target detect...

Restricted by the ill-posed antenna measurement matrix, the conventional smoothed L0 norm algorithm (SL0) fails to enable direct real aperture radar angular super-resolution imaging. This paper proposes a modified smoothed L0 norm (MSL0) algorithm to address this issue. First, as the pseudo-inverse of the ill-posed antenna measurement matrix is req...

Radar countermeasure (RCM) is increasingly important in modern warfare. Fast and accurate jamming decision made by RCM systems can provide timely electronic protection for important or high-value targets. To quickly find jamming policy against the multifunctional radar (MFR), a jamming policy generation scheme via heuristic programming reinforcemen...

The ability of wide-area and fast-revisit observation with beam scanning in both azimuth and elevation dimensions has allowed the airborne real aperture radar to be a hotspot in applications of aircraft formation identification and airborne warning and control system. However, the azimuth-elevation two-dimensional (2-D) angular resolution is limite...

Multistatic airborne SAR (MuA-SAR) benefits from the ability to flexibly adjust the positions of multiple transmitters and receivers in space, which can shorten the synthetic aperture time to achieve the required resolution. To ensure both imaging efficiency and quality of different system spatial configurations and trajectories, the fast factorize...

Convolutional neural networks (CNNs) have achieved high performance in synthetic aperture radar (SAR) automatic target recognition (ATR). However, the performance of CNNs depends heavily on a large amount of training data. The insufficiency of labeled training SAR images limits the recognition performance and even invalidates some ATR methods. Furt...

Although deep learning-based methods have achieved excellent performance on SAR ATR, the fact that it is difficult to acquire and label a lot of SAR images makes these methods, which originally performed well, perform weakly. This may be because most of them consider the whole target images as input, but the researches find that, under limited trai...

Synthetic aperture radar automatic target recognition (SAR ATR) methods fall short with limited training data. In this letter, we propose a causal interventional ATR method (CIATR) to formulate the problem of limited SAR data which helps us uncover the ever-elusive causalities among the key factors in ATR, and thus pursue the desired causal effect...

Synthetic aperture radar automatic target recognition (SAR ATR) with limited data has recently been a hot research topic to enhance weak generalization. Despite many excellent methods being proposed, a fundamental theory is lacked to explain what problem the limited SAR data causes, leading to weak generalization of ATR. In this paper, we establish...

Sufficient synthetic aperture radar (SAR) target images are very important for the development of researches. However, available SAR target images are often limited in practice, which hinders the progress of SAR application. In this paper, we propose an azimuth-controllable generative adversarial network to generate precise SAR target images with a...

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 UA...